bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling unique clinical phenotypes of hip fracture patients and the temporal association with cardiovascular events
Authors: Hsu Warrington W. Q. , Zhang Xiaowen , Sing Chor-Wing , Tan Kathryn C. B. , Wong Ian Chi-Kei , Lau Wallis C. Y. , Cheung Ching-Lung 
Published: May 2024

AbstractCardiovascular events are the leading cause of death among hip fracture patients. This study aims to identify subphenotypes of hip fracture patients and investigate their association with incident cardiovascular events, all-cause mortality, and health service utilisation in Hong Kong and the United Kingdom populations. By the latent class analysis, we show three distinct clusters in the Hong Kong cohort (n = 78,417): Cluster 1 has cerebrovascular and hypertensive diseases, hyperlipidemia, and diabetes; Cluster 2 has congestive heart failure; Cluster 3 consists of relatively healthy patients. Compared to Cluster 3, higher risks of major adverse cardiovascular events are observed in Cluster 1 (hazard ratio 1.97, 95% CI 1.83 to 2.12) and Cluster 2 (hazard ratio 4.06, 95% CI 3.78 to 4.35). Clusters 1 and 2 are also associated with a higher risk of mortality, more unplanned accident and emergency visits and longer hospital stays. Self-controlled case series analysis shows a significantly elevated risk of major adverse cardiovascular events within 60 days post-hip fracture. Similar associations are observed in the United Kingdom cohort (n = 27,948). Pre-existing heart failure is identified as a unique subphenotype associated with poor prognosis after hip fractures.
BRAIN - Holocene archaeo-data for assessing plant-cultural diversity in Italy and other Mediterranean regions
Authors: Mercuri Anna Maria , Clò Eleonora , Zappa Jessica , Bosi Giovanna , Furia Elisa , Ricucci Cristina , Di Lena Matteo , Camerini Federico , Florenzano Assunta 
Published: May 2024

AbstractIn the field of botany applied to archaeological and palaeoecological studies, the multi- and inter-disciplinary nature of this research produces a lack of data sharing and scattered articles in the specialty literature or in national and international journals. The vast production of archaeobotany and palynology data makes it necessary to develop a tool for the availability, accessibility, and dissemination of existing research. Many databases exist on palaeoecology, archaeobotany or pollen data. There are no collections focused on archaeological sites and human-induced environments and centred on Southern Europe and the Mediterranean. BRAIN - Botanical Records of Archaeobotany Italian Network is the first database listing sites from which all types of plant records are available in Italy and nearby Mediterranean regions. BRAIN represents the largest integrated collection of archaeo/palaeo-botanical data and a range of descriptive information that makes data recovery FAIR ready. This unique network hosts data on the availability of anthropogenic pollen, palynomorphs and plant macroremains in the same database, and experts of different research fields may contribute to it.
Smart device interest, perceived usefulness, and preferences in rural Alabama seniors
Authors: Anderson Monica 
Published: May 2024

AbstractLimited data exist on the preferences for smart home devices in rural Americans. We examined the interest, usefulness, and pleasantness of various smart home interfaces and determined whether they differed by ethnicity, rurality, age, and gender. A total of 118 older adults living in the rural Deep South completed a survey instrument that assessed interest in various smart home applications and was queried about the perceived usefulness and perceived ease of use of screen, voice, and robot interfaces in 7 distinct scenarios. Personality data was collected via the Big Five Inventory. Technology readiness was measured using a technological readiness instrument. Participants were primarily female (81%), rural (76%), African American (69%), and aged 65-74 years old (51%). Participants were recruited from a total of 5 cities in West Alabama within the Black Belt. Data was collected before COVID-19 (July 2018 through July 2019).
Machine learning models for predicting early hemorrhage progression in traumatic brain injury
Authors: Lee Heui Seung , Kim Ji Hee , Son Jiye , Park Hyeryun , Choi Jinwook 
Published: May 2024

AbstractThis study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predict the risk of ICH progression using initial CT scans and identify clinical factors associated with this progression. A retrospective analysis of TBI patients between January 2010 and December 2021 was performed, focusing on initial CT evaluations and demographic, comorbid, and medical history data. ICH was categorized into intraparenchymal hemorrhage (IPH), petechial hemorrhage (PH), and subarachnoid hemorrhage (SAH). Within our study cohort, we identified a 22.2% progression rate of ICH among 650 TBI patients. The Random Forest algorithm identified variables such as petechial hemorrhage (PH) and countercoup injury as significant predictors of ICH progression. The XGBoost algorithm, incorporating key variables identified through SHAP values, demonstrated robust performance, achieving an AUC of 0.9. Additionally, an individual risk assessment diagram, utilizing significant SHAP values, visually represented the impact of each variable on the risk of ICH progression, providing personalized risk profiles. This approach, highlighted by an AUC of 0.913, underscores the model’s precision in predicting ICH progression, marking a significant step towards enhancing TBI patient management through early identification of ICH progression risks.
Unveiling excitons in two-dimensional $$\beta$$-pnictogens
Authors: Guassi Marcos R. , Besse Rafael , Piotrowski Maurício J. , C. Rêgo Celso R. , Guedes-Sobrinho Diego , da Rosa Andréia Luisa , Cavalheiro Dias Alexandre 
Published: May 2024

AbstractIn this paper, we investigate the optical, electronic, vibrational, and excitonic properties of four two-dimensional $$\beta$$
β
-pnictogen materials—nitrogenene, phosphorene, arsenene, and antimonene—via density functional theory calculations and the Bethe–Salpeter equation. These materials possess indirect gaps with significant exciton binding energies, demonstrating isotropic behavior under circular light polarization and anisotropic behavior under linear polarization by absorbing light within the visible solar spectrum (except for nitrogenene). Furthermore, we observed that Raman frequencies red-shift in heavier pnictogen atoms aligning with experimental observations; simultaneously, quasi-particle effects notably influence the linear optical response intensively. These monolayers’ excitonic effects lead to optical band gaps optimized for solar energy harvesting, positioning them as promising candidates for advanced optoelectronic device applications.
Shaping the energy curves of a servomotor-based hexapod robot
Authors: Brodoline Ilya , Sauvageot Emilie , Viollet Stéphane , Serres Julien R. 
Published: May 2024

AbstractThe advantageous versatility of hexapod robots is often accompanied by high power consumption, while animals have evolved an energy efficient locomotion. However, there are a lack of methods able to compare and apply animals’ energetic optimizations to robots. In this study, we applied our method to a full servomotor-based hexapod robot to evaluate its energetic performance. Using an existing framework based on the laws of thermodynamics, we estimated four metrics using a dedicated test bench and a simulated robotic leg. We analyzed the characteristics of a single leg to shape the energetic profile of the full robot to a given task. Energy saving is improved by 10% through continuous duty factor adjustment with a 192% increase in power maximization. Moreover, adjusting the robot’s velocity by the step length and associating this with gait switching, reduces the power loss by a further 10% at low-speed locomotion. However, unlike in animals, only one unique optimal operating point has been revealed, which is a disadvantage caused by the low energetic efficiency of servomotor-based hexapods. Thus, these legged robots are severely limited in their capacity to optimally adjust their locomotion to various tasks—a counter-intuitive conclusion for a supposedly versatile robot.
Assessment of heavy oil recovery mechanisms using in-situ synthesized CeO2 nanoparticles
Authors: Mehrooz Nafiseh , Gharibshahi Reza , Jafari Arezou , Shadan Behrad , Delavari Hamid , Sadeghnejad Saeid 
Published: May 2024

AbstractThis project investigated the impact of low-temperature, in-situ synthesis of cerium oxide (CeO2) nanoparticles on various aspects of oil recovery mechanisms, including changes in oil viscosity, alterations in reservoir rock wettability, and the resulting oil recovery factor. The nanoparticles were synthesized using a microemulsion procedure and subjected to various characterization analyses. Subsequently, these synthesized nanoparticles were prepared and injected into a glass micromodel, both in-situ and ex-situ, to evaluate their effectiveness. The study also examined the movement of the injected fluid within the porous media. The results revealed that the synthesized CeO2 nanoparticles exhibited a remarkable capability at low temperatures to reduce crude oil viscosity by 28% and to lighten the oil. Furthermore, the addition of CeO2 nanoparticles to the base fluid (water) led to a shift in the wettability of the porous medium, resulting in a significant reduction in the oil drop angle from 140° to 20°. Even a minimal presence of CeO2 nanoparticles (0.1 wt%) in water increased the oil production factor from 29 to 42%. This enhancement became even more pronounced at a concentration of 0.5 wt%, where the oil production factor reached 56%. Finally, it was found that the in-situ injection, involving the direct synthesis of CeO2 nanoparticles within the reservoir using precursor salts solution and reservoir energy, led to an 11% enhancement in oil production efficiency compared to the ex-situ injection scenario, where the nanofluid is prepared outside the reservoir and then injected into it.
Replication stress as a driver of cellular senescence and aging
Authors: Herr Lauren M. , Schaffer Ethan D. , Fuchs Kathleen F. , Datta Arindam , Brosh Robert M. 
Published: May 2024

AbstractReplication stress refers to slowing or stalling of replication fork progression during DNA synthesis that disrupts faithful copying of the genome. While long considered a nexus for DNA damage, the role of replication stress in aging is under-appreciated. The consequential role of replication stress in promotion of organismal aging phenotypes is evidenced by an extensive list of hereditary accelerated aging disorders marked by molecular defects in factors that promote replication fork progression and operate uniquely in the replication stress response. Additionally, recent studies have revealed cellular pathways and phenotypes elicited by replication stress that align with designated hallmarks of aging. Here we review recent advances demonstrating the role of replication stress as an ultimate driver of cellular senescence and aging. We discuss clinical implications of the intriguing links between cellular senescence and aging including application of senotherapeutic approaches in the context of replication stress.
Shoreline retreat and beach nourishment are projected to increase in Southern California
Authors: Amrouni Oula , Heggy Essam , Hzami Abderraouf 
Published: May 2024

AbstractSandy beaches in Southern California are experiencing rising coastal erosion due to changes in precipitation patterns and urban growth. As a result, beach nourishment is necessary for mitigation. In our study, we forecast the rates of shoreline retreat and the required volumes of sand nourishment to mitigate it for the coming decades. We employ photogrammetric multi-decadal shoreline positioning and Digital Shoreline Analysis System methods to measure and predict the coastal evolution of the Gulf of Santa Catalina in Southern California. This region is hypothesized to be globally representative of other semi-arid sandy coasts facing similar hydroclimatic and anthropogenic challenges. Our findings indicate that Southern California’s shoreline retreat rates for sandy beaches will increase from the present average value of ~−1.45 to −2.12 meters per year in 2050 and to −3.18 meters per year in 2100. Consequently, the annual volume of sand required for beach nourishment could triple by 2050, increasing from the present-day amount of ~1223 to ~3669 cubic meters per year per kilometer. However, the associated cost for this nourishment will grow five times, exacerbating several coastal communities’ economic and logistical pressures. Similar trends are emerging globally, with semi-arid developing nations already grappling with coastal hazards and may struggle to manage the escalating costs of curbing beach nourishment.
Evidence of direct and indirect reciprocity in network-structured economic games
Authors: Redhead Daniel , Gervais Matthew , Kajokaite Kotrina , Koster Jeremy , Hurtado Manyoma Arlenys , Hurtado Manyoma Danier , McElreath Richard , Ross Cody T. 
Published: May 2024

AbstractFormal theoretical models propose that cooperative networks can be maintained when individuals condition behavior on social standing. Here, we empirically examine the predictions of such models of positive and negative indirect reciprocity using a suite of network-structured economic games in four rural Colombian communities (Nind = 496 individuals, Nobs = 53,876 ratings/transfers). We observe that, at a dyadic-level, individuals have a strong tendency to exploit and punish others in bad standing (e.g., those perceived as selfish), and allocate resources to those in good standing (e.g., those perceived as generous). These dyadic findings scale to a more generalized, community level, where reputations for being generous are associated with receipt of allocations, and reputations for being selfish are associated with receipt of punishment. These empirical results illustrate the roles that both positive and negative reciprocity, and costly punishment, play in sustaining community-wide cooperation networks.
Circadian regulation of macromolecular complex turnover and proteome renewal
Authors: Seinkmane Estere , Edmondson Anna , Peak-Chew Sew Y , Zeng Aiwei , Rzechorzek Nina M , James Nathan R , West James , Munns Jack , Wong David CS , Beale Andrew D , O’Neill John S 
Published: May 2024

AbstractAlthough costly to maintain, protein homeostasis is indispensable for normal cellular function and long-term health. In mammalian cells and tissues, daily variation in global protein synthesis has been observed, but its utility and consequences for proteome integrity are not fully understood. Using several different pulse-labelling strategies, here we gain direct insight into the relationship between protein synthesis and abundance proteome-wide. We show that protein degradation varies in-phase with protein synthesis, facilitating rhythms in turnover rather than abundance. This results in daily consolidation of proteome renewal whilst minimising changes in composition. Coupled rhythms in synthesis and turnover are especially salient to the assembly of macromolecular protein complexes, particularly the ribosome, the most abundant species of complex in the cell. Daily turnover and proteasomal degradation rhythms render cells and mice more sensitive to proteotoxic stress at specific times of day, potentially contributing to daily rhythms in the efficacy of proteasomal inhibitors against cancer. Our findings suggest that circadian rhythms function to minimise the bioenergetic cost of protein homeostasis through temporal consolidation of protein turnover.
Calibrated confidence learning for large-scale real-time crash and severity prediction
Authors: Islam Md Rakibul , Wang Dongdong , Abdel-Aty Mohamed 
Published: May 2024

AbstractReal-time crash and severity prediction is a complex task, and there is no existing framework to predict crash likelihood and severity together. Creating such a framework poses numerous challenges, particularly not independent and identically distributed (non-IID) data, large model sizes with high computational costs, missing data, sensitivity vs. false alarm rate (FAR) trade-offs, and real-world deployment strategies. This study introduces a novel modeling technique to address these challenges and develops a deployable real-world framework. We used extensive real-time traffic and weather data to develop a crash likelihood prediction modeling prototype, leveraging our preliminary work of spatial ensemble modeling. Next, we equipped this spatial ensemble model with local model regularization to calibrate model confidence training. The investigated regularizations include weight decay, label smoothing and knowledge distillation. Furthermore, post-calibration on model outputs was conducted to improve severity rating identification. We tested the framework to predict crashes and severity in real-time, categorizing crashes into four levels. Results were compared with benchmark models, real-world deployment mechanisms were explained, traffic safety improvement potential and sustainability aspects of the study were discussed. Modeling results demonstrated excellent performance, and fatal, severe, minor and PDO crash severities were predicted with 91.7%, 83.3%, 85.6%, and 87.7% sensitivity, respectively, and with very low FAR. Similarly, the viability of our model to predict different severity levels for specific crash types, i.e., all-crash types, rear-end crashes, and sideswipe/angle crashes, were examined, and it showed excellent performance. Our modeling technique showed great potential for reducing model size, lowering computational costs, improving sensitivity, and, most importantly, reducing FAR. Finally, the deployment strategy for the proposed crash and severity prediction technique is discussed, and its potential to predict crashes with severity levels in real-time will make a substantial contribution to tailoring specific strategies to prevent crashes.
Nicht kleinzelliges Lungenkarzinom – Vorreiter der personalisierten Onkologie
Authors: Saalfeld Felix Carl , Aust Daniela E , Wermke Martin 
Published: May 2024

ZUSAMMENFASSUNGBei keiner anderen Krebserkrankung ist die klinische Praxis so nah an den Idealen der personalisierten Onkologie wie in der Behandlung des nicht kleinzelligen Lungenkarzinoms (NSCLC). Wir stellen hier kurz die Grundprinzipien der molekularen Analyse dar. Der Fokus des Artikels liegt auf dem klinischen Nutzen der Therapie. Schließlich zeigen wir die Herausforderungen für das ärztliche Personal und strukturelle Lösungsansätze auf.
Ein Gewichtsreduktionskurs mit dem Schwerpunkt der Stärkung von
„Coping“ Strategien für die low carb Ernährung ist einfach und
erfolgreich
Authors: Lilienfeld-Toal Anna. v. , Tews Dietrich , Lilienfeld-Toal Hermann v. 
Published: May 2024

ZusammenfassungEin Weg zur Reduzierung des Körpergewichts besteht in der Reduktion der Aufnahme
von Kohlenhydraten mit der Nahrung, sodass geringere postprandiale Anstiege von
Blutglukose und Insulin auftreten. Allerdings führt die Senkung der Blutglukose
zu starken Impulsen in der Regulation der Nahrungsaufnahme. So werden
verschiedene Essimpulse bei Menschen mit Übergewicht ausgelöst, die
Kohlenhydrate in der Nahrung vermeiden. Wir stellten diese Impulse zusammen und
entwickelten ein systematisches Vorgehen, um ihnen zu begegnen. Hiermit bildeten
wir ein Curriculum für einen 1-Jahres-Kurs mit Übergewichtigen, die sich eine
Gewichtsreduktion vornahmen. Die Gruppensitzungen wurden von einer geschulten
Person geleitet. Im Curriculum war zusätzlich ein Austausch über die Erlebnisse
während der Kohlenhydrat-Reduktion enthalten, sowie die Vermittlung von Wissen
über die Pathomechanismen der Gewichtsentwicklung. Weitere Anforderungen an die
Teilnehmer wurden nicht gestellt. Am Ende des einjährigen Kurses reduzierten 18
Teilnehmer aus mehreren Gruppen ihr Gewicht im Mittel um 8,6% vom
Ausgangsgewicht. Parameter des Glukosestoffwechsels besserten sich ebenso wie
psychologische Indikatoren für Essimpulse. Wir nehmen an, dass ein solcher Kurs
in Gruppen, der sich auf die psychologischen Gefahren konzentriert, die mit
einem Vermeiden von Kohlenhydraten in der Nahrung verbunden sind, ein einfach
anwendbarer Weg gegen das Problem des Übergewichtes in jeder spezialisierten
Einrichtung ist.
Update of the competence-based catalog of learning objectives in nuclear medicine for the study of human medicine in Germany
Authors: Heidemanns Stefanie , Trautmann Stephanie , Weidt Daniela , Hellwig Dirk 
Published: May 2024

Abstract
Aim To update the subject-specific, competence-based catalog of learning objectives for medical studies in Germany published by the German Society of Nuclear Medicine (DGN) in 2018, prioritizing relevant learning objectives.
Methods Based on the previous catalog, the writing group compiled nuclear medicine topics and formulated competence-based learning objectives, including medical developments, device innovations and new radiopharmaceutical approvals. These were presented for prioritization to the 180 habilitated DGN members as an expert group in a Delphi process. The first round of voting assessed firstly the topics in terms of necessity or dispensability, and secondly the detailed learning objectives of the topics were assessed for their relevance to academic teaching in nuclear medicine. The results of the first survey were used to draft a catalog of learning objectives with final approval by the expert group in a second survey. The time available for teaching nuclear medicine was also recorded.
Results The writing group developed 240 competence-based learning objectives from 41 topics. After a first Delphi round, 73 detailed competence-based learning objectives from 15 topics were compiled. The mean teaching time was 8.4 h for lectures, 3.7 h for seminars and 3.6 h for practical courses. In a second Delphi round, the agreement of the expert group was at least 95% for the selected topics and at least 90% for the detailed learning objectives.
Summary The catalog of subject-specific learning objectives, updated by expert consensus, provides basic knowledge, skills and competences related to the most relevant diagnostic and therapeutic procedures in nuclear medicine, taking into account both long-established topics and recently introduced innovations.
Patient Demographic Factors Impact KOOS JR Response Rates for Total Knee Arthroplasty Patients
Authors: Tong Yixuan , Rajahraman Vinaya , Gupta Rajan , Schwarzkopf Ran , Rozell Joshua C. 
Published: May 2024

AbstractThe Knee injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR) is a validated patient-reported measure for assessing pain and function following total knee arthroplasty (TKA). This study investigates how patient demographic factors (i.e., age, sex, and race) correlate with KOOS JR response rates. This was a retrospective cohort study of adult, English-speaking patients who underwent primary TKA between 2017 and 2023 at an academic institution. KOOS JR completion status—complete or incomplete—was recorded within 90 days postoperatively. Standard statistical analyses were performed to assess KOOS JR completion against demographic factors. Among 2,883 total patients, 70.2% had complete and 29.8% had incomplete KOOS JR questionnaires. Complete status (all p < 0.01) was associated with patients aged 60 to 79 (71.8%), white race (77.6%), Medicare (81.7%), marriage (76.8%), and the highest income quartile (75.7%). Incomplete status (all p < 0.001) was associated with patients aged 18 to 59 (64.4%), Medicaid (82.4%), and lower income quartiles (41.6% first quartile, 36.8% third quartile). Multiple patient demographic factors may affect KOOS JR completion rates; patients who are older, white, and of higher socioeconomic status are more likely to participate. Addressing underrepresented groups is important to improve the utility and generalizability of the KOOS JR.