bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transient and general synthesis of high-density and ultrasmall nanoparticles on two-dimensional porous carbon via coordinated carbothermal shock
Authors: Shi Wenhui , Li Zezhou , Gong Zhihao , Liang Zihui , Liu Hanwen , Han Ye-Chuang , Niu Huiting , Song Bo , Chi Xiaodong , Zhou Jihan , Wang Hua , Xia Bao Yu , Yao Yonggang , Tian Zhong-Qun 
Published: April 2023

AbstractCarbon-supported nanoparticles are indispensable to enabling new energy technologies such as metal-air batteries and catalytic water splitting. However, achieving ultrasmall and high-density nanoparticles (optimal catalysts) faces fundamental challenges of their strong tendency toward coarsening and agglomeration. Herein, we report a general and efficient synthesis of high-density and ultrasmall nanoparticles uniformly dispersed on two-dimensional porous carbon. This is achieved through direct carbothermal shock pyrolysis of metal-ligand precursors in just ~100 ms, the fastest among reported syntheses. Our results show that the in situ metal-ligand coordination (e.g., N → Co2+) and local ordering during millisecond-scale pyrolysis play a crucial role in kinetically dominated fabrication and stabilization of high-density nanoparticles on two-dimensional porous carbon films. The as-obtained samples exhibit excellent activity and stability as bifunctional catalysts in oxygen redox reactions. Considering the huge flexibility in coordinated precursors design, diversified single and multielement nanoparticles (M = Fe, Co, Ni, Cu, Cr, Mn, Ag, etc) were generally fabricated, even in systems well beyond traditional crystalline coordination chemistry. Our method allows for the transient and general synthesis of well-dispersed nanoparticles with great simplicity and versatility for various application schemes.
A Large-scale Synthetic Pathological Dataset for Deep Learning-enabled Segmentation of Breast Cancer
Authors: Ding Kexin , Zhou Mu , Wang He , Gevaert Olivier , Metaxas Dimitris , Zhang Shaoting 
Published: April 2023

AbstractThe success of training computer-vision models heavily relies on the support of large-scale, real-world images with annotations. Yet such an annotation-ready dataset is difficult to curate in pathology due to the privacy protection and excessive annotation burden. To aid in computational pathology, synthetic data generation, curation, and annotation present a cost-effective means to quickly enable data diversity that is required to boost model performance at different stages. In this study, we introduce a large-scale synthetic pathological image dataset paired with the annotation for nuclei semantic segmentation, termed as Synthetic Nuclei and annOtation Wizard (SNOW). The proposed SNOW is developed via a standardized workflow by applying the off-the-shelf image generator and nuclei annotator. The dataset contains overall 20k image tiles and 1,448,522 annotated nuclei with the CC-BY license. We show that SNOW can be used in both supervised and semi-supervised training scenarios. Extensive results suggest that synthetic-data-trained models are competitive under a variety of model training settings, expanding the scope of better using synthetic images for enhancing downstream data-driven clinical tasks.
Estimating social bias in data sharing behaviours: an open science experiment
Authors: Acciai Claudia , Schneider Jesper W. , Nielsen Mathias W. 
Published: April 2023

AbstractOpen data sharing is critical for scientific progress. Yet, many authors refrain from sharing scientific data, even when they have promised to do so. Through a preregistered, randomized audit experiment (N = 1,634), we tested possible ethnic, gender and status-related bias in scientists’ data-sharing willingness. 814 (54%) authors of papers where data were indicated to be ‘available upon request’ responded to our data requests, and 226 (14%) either shared or indicated willingness to share all or some data. While our preregistered hypotheses regarding bias in data-sharing willingness were not confirmed, we observed systematically lower response rates for data requests made by putatively Chinese treatments compared to putatively Anglo-Saxon treatments. Further analysis indicated a theoretically plausible heterogeneity in the causal effect of ethnicity on data-sharing. In interaction analyses, we found indications of lower responsiveness and data-sharing willingness towards male but not female data requestors with Chinese names. These disparities, which likely arise from stereotypic beliefs about male Chinese requestors’ trustworthiness and deservingness, impede scientific progress by preventing the free circulation of knowledge.
Clinical courses of 24,563 hospitalized COVID-19 patients during the first 12 months of the pandemic in the Central City of Iran
Authors: Namayandeh Seyedeh Mahideh , Dehghan HamidReza , Lotfi Mohammad Hassan , Khajehaminian Mohammad Reza , Hosseini Saeed , Bahrevar Vali , Jarrahi AliAkbar , Majidpour Fatemeh 
Published: April 2023

AbstractThis study was designed and implemented to analyze and establish documents related to the above cases in the first to third COVID-19 epidemic waves for the use of researchers and doctors during and after the epidemic. The current case series study was conducted on 24,563 thousand hospitalized COVID-19 patients by examining their clinical characteristics within a one-year period from the beginning of the pandemic on 02.22.2020 to 02.14.2021, which included the first to the third waves, based on gender and severity of COVID-19. The mean age of the participants was 56 ± 20.71, and 51.8% were male. Out of a total of 24,563 thousand hospitalized COVID-19 patients until February 2021, there were 2185 mortalities (9.8%) and 2559 cases of severe COVID-19 (13.1%). The median length of hospitalization from the time of admission to discharge or death in the hospital (IQR: 13–41) was estimated to be 21 days. The rate of hospital mortality was higher in severe (37.8%) than in non-severe (4.8%) cases of COVID-19, While the risk of severe cases increased significantly in the third (HR = 1.65, 95% CI: 1.46–1.87, P < 0.001) and early fourth waves (HR = 2.145, 95% CI: 1.7–2.71, P < 0.001). Also, the risk of contracting severe COVID-19 increased significantly in patients aged ≥ 65 years old (HR = 2.1, 95% CI 1.1.93–2.72, P < 0.001). As shown by the results, the rates of hospital mortality (9.3% vs. 8.5%) and severe cases of COVID-19 (13.6% vs. 12.5%) were higher among men than women (P < 0.01). In our study, the mortality rate and severity of COVID-19 were within the scope of global studies. Men experienced higher severity and mortality than women. The was a significantly higher prevalence of old age and underlying diseases in individuals with severe COVID-19. Our data also showed that patients with a previous history of COVID-19 had a more severe experience of COVID-19, while most of these patients were also significantly older and had an underlying disease.
Post-intensive care syndrome and pulmonary fibrosis in patients surviving ARDS-pneumonia of COVID-19 and non-COVID-19 etiologies
Authors: Sturgill Jamie L. , Mayer Kirby P. , Kalema Anna G. , Dave Kinjal , Mora Stephanie , Kalantar Alborz , Carter David J. , Montgomery-Yates Ashley A. , Morris Peter E. 
Published: April 2023

AbstractThe purpose was to examine patient-centered outcomes and the occurrence of lung fibrotic changes on Chest computed tomography (CT) imaging following pneumonia-related acute respiratory distress syndrome (ARDS). We sought to investigate outpatient clinic chest CT imaging in survivors of COVID19-related ARDS and non-COVID-related ARDS, to determine group differences and explore relationships between lung fibrotic changes and functional outcomes. A retrospective practice analysis of electronic health records at an ICU Recovery Clinic in a tertiary academic medical center was performed in adult patients surviving ARDS due to COVID-19 and non-COVID etiologies. Ninety-four patients with mean age 53 ± 13 and 51% male were included (n = 64 COVID-19 and n = 30 non-COVID groups). There were no differences for age, sex, hospital length of stay, ICU length of stay, mechanical ventilation duration, or sequential organ failure assessment (SOFA) scores between the two groups. Fibrotic changes visualized on CT imaging occurred in a higher proportion of COVID-19 survivors (70%) compared to the non-COVID group (43%, p < 0.001). Across both groups, patients with fibrotic changes (n = 58) were older, had a lower BMI, longer hospital and ICU LOS, lower mean RASS scores, longer total duration of supplemental oxygen. While not statistically different, patients with fibrotic changes did have reduced respiratory function, worse performance on the six-minute walk test, and had high occurrences of anxiety, depression, emotional distress, and mild cognitive impairment regardless of initial presenting diagnosis. Patients surviving pneumonia-ARDS are at high risk of impairments in physical, emotional, and cognitive health related to Post-Intensive Care Syndrome. Of clinical importance, pulmonary fibrotic changes on chest CT occurred in a higher proportion in COVID-ARDS group; however, no functional differences were measured in spirometry or physical assessments at ICU follow-up. Whether COVID infection imparts a unique recovery is not evident from these data but suggest that long-term follow up is necessary for all survivors of ARDS.
Towards reducing chemical usage for weed control in agriculture using UAS imagery analysis and computer vision techniques
Authors: Sapkota Ranjan , Stenger John , Ostlie Michael , Flores Paulo 
Published: April 2023

AbstractCurrently, applying uniform distribution of chemical herbicide through a sprayer without considering the spatial distribution information of crops and weeds is the most common method of controlling weeds in commercial agricultural production system. This kind of weed management practice lead to excessive amounts of chemical herbicides being applied in a given field. The objective of this study was to perform site-specific weed control (SSWC) in a corn field by: (1) using a unmanned aerial system (UAS) to map the spatial distribution information of weeds in the field; (2) creating a prescription map based on the weed distribution map, and (3) spraying the field using the prescription map and a commercial size sprayer. In this study, we assumed that plants growing outside the corn rows are weeds and they need to be controlled. The first step in implementing such an approach is identifying the corn rows. For that, we are proposing a Crop Row Identification algorithm, a computer vision algorithm that identifies corn rows on UAS imagery. After being identified, the corn rows were then removed from the imagery and remaining vegetation fraction was classified as weeds. Based on that information, a grid-based weed prescription map was created and the weed control application was implemented through a commercial-size sprayer. The decision of spraying herbicides on a particular grid was based on the presence of weeds in that grid cell. All the grids that contained at least one weed were sprayed, while the grids free of weeds were not. Using our SSWC approach, we were able to save 26.2% of the acreage from being sprayed with herbicide compared to the current method. This study presents a full workflow from UAS image collection to field weed control implementation using a commercial size sprayer, and it shows that some level of savings can potentially be obtained even in a situation with high weed infestation, which might provide an opportunity to reduce chemical usage in corn production systems.
Discovery of novel CSF biomarkers to predict progression in dementia using machine learning
Authors: Gogishvili Dea , Vromen Eleonora M. , Koppes-den Hertog Sascha , Lemstra Afina W. , Pijnenburg Yolande A. L. , Visser Pieter Jelle , Tijms Betty M. , Del Campo Marta , Abeln Sanne , Teunissen Charlotte E. , Vermunt Lisa 
Published: April 2023

AbstractProviding an accurate prognosis for individual dementia patients remains a challenge since they greatly differ in rates of cognitive decline. In this study, we used machine learning techniques with the aim to identify cerebrospinal fluid (CSF) biomarkers that predict the rate of cognitive decline within dementia patients. First, longitudinal mini-mental state examination scores (MMSE) of 210 dementia patients were used to create fast and slow progression groups. Second, we trained random forest classifiers on CSF proteomic profiles and obtained a well-performing prediction model for the progression group (ROC–AUC = 0.82). As a third step, Shapley values and Gini feature importance measures were used to interpret the model performance and identify top biomarker candidates for predicting the rate of cognitive decline. Finally, we explored the potential for each of the 20 top candidates in internal sensitivity analyses. TNFRSF4 and TGF $$\upbeta $$
β
-1 emerged as the top markers, being lower in fast-progressing patients compared to slow-progressing patients. Proteins of which a low concentration was associated with fast progression were enriched for cell signalling and immune response pathways. None of our top markers stood out as strong individual predictors of subsequent cognitive decline. This could be explained by small effect sizes per protein and biological heterogeneity among dementia patients. Taken together, this study presents a novel progression biomarker identification framework and protein leads for personalised prediction of cognitive decline in dementia.
Optimization of production system of shale oil development in Ordos basin, China
Authors: Wan Xiaolong , Ma Shuwei , Fan Jianming , Zhang Yuanli , Zhang Chao 
Published: April 2023

AbstractIn this paper, production system (PS) of shale oil is optimized according to production data and indoor experiments, including core and fluid tests. Results showed that: ① Pressure drop rate at wellhead is a reasonable reference for the determination of post-fracture shut-in duration (PFSID). When pressure at a wellhead of horizontal well is relatively stable and the pressure drop less than 0.1 MPa per day for three consecutive days, PFSID ends; ② Flowback intensity of fracturing fluid affects the effectiveness of proppant underground, thus flowback intensity can be determined by the critical flow rate and safety factor of each proppant; ③ Flowback intensity should be varied during different development stages, which could be divided into four according to production gas and oil ratio(GOR) of a shale oil horizontal well: low, medium–high, high and high-low production GOR. During the stage of low production GOR, ratio of flow pressure and saturation pressure should be maintained greater than 1.0, and the initial daily liquid productivity for a hundred-meter oil-bearing lateral length in a horizontal well is 2.4 ~ 2.9 m3/d; and during the medium–high production GOR, high production GOR and high-low production GOR stages, the responding initial daily liquid productivity should be maintained between 0.8 ~ 1.0 or less than 0.8 respectively.
Causal Bayesian machine learning to assess treatment effect heterogeneity by dexamethasone dose for patients with COVID-19 and severe hypoxemia
Authors: Blette Bryan S. , Granholm Anders , Li Fan , Shankar-Hari Manu , Lange Theis , Munch Marie Warrer , Møller Morten Hylander , Perner Anders , Harhay Michael O. 
Published: April 2023

AbstractThe currently recommended dose of dexamethasone for patients with severe or critical COVID-19 is 6 mg per day (mg/d) regardless of patient features and variation. However, patients with severe or critical COVID-19 are heterogenous in many ways (e.g., age, weight, comorbidities, disease severity, and immune features). Thus, it is conceivable that a standardized dosing protocol may not be optimal. We assessed treatment effect heterogeneity in the COVID STEROID 2 trial, which compared 6 mg/d to 12 mg/d, using a causal inference framework with Bayesian Additive Regression Trees, a flexible modeling method that detects interactive effects and nonlinear relationships among multiple patient characteristics simultaneously. We found that 12 mg/d of dexamethasone, relative to 6 mg/d, was probably associated with better long-term outcomes (days alive without life support and mortality after 90 days) among the entire trial population (i.e., no signals of harm), and probably more beneficial among those without diabetes mellitus, that were older, were not using IL-6 inhibitors at baseline, weighed less, or had higher level respiratory support at baseline. This adds more evidence supporting the use of 12 mg/d in practice for most patients not receiving other immunosuppressants and that additional study of dosing could potentially optimize clinical outcomes.
The sex impact on the technological and chemical characteristics of meat derived from the Polish native chicken breed
Authors: Kasperek Kornel , Drabik Kamil , Sofińska-Chmiel Weronika , Karwowska Małgorzata , Zięba Grzegorz , Batkowska Justyna 
Published: April 2023

AbstractThe aim of the study was to evaluate the birds’ sex as well as the caponisation influence on the technological traits of obtained meat, fatty acids profile as well as main chemical compounds distribution. In this study, 40 hens, roosters and green-legged partridge capons each were used (4 replications each). At 24 weeks of age, 2 birds from each replication subgroup were selected and slaughtered. During dissection analysis, pectoral and femoral muscles were sampled. Acidity, colour, tenderness, water holding capacity, drip and cooking loss were determined in the obtained material. The fatty acid profile of the meat was also determined, as well as the distribution of components in the pressed meat samples using FTIR spectroscopy. Statistically significant differences in the colour lightness index (L*) of the breast muscles were recorded, with cockerel meat being the darkest and capon meat the lightest. The greatest natural water loss was recorded in the hens' pectoral muscle; cooking loss was also the greatest in these samples. Roosters showed significantly the lowest content of monounsaturated fatty acids, at the same time the highest proportion of the n3 fatty acids group was found in capons. Irrespective of muscle, meat from roosters showed the highest susceptibility to oxidation (PI index). The variation in the chemical composition of the meat was confirmed by FTIR mapping.
The effect of acute exercise on circulating immune cells in newly diagnosed breast cancer patients
Authors: Koivula Tiia , Lempiäinen Salla , Rinne Petteri , Rannikko Jenna H. , Hollmén Maija , Sundberg Carl Johan , Rundqvist Helene , Minn Heikki , Heinonen Ilkka 
Published: April 2023

AbstractThe role of exercise in cancer prevention and control is increasingly recognized, and based on preclinical studies, it is hypothesized that mobilization of leukocytes plays an important role in the anti-tumor effect. Thus, we examined how 10-min acute exercise modulates immune cells in newly diagnosed breast cancer patients. Blood samples were taken at rest, immediately after exercise and 30 min after exercise and phenotypic characterization of major leukocyte subsets was done using 9-color flow cytometry. Total leukocyte count increased by 29%, CD8+ T cell count by 34%, CD19+ B cell count by 18%, CD56+CD16+ NK cell count by 130%, and CD14+CD16+ monocyte count by 51% immediately after acute exercise. Mobilization of CD45+, CD8+, CD19+, and CD56+CD16+ cells correlated positively with exercising systolic blood pressure, heart rate percentage of age predicted maximal heart rate, rate pressure product, and mean arterial pressure. Our findings indicate that a single bout of acute exercise of only 10 min can cause leukocytosis in breast cancer patients. Mobilization of leukocytes appear to be directly related to the intensity of exercise. It is possible that the positive effect of exercise on oncologic outcome might be partly due to immune cell mobilization as documented in the present study.
CCL2 is required for initiation but not persistence of HIV infection mediated neurocognitive disease in mice
Authors: Kim Boe-Hyun , Hadas Eran , Kelschenbach Jennifer , Chao Wei , Gu Chao-Jiang , Potash Mary Jane , Volsky David J. 
Published: April 2023

AbstractHIV enters the brain within days of infection causing neurocognitive impairment (NCI) in up to half of infected people despite suppressive antiretroviral therapy. The virus is believed to enter the brain in infected monocytes through chemotaxis to the major monocyte chemokine, CCL2, but the roles of CCL2 in established NCI are not fully defined. We addressed this question during infection of conventional and CCL2 knockout mice with EcoHIV in which NCI can be verified in behavioral tests. EcoHIV enters mouse brain within 5 days of infection, but NCI develops gradually with established cognitive disease starting 25 days after infection. CCL2 knockout mice infected by intraperitoneal injection of virus failed to develop brain infection and NCI. However, when EcoHIV was directly injected into the brain, CCL2 knockout mice developed NCI. Knockout of CCL2 or its principal receptor, CCR2, slightly reduced macrophage infection in culture. Treatment of mice prior to and during EcoHIV infection with the CCL2 transcriptional inhibitor, bindarit, prevented brain infection and NCI and reduced macrophage infection. In contrast, bindarit treatment of mice 4 weeks after infection affected neither brain virus burden nor NCI. Based on these findings we propose that HIV enters the brain mainly through infected monocytes but that resident brain cells are sufficient to maintain NCI. These findings suggest that NCI therapy must act within the brain.
The association between acetylsalicylic acid and subarachnoid haemorrhage: the Framingham Heart Study
Authors: Ewbank Frederick , Birks Jacqueline , Bulters Diederik 
Published: April 2023

AbstractStudies investigating the association between acetylsalicylic acid (ASA) use and spontaneous subarachnoid haemorrhage (SAH) in the general population have produced conflicting results. The aim of this study is to clarify the relationship between SAH and ASA. We included all participants who reported on ASA use during interim examinations of the Framingham Heart Study Cohorts. Using Cox proportional-hazards regression modelling, we estimated the hazard ratio (HR) associated with ASA use. 7692 participants were included in this study. There were 30 cases of SAH during follow up, with an estimated incidence of 10.0 per 100,000 person- years (CI 6.90–14.15). Univariate analysis showed no association between regular ASA use and SAH (HR, 0.33 [0.08–1.41]; p = 0.14). This was similar when accounting for smoking (HR, 0.35 [0.08–1.51]; p = 0.16). Using a large longitudinal dataset from the Framingham Heart Study, we observed some evidence suggesting fewer SAH in those participants taking regular ASA. However, multivariate statistical analysis showed no significant association between ASA use and SAH. Due to the low incidence of SAH in the general population, the absolute number of SAH events was low and it remains uncertain if a significant effect would become apparent with more follow up.