bluuebunny/crossref_metadata_2025_split huggingface dataset:
A feasibility study using sodium alginate injection for penetrating abdominal trauma in a swine model
Authors: Barsky Daniel , Ben Ya’acov Ami , Avraham Linn Wagnert , Nachman Dean , Eisenkraft Arik , Mintz Yoav , Shteyer Eyal 
Published: October 2022

AbstractPenetrating abdominal injury is a major cause of death in trauma. Sodium alginate hydrogel, a hemostatic agent, offers a platform for targeting both mechanical and biological injuries. The current study assessed the effect of Very Low Viscosity (high) G (VLVG) alginate following abdominal trauma in a swine model of penetrating abdominal injury. Seven anesthetized pigs were instrumented with invasive monitoring catheters and abdominal trauma was introduced by laparoscopic hepatectomy. Ten minutes after the induction of hypovolemic shock, three animals were intra-abdominally administered with VLVG alginate (study group) and four animals with saline (control group). During 8 h of continuous monitoring, various hemodynamic and biochemical variables were measured and liver biopsies for histological evaluation were taken. Hemodynamically, VLVG alginate-treated animals were more stable than controls, as reflected by their lower heart rate and higher blood pressure (p < 0.05 for both). They also had lower levels of liver enzymes and lactate, and less histopathological damage. We show that VLVG alginate might be a promising new agent for reducing penetrating intra-abdominal injury, with hemostatic and biocompatibility efficiency, and tissue preserving properties. Future effort of integrating it with a dispersal device may turn it into a valuable pre-hospital emergency tool to improve survival of trauma casualties.
Modeling fine-grained spatio-temporal pollution maps with low-cost sensors
Authors: Iyer Shiva R. , Balashankar Ananth , Aeberhard William H. , Bhattacharyya Sujoy , Rusconi Giuditta , Jose Lejo , Soans Nita , Sudarshan Anant , Pande Rohini , Subramanian Lakshminarayanan 
Published: October 2022

AbstractThe use of air quality monitoring networks to inform urban policies is critical especially where urban populations are exposed to unprecedented levels of air pollution. High costs, however, limit city governments’ ability to deploy reference grade air quality monitors at scale; for instance, only 33 reference grade monitors are available for the entire territory of Delhi, India, spanning 1500 sq km with 15 million residents. In this paper, we describe a high-precision spatio-temporal prediction model that can be used to derive fine-grained pollution maps. We utilize two years of data from a low-cost monitoring network of 28 custom-designed low-cost portable air quality sensors covering a dense region of Delhi. The model uses a combination of message-passing recurrent neural networks combined with conventional spatio-temporal geostatistics models to achieve high predictive accuracy in the face of high data variability and intermittent data availability from low-cost sensors (due to sensor faults, network, and power issues). Using data from reference grade monitors for validation, our spatio-temporal pollution model can make predictions within 1-hour time-windows at 9.4, 10.5, and 9.6% Mean Absolute Percentage Error (MAPE) over our low-cost monitors, reference grade monitors, and the combined monitoring network respectively. These accurate fine-grained pollution sensing maps provide a way forward to build citizen-driven low-cost monitoring systems that detect hazardous urban air quality at fine-grained granularities.
Strong modulation of carrier effective mass in WTe2 via coherent lattice manipulation
Authors: Soranzio Davide , Savoini Matteo , Beaud Paul , Cilento Federico , Boie Larissa , Dössegger Janine , Ovuka Vladimir , Houver Sarah , Sander Mathias , Zerdane Serhane , Abreu Elsa , Deng Yunpei , Mankowsky Roman , Lemke Henrik T. , Parmigiani Fulvio , Peressi Maria , Johnson Steven L. 
Published: October 2022

AbstractThe layered transition-metal dichalcogenide WTe2 is characterized by distinctive transport and topological properties. These properties are largely determined by electronic states close to the Fermi level, specifically to electron and hole pockets in the Fermi sea. In principle, these states can be manipulated by changes to the crystal structure. The precise impact of particular structural changes on the electronic properties is a strong function of the specific nature of the atomic displacements. Here, we report on time-resolved X-ray diffraction and infrared reflectivity measurements of the coherent structural dynamics in WTe2 induced by femtosecond laser pulses excitation (central wavelength 800 nm), with emphasis on a quantitative description of both in-plane and out-of-plane vibrational modes. We estimate the magnitude of these motions, and calculate via density functional theory their effect on the electronic structure. Based on these results, we predict that phonons periodically modulate the effective mass of carriers in the electron and hole pockets up to 20%. This work opens up new opportunities for modulating the peculiar transport properties of WTe2 on short time scales.
Older Barbary macaques show limited capacity for self-regulation to avoid hazardous social interactions
Authors: Rathke Eva-Maria , Mundry Roger , Fischer Julia 
Published: October 2022

AbstractAccording to the Strength-and-Vulnerability-Integration (SAVI) model, older people are more motivated to avoid negative affect and high arousal than younger people. To explore the biological roots of this effect, we investigate communicative interactions and social information processing in Barbary macaques (Macaca sylvanus) living at ‘La Forêt des Singes’ in Rocamadour, France. The study combines an analysis of the production of (N = 8185 signals, 84 signallers) and responses to communicative signals(N = 3672 events, 84 receivers) with a field experiment (N = 166 trials, 45 subjects). Here we show that older monkeys are not more likely to specifically ignore negative social information or to employ avoidance strategies in stressful situations, although they are overall less sociable. We suggest that the monkeys have only a limited capacity for self-regulation within social interactions and rather rely on general avoidance strategies to decrease the risk of potentially hazardous social interactions.
A ventral stream-prefrontal cortex processing cascade enables working memory gating dynamics
Authors: Yu Shijing , Rempel Sarah , Gholamipourbarogh Negin , Beste Christian 
Published: October 2022

AbstractThe representation of incoming information, goals and the flexible processing of these are required for cognitive control. Efficient mechanisms are needed to decide when it is important that novel information enters working memory (WM) and when these WM ‘gates’ have to be closed. Compared to neural foundations of maintaining information in WM, considerably less is known about what neural mechanisms underlie the representational dynamics during WM gating. Using different EEG analysis methods, we trace the path of mental representations along the human cortex during WM gate opening and closing. We show temporally nested representational dynamics during WM gate opening and closing depending on multiple independent neural activity profiles. These activity profiles are attributable to a ventral stream-prefrontal cortex processing cascade. The representational dynamics start in the ventral stream during WM gate opening and WM gate closing before prefrontal cortical regions are modulated. A regional specific activity profile is shown within the prefrontal cortex depending on whether WM gates are opened or closed, matching overarching concepts of prefrontal cortex functions. The study closes an essential conceptual gap detailing the neural dynamics underlying how mental representations drive the WM gate to open or close to enable WM functions such as updating and maintenance.
Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution
Authors: Alsaigh Tom , Evans Doug , Frankel David , Torkamani Ali 
Published: October 2022

AbstractAtherogenesis involves an interplay of inflammation, tissue remodeling and cellular transdifferentiation (CTD), making it especially difficult to precisely delineate its pathophysiology. Here we use single-cell RNA sequencing and systems-biology approaches to analyze the transcriptional profiles of vascular smooth muscle cells (VSMCs) and endothelial cells (ECs) in calcified atherosclerotic core (AC) plaques and patient-matched proximal adjacent (PA) portions of carotid artery tissue from patients undergoing carotid endarterectomy. Our results reveal an anatomic distinction whereby PA cells express inflammatory mediators, while cells expressing matrix-secreting genes occupy a majority of the AC region. Systems biology analysis indicates that inflammation in PA ECs and VSMCs may be driven by TNFa signaling. Furthermore, we identify POSTN, SPP1 and IBSP in AC VSMCs, and ITLN1, SCX and S100A4 in AC ECs as possible candidate drivers of CTD in the atherosclerotic core. These results establish an anatomic framework for atherogenesis which forms the basis for exploration of a site-specific strategy for disruption of disease progression.
Machine learned synthesizability predictions aided by density functional theory
Authors: Lee Andrew , Sarker Suchismita , Saal James E. , Ward Logan , Borg Christopher , Mehta Apurva , Wolverton Christopher 
Published: October 2022

AbstractA grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore phase stability information. Here, we combine thermodynamic stability calculated using density functional theory with composition-based features to train a machine learning model that predicts a material’s synthesizability. Our model predicts the synthesizability of ternary 1:1:1 compositions in the half-Heusler structure, achieving a cross-validated precision of 0.82 and recall of 0.82. Our model shows improvement in predicting non-half-Heuslers compared to a previous study’s model, and identifies 121 synthesizable candidates out of 4141 unreported ternary compositions. More notably, 39 stable compositions are predicted unsynthesizable while 62 unstable compositions are predicted synthesizable; these findings otherwise cannot be made using density functional theory stability alone. This study presents a new approach for accurately predicting synthesizability, and identifies new half-Heuslers for experimental synthesis.
Identification of potential M2 macrophage-associated diagnostic biomarkers in coronary artery disease
Authors: Li Kunlin , Kong Ruize , Ma Lijing , Cao Yu , Li Wei , Chen Rui , Gong Kunmei , Jiang Lihong 
Published: October 2022

Abstract
Background: M2 macrophages have been reported to be important in the progression of coronary artery disease (CAD). Thus, the present study aims at exploring the diagnostic value of M2 macrophage-associated genes in CAD.
Methods: Transcriptome profile of CAD and control samples were downloaded from Gene Expression Omnibus database. The proportion of immune cells was analyzed using cell type identification by estimating relative subsets of RNA transcripts. Weighted Gene Co-expression Network Analysis (WGCNA) was carried out to screen the relevant module associated with M2 macrophages. Differential CAD and control samples of expressed genes (DEGs) were identified by the limma R package. Functional enrichment analysis by means of the clusterProfiler R package. Least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms were carried out to select signature genes. Receiver operating curves (ROC) were plotted to evaluate the diagnostic value of selected signature genes. The expressions of potential diagnostic markers were validated by RT-qPCR. The ceRNA network of diagnostic biomarkers was constructed via miRwalk and Starbase database. CMap database was used to screen candidate drugs in the treatment of CAD by targeting diagnostic biomarkers.
Results: A total of 166 M2 macrophage-associated genes were identified by WGCNA. By intersecting those genes with 879 DEGs, 53 M2 macrophage-associated DEGs were obtained in the present study. By LASSO, RF, and ROC analyses, C1orf105, CCL22, CRYGB, FRK, GAP43, REG1P, CALB1, and PTPN21 were identified as potential diagnostic biomarkers. RT-qPCR showed the consistent expression patterns of diagnostic biomarkers between GEO dataset and clinical samples. Perhexiline, alimemazine and mecamylamine were found to be potential drugs in the treatment of CAD.
Conclusion: We identified eight M2 macrophage-associated diagnostic biomarkers and candidate drugs for the CAD treatment.
Stable routing protocol for unmanned aerial vehicle ad‐hoc networks based on DQN‐OLSR
Authors: Zeng Youjun , Zhou Jie , Liu Youjiang , Cao Tao , Yang Dalong , Liu Yu , Shi Xianhua 
Published: October 2022

AbstractIn unmanned aerial vehicle ad‐hoc network (UANET), the network topology changes with time due to the movement of the unmanned aerial vehicles (UAVs), which brings great challenges to the design of the routing protocol. In traditional routing protocols, when UANET topology changes, nodes cannot dynamically update neighbour nodes and topology information, and routing table calculation cannot accurately reflect the actual transmission path. As a result, network cannot meet the quality of service (QoS) requirements such as low end‐to‐end delay, high throughput and low packet loss rate. This paper proposes a dynamically optimized link state routing (OLSR) protocol based on Deep Q‐Network algorithm (DQN‐OLSR). In this protocol, each node first adjusts the sending interval of Hello messages adaptively in real time, according to the position and speed information of its neighbour nodes. Then the protocol uses the DQN algorithm to dynamically adjust the flooding interval of topology control (TC) messages to improve the routing update capability of nodes. The simulation verifies that the UANETs under this protocol have higher throughput and less packet loss rate than ad‐hoc on‐demand distance vector (AODV), grid routing protocol (GRP) and OLSR protocols, at different movement speeds in random waypoint (RWP) and random walk mobile models. Under nomadic as well as pursue mobile models, DQN‐OLSR performs consistently with OLSR QoS performance, with the best performance among all four protocols. By further adding positioning errors to the nodes, it shows that the proposed protocol has good robustness, and the QoS performance degradation keeps within a low level.
The Synthesis of Novel P,N-Ferrocenylpyrrolidine-Containing Ligands and Their Application in Pd-Catalyzed Allylic Alkylation – A Synthetic and Mechanistic Investigation
Authors: Guiry Patrick J. , Brennan Therese B. , Müller-Bunz Helge 
Published: October 2022

AbstractThe synthesis of a series of planar chiral P,N-ferrocenylpyrrolidine-containing ligands, with varying substituents at the phosphorus donor atom, is described. The phosphorus donor atom was introduced via a diastereoselective ortho-directed metalation of N-methylpyrrolidinyl ferrocene followed by a quench with various chlorophosphines. These P,N systems are very active in Pd-catalyzed allylic alkylation of 1,3-diphenylpropenyl acetate with dimethylmalonate (conversions of up to 100%) and demonstrated good levels of enantioselectivity (up to 85% ees). Good selectivity for the (R)-enantiomer was observed and mechanistic studies, involving X-ray crystallography and NMR spectroscopic experiments, were employed to help rationalize the observed stereochemical outcome of the reaction.
Factors Associated with Early Career Research Productivity after Ophthalmology Residency
Authors: Wieder Matthew S. , He Catherine H. , Pahl Daniel A. , Parsikia Afshin , Mbekeani Joyce N. 
Published: October 2022

Abstract
Background Few studies have evaluated associations between ophthalmology trainee characteristics and performance with postgraduate research productivity.
Purpose This article evaluates factors associated with post-residency research productivity among U.S. ophthalmology graduates.
Methods Publicly available information of residents graduating between 2009 and 2014 from 30 randomly selected U.S. ophthalmology programs was collected from June to September 2020. Differences in publications between the 5 years post-residency and pre-residency/residency period were used as metrics of productivity. Residents with incomplete records were excluded.
Results A total of 758 of 768 residents, 306 females (40.4%) and 452 males (59.6%), met inclusion criteria. The mean (standard deviation [SD]) number of pre-residency publications was 1.7 (4.0), residency was 1.3 (2.2), and post-residency was 4.0 (7.3). Mean (SD) H-index was 4.2 (4.9). Top-ranked residency (p = 0.001), Alpha Omega Alpha (AOA) medical honor status (p = 0.002), U.S. medical school graduates (p < 0.001), and academic career (p < 0.001) were all associated with higher pre-/post-residency mean publication difference. Pursuing fellowship training also was associated with higher total publications (p < 0.001). Of all pre-residency degrees, PhD had the greatest odds of high postgraduate publications (defined as > 4). There was a positive correlation between both pre-residency/residency and post-residency publications (rho = 0.441; p < 0.001) and between mean difference of pre-residency/post-residency publications for residents at a program and that program's Doximity rank (rho = 0.497; p < 0.001). Multivariate logistic regression revealed, academic career choice (odds ratio [OR] = 3.38; p < 0.001), Heed fellowship (OR = 3.12; p = 0.031), > 2 residency publications (OR = 2.89; p < 0.001), AOA status (OR = 2.0; p = 0.004), and top-ranked residency programs (OR = 1.89; p = 0.007), had greatest odds of > 4 postgraduation publications.
Conclusion Higher post-residency productivity was associated with multiple factors, with choice of an academic career, Heed fellowship, and residency productivity playing key roles.
Chordoma of the Clivus with Metastasis to Femur
Authors: Matmusaev Maruf , Nagatani Tetsuya , Kishida Yugo , Ansari Ahmed 
Published: October 2022

AbstractChordomas are aggressive and invasive tumors that are notoriously famous for their recurrence and metastasis. They present with diverse manifestations, usually with lower cranial nerve involvement. Here, we present the first reported case of chondroid chordoma with femur metastasis. A 71-year-old lady presented to us with a headache and diplopia. MRI of the brain revealed an enhanced broad and destructive mass in the infrasellar region with complete destruction of the clivus, right cavernous sinus. She underwent multiple surgeries along with gamma knife and proton therapy. The patient later presented with a trochanteric fracture and needed a hip replacement. Biopsy curettage of the femur lesion revealed a chondroid chordoma of the femur. The patient died later of a chest infection. Multimodality treatment is required in chordoma management, including surgery, gamma knife, and proton therapy. A firm discerning eye is required in the elderly toward metastatic spread to the femur in cases presenting with fractures of long bones.
Developing the VA Geriatric Scholars Programs' Clinical Dashboards Using the PDSA Framework for Quality Improvement
Authors: Burningham Zachary , Lagha Regina Richter , Duford-Hutchinson Brittany , Callaway-Lane Carol , Sauer Brian C. , Halwani Ahmad S. , Bell Jamie , Huynh Tina , Douglas Joseph R. , Kramer B. Josea 
Published: October 2022

AbstractBackground Involving clinician end users in the development process of clinical dashboards is important to ensure that user needs are adequately met prior to releasing the dashboard for use. The challenge with following this approach is that clinician end users can undergo periodic turnover, meaning, the clinicians that played a role in the initial development process may not be the same individuals that use the dashboard in future.Objectives Here, we summarize our Plan, Do, Study, Act (PDSA)-guided clinical dashboard development process for the VA Geriatric Scholars Program (GSP) and the value of continuous, iterative development. We summarize dashboard adaptations that resulted from two PDSA cycles of improvement for the potentially inappropriate medication dashboard (PIMD), one of many Geriatric Scholars clinical dashboards. We also present the evaluative performance of the PIMD.Methods Evaluation of the PIMD was performed using the system usability scale (SUS) and through review of user interaction logs. Routine end users that were Geriatric Scholars and had evidence of 5 or more dashboard views were invited to complete an electronic form that contained the 10-item SUS.Results The proportion of Geriatric Scholars that utilized the PIMD increased for each iterative dashboard version that was produced as a byproduct from feedback (31.0% in 2017 to 60.2% in 2019). The overall usability of the PIMD among routine users was found to be above average (SUS score: 75.2 [95% CI 70.5–79.8]) in comparison to the recommended standard of acceptability (SUS score: 68)Conclusion The solicitation of feedback during dashboard orientations led to iterative adaptations of the PIMD that broadened its intended use. The presented PDSA-guided process to clinical dashboard development for the VA GSP can serve as a valuable framework for development teams seeking to produce well-adopted and usable health information technology (IT) innovations.
Attention and counter-framing in the Black Lives Matter movement on Twitter
Authors: Klein Colin , Reimann Ritsaart , Quintana Ignacio Ojea , Cheong Marc , Ferreira Marinus , Alfano Mark 
Published: October 2022

AbstractThe social media platform Twitter platform has played a crucial role in the Black Lives Matter (BLM) movement. The immediate, flexible nature of tweets plays a crucial role both in spreading information about the movement’s aims and in organizing individual protests. Twitter has also played an important role in the right-wing reaction to BLM, providing a means to reframe and recontextualize activists’ claims in a more sinister light. The ability to bring about social change depends on the balance of these two forces, and in particular which side can capture and maintain sustained attention. The present study examines 2 years worth of tweets about BLM (about 118 million in total). Timeseries analysis reveals that activists are better at mobilizing rapid attention, whereas right-wing accounts show a pattern of moderate but more sustained activity driven by reaction to political opponents. Topic modeling reveals differences in how different political groups talk about BLM. Most notably, the murder of George Floyd appears to have solidified a right-wing counter-framing of protests as arising from dangerous “terrorist” actors. The study thus sheds light on the complex network and rhetorical effects that drive the struggle for online attention to the BLM movement.