bluuebunny/crossref_metadata_2025_split huggingface dataset:
The proneural subtype is not associated with survival benefit from bevacizumab in newly diagnosed glioblastoma: a secondary analysis of the GLARIUS trial
Authors: Weller Johannes , Zeyen Thomas , Schäfer Niklas , Schaub Christina , Potthoff Anna-Laura , Steinbach Joachim P. , Hau Peter , Seidel Clemens , Goldbrunner Roland , Tabatabai Ghazaleh , Vatter Hartmut , Tzaridis Theophilos , Schneider Matthias , Herrlinger Ulrich 
Published: October 2023

Abstract
Purpose
The AVAglio trial reported a significant survival benefit for first line bevacizumab treatment in patients with IDH wildtype glioblastoma of the proneural gene expression subtype. We here aim to replicate these findings in an independent trial cohort.

Methods
We evaluate the treatment benefit of bevacizumab according to gene expression subtypes of pretreatment tumor samples (n = 123) in the GLARIUS trial (NCT00967330) for MGMT unmethylated glioblastoma patients with Kaplan-Meier analyses, log-rank tests and Cox regression models.

Results
Employing the Phillips classifier, bevacizumab conferred a significant PFS advantage in patients with proneural IDH wild-type tumors (10.4 vs. 6.0 months, p = 0.002), but no OS advantage (16.4 vs. 17.4 months, p = 0.6). Multivariable analysis adjusting for prognostic covariates confirmed the absence of a significant OS advantage from bevacizumab (hazard ratio, 1.05, 95% CI, 0.42 to 2.64; p = 0.14). Further, there was no interaction between the proneural subtype and treatment arm (p = 0.15). These results were confirmed in analyses of tumor subgroups according to the Verhaak classifier.

Conclusion
In contrast to AVAglio, glioblastoma gene expression subgroups were not associated with a differential OS benefit from first-line bevacizumab in the GLARIUS trial.
On partially observed jump diffusions II: the filtering density
Authors: Davie Alexander , Germ Fabian , Gyöngy István 
Published: October 2023

AbstractA partially observed jump diffusion $$Z=(X_t,Y_t)_{t\in [0,T]}$$

Z
=

(

X
t

,

Y
t

)

t
∈
[
0
,
T
]

given by a stochastic differential equation driven by Wiener processes and Poisson martingale measures is considered when the coefficients of the equation satisfy appropriate Lipschitz and growth conditions. Under general conditions it is shown that the conditional density of the unobserved component $$X_t$$

X
t

given the observations $$(Y_s)_{s\in [0,t]}$$

(

Y
s

)

s
∈
[
0
,
t
]

exists and belongs to $$L_p$$

L
p

if the conditional density of $$X_0$$

X
0

given $$Y_0$$

Y
0

exists and belongs to $$L_p$$

L
p

.
Dyadic Clustering in International Relations
Authors: Carlson Jacob , Incerti Trevor , Aronow P. M. 
Published: October 2023

AbstractQuantitative empirical inquiry in international relations often relies on dyadic data. Standard analytic techniques do not account for the fact that dyads are not generally independent of one another. That is, when dyads share a constituent member (e.g., a common country), they may be statistically dependent, or “clustered.” Recent work has developed dyadic clustering robust standard errors (DCRSEs) that account for this dependence. Using these DCRSEs, we reanalyzed all empirical articles published in International Organization between January 2014 and January 2020 that feature dyadic data. We find that published standard errors for key explanatory variables are, on average, approximately half as large as DCRSEs, suggesting that dyadic clustering is leading researchers to severely underestimate uncertainty. However, most (67% of) statistically significant findings remain statistically significant when using DCRSEs. We conclude that accounting for dyadic clustering is both important and feasible, and offer software in R and Stata to facilitate use of DCRSEs in future research.
Feasibility of Live Video Feed Transmission from Unmanned Aerial Vehicles for Medical Surveillance During the 2022 Montreal Marathon
Authors: Lafortune Raphaël , Afram Eddy , Grossman Arielle , Drolet Ann-Rebecca , de Champlain François , Iannuzzi David , Homier Valérie 
Published: October 2023

AbstractIntroduction:In recent years, unmanned aerial vehicles (UAVs) have been increasingly used for medical surveillance purposes in mass-gathering events. No studies have investigated the reliability of live video transmission from UAVs for accurate identification of distressed race participants in need of medical attention. The aim of this study was to determine the proportion of time during which live medical surveillance UAV video feed was successfully transmitted and considered of sufficient quality to identify acute illness in runners participating in the 2022 Montreal Marathon (Canada).Methods:Four UAVs equipped with high-resolution cameras were deployed at two pre-defined high-risk areas for medical incidents located within the last 500 meters of the race. The video footage was transmitted in real-time during four consecutive hours to a remote viewing station where four research assistants monitored it on large screens. Interruptions in live feed transmission and moments with inadequate field of view (FOV) on runners were documented.Results:On September 25, 2022, a total of 6,916 athletes ran during the Montreal Marathon and Half Marathon. Out of the eight hours of video footage analyzed (four hours per high-risk area), 91.7% represented uninterrupted live video feed with an adequate view of the runners passing through the high-risk areas. There was a total of 18 live feed interruptions leading to a total interruption time of 22 minutes and 19 seconds (median interruption time of 32 seconds) and eight distinct moments with inadequate FOV on runners which accounted for 17 minutes and 33 seconds (median of 1 minute 47 seconds per moments with inadequate FOV). Active surveillance of drone-captured footage allowed early identification of two race participants in need of medical attention. Appropriate resources were dispatched, and UAV repositioning allowed for real-time viewing of the medical response.Conclusion:Live video transmission from UAVs for medical surveillance of runners passing through higher risk segments of a marathon for four consecutive hours is feasible. Live feed interruptions and moments with inadequate FOV could be minimized through practice and additional equipment redundancy.
On the Resolution Sensitivity of Equatorial Precipitation in a GFDL Global Atmospheric Model
Authors: Lin Pu , Ming Yi , Robinson Thomas 
Published: October 2023

AbstractWe performed a series of aquaplanet simulations at the horizontal resolution from 50 to 6 km with identical parameterization settings using the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4 implemented with the two‐moment Morrison‐Gettelman cloud microphysics with prognostic precipitation (GFDL AM4‐MG2). At the finer resolution, the global mean resolved‐scale precipitation increases and that from cumulus parameterization decreases. The model also simulates less/thinner clouds over the low latitudes and more/thicker clouds over the high latitudes as the resolution increases. The precipitation over the deep tropics is investigated in detail. We find little resolution sensitivity in the daily mean precipitation extremes. Changes of the equatorial resolved precipitation with resolution cannot be fully explained by the resolution dependence in the vertical velocity amplitude. We report a robust sensitivity in the convective organization over the deep tropics to the model resolution. In simulations of finer resolution, the localized convection is suppressed, and the organized convective system associated with large‐scale circulations becomes more prominent.
Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity
Authors: Fu Dan , Chang Ping , Liu Xue 
Published: October 2023

AbstractIt has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model.
Ice Shelf Water Structure Beneath the Larsen C Ice Shelf in Antarctica
Authors: Na Ji Sung , Davis Peter E. D. , Kim Byeong‐Hoon , Jin Emilia Kyung , Lee Won Sang 
Published: October 2023

AbstractUnderstanding ice shelf water (ISW) structure is crucial for studying the basal melting of ice shelves. In this study, we performed large‐eddy simulation experiments to assess ISW structure and basal melt patterns under different current velocity scenarios observed in the Larsen C ice shelf, Antarctica. The LES results revealed that the thickness of ISW is primarily determined by the meridional velocity (perpendicular to the grounding line), while the zonal velocity influences the potential temperature and salinity of ISW. We found that a key parameter determining the basal melt rate was northward meltwater advection which originates from variances in meltwater generation. This advection, in turn, leads to the tilted isopycnals and the potential for thermohaline interleaving in a diffusive convection regime. The different slopes of isopycnals induce distinct heat fluxes, resulting in different basal melt rates far from and near the grounding line (∼0.44 and 1.59 m yr−1, respectively).
Dissolved Organic Radiocarbon in the West Indian Ocean
Authors: Druffel Ellen R. M. , Lewis Christian B. , Griffin Sheila , Flaherty Alessandra , Rudresh Megha , Hauksson Niels E. , Key Robert M. , McNichol Ann P. , Hwang Jeomshik , Walker Brett D. 
Published: October 2023

AbstractWe report marine dissolved organic carbon (DOC) concentrations, and DOC Δ14C and δ13C in seawater collected from the West Indian Ocean during the GO‐SHIP I07N cruise in 2018. We find bomb 14C in DOC from the upper 1,000 m of the water column. There is no significant change in ∆14C of DOC in deep water northward, unlike that of dissolved inorganic carbon (DIC), suggesting that transport of deep water northward is not controlling the 14C age of DOC. Variability of DOC ∆14C, including high values in the deep waters, is more pronounced than in other oceans, suggesting that dissolution of surface derived particulate organic carbon is a source of modern carbon to deep DOC in the West Indian Ocean. Low δ13C are present at two of the five stations studied, suggesting a source of low δ13C DOC, or additional microbial utilization of deep DOC.
Tropical Cyclone Fullness and Outer Region Size Growth: The Role of Spatial Distribution of Very Deep Convection
Authors: Hong Jiacheng , Wu Qiaoyan 
Published: October 2023

AbstractThis paper investigates the relationship between the growth of the 34‐kt wind radius (R34) of tropical cyclones (TCs) and their fullness using best‐track data from 2001 to 2020. The storms were categorized into four groups based on a fullness scale: FS1 (fullness ≤ 0.4), FS2 (0.4 < fullness ≤ 0.6), FS3 (0.6 < fullness ≤ 0.8), and FS4 (fullness > 0.8). These groups exhibit unique spatial patterns of very deep convective clouds with infrared brightness temperatures <208 K. The mean R34 growth rates in 24 hr decrease from FS1 to FS4, which is linked to the higher coverage of very deep convection around R34 in storms with lower fullness. This study demonstrates that TC fullness can characterize the spatial distribution of deep convection in storms and serve as a representation of the growth of TC outer region size. These results have implications for understanding the mechanisms behind TC outer size growth.
A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model
Authors: Fan Chongxing , Chen Yi‐Hsuan , Chen Xiuhong , Lin Wuyin , Yang Ping , Huang Xianglei 
Published: October 2023

AbstractBecause longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m2 on the global average and 2 W/m2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.
The BRCA1/BARD1 complex recognizes pre-ribosomal RNA to facilitate homologous recombination
Authors: Wu Duo , Huang Huang , Chen Tenglong , Gai Xiaochen , Li Qilin , Wang Chunhui , Yao Jia , Liu Yu , Cai Shang , Yu Xiaochun 
Published: October 2023

AbstractThe BRCA1/BARD1 complex plays a key role in the repair of DNA double-strand breaks (DSBs) in both somatic cells and germ cells. However, the underlying molecular mechanism by which this complex mediates DSB repair is not fully understood. Here, we examined the XY body of male germ cells, where DSBs are accumulated. We show that the recruitment of the BRCA1/BARD1 complex to the unsynapsed axis of the XY body is mediated by pre-ribosomal RNA (pre-rRNA). Similarly, the BRCA1/BARD1 complex associates with pre-rRNA in somatic cells, which not only forms nuclear foci in response to DSBs, but also targets the BRCA1/BARD1 complex to DSBs. The interactions between the BRCT domains of the BRCA1/BARD1 complex and pre-rRNA induce liquid–liquid phase separations, which may be the molecular basis of DSB-induced nuclear foci formation of the BRCA1/BARD1 complex. Moreover, cancer-associated mutations in the BRCT domains of BRCA1 and BARD1 abolish their interactions with pre-rRNA. Pre-rRNA also mediates BRCA1-dependent homologous recombination, and suppression of pre-rRNA biogenesis sensitizes cells to PARP inhibitor treatment. Collectively, this study reveals that pre-rRNA is a functional partner of the BRCA1/BARD1 complex in the DSB repair.
Both sexes develop DKD in the CD1 uninephrectomized streptozotocin mouse model
Authors: Trink Jackie , Nmecha Ifeanyi Kennedy , Zhang Dan , MacDonald Melissa , Gao Bo , Krepinsky Joan C. 
Published: October 2023

AbstractDiabetic kidney disease (DKD) is characterized by a progressive increase in albuminuria and typical pathologic features. Recent studies have shown that sex is an important factor to consider in the pathogenesis of DKD. Presently, the hallmarks of this disease have primarily been studied in male rodent models. Here we explored the influence of sex in a murine model of DKD. CD1 mice underwent a right nephrectomy followed by intraperitoneal injection with 200 mg/kg streptozotocin to induce type 1 diabetes. Due to a high mortality rate, females required a reduction in streptozotocin to 150 mg/kg. Mice were followed for 12 weeks. Both sexes developed comparable hyperglycemia, while albuminuria and glomerular volume were increased to a greater degree in females and kidney hypertrophy was only seen in females. Males had a greater increase in blood pressure and glomerular basement membrane thickening, and a greater decrease in endpoint weight. Serum TGFβ1 levels were increased only in females. However, both sexes showed a similar increase in induction of kidney fibrosis. T cell and macrophage infiltration were also increased in both sexes. While some differences were observed, overall, both sexes developed clinical and pathologic characteristics of early DKD. Future studies evaluating therapeutic interventions can thus be assessed in both sexes of this DKD model.
An Honest Joker reveals stereotypical beliefs about the face of deception
Authors: Zhou Xingchen , Jenkins Rob , Zhu Lei 
Published: October 2023

AbstractResearch on deception detection has mainly focused on Simple Deception, in which false information is presented as true. Relatively few studies have examined Sophisticated Deception, in which true information is presented as false. Because Sophisticated Deception incentivizes the appearance of dishonesty, it provides a window onto stereotypical beliefs about cues to deception. Here, we adapted the popular Joker Game to elicit spontaneous facial expressions under Simple Deception, Sophisticated Deception, and Plain Truth conditions, comparing facial behaviors in static, dynamic nonspeaking, and dynamic speaking presentations. Facial behaviors were analysed via machine learning using the Facial Action Coding System. Facial activations were more intense and longer lasting in the Sophisticated Deception condition than in the Simple Deception and Plain Truth conditions. More facial action units intensified in the static condition than in the dynamic speaking condition. Simple Deception involved leaked facial behaviors of which deceivers were unaware. In contrast, Sophisticated Deception involved deliberately leaked facial cues, including stereotypical cues to lying (e.g., gaze aversion). These stereotypes were inaccurate in the sense that they diverged from cues in the Simple Deception condition—the actual appearance of deception in this task. Our findings show that different modes of deception can be distinguished via facial action analysis. They also show that stereotypical beliefs concerning cues to deception can inform behavior. To facilitate future research on these topics, the multimodal stimuli developed in this study are available free for scientific use.
Co-evolution of conditional cooperation and social norm
Authors: Battu Balaraju 
Published: October 2023

AbstractThe co-evolution of conditional cooperation and social norms has garnered significant attention, yet the underlying mechanisms remain elusive. Social norms result from empirical expectations, individual expectations of group behavior, and normative expectations, the population's expectations of individual behavior. Aligning these expectations aids in norm formation, but diverse individual reactions to observed behavior and their sensitivity to norm conformity can be challenging. In our study, the agents are initially endowed with diverse conditional expectations, which mirror their anticipations regarding group behavior and their inherent inclination to conform to social norms, indicative of their sensitivity to psychic costs. These agents engage in a repeated public goods game, where their decisions to cooperate are shaped by their conditional expectations and the observed levels of cooperation within their group. Concurrently, free riders experience psychic costs determined by the overall level of cooperation, contribution costs, and the individual’s inclination to adhere to social norms. Remarkably, our simulations unveil that agents commencing with random conditional expectations and a propensity to conform to norms can adapt to lower conditional expectations and moderate their propensity to conform to norms when initial cooperation levels are high and the contribution cost is reduced. Interestingly, increasing contribution costs intensify the population’s response to norm enforcement, but this doesn’t always result in a corresponding increase in cooperation. By incorporating population diversity and accounting for empirical and normative expectations within our model, we gain valuable insights into the intricate relationship between conditional cooperation and the emergence of social norms.
Evaluation of awareness and knowledge of CT technologist regarding diagnostic reference levels in Iran
Authors: MirDerikvand A. , Bagherzadeh S. , MohammadSharifi A. 
Published: October 2023

The purpose of this study was to determine the level of knowledge and awareness regarding radiation protection and Dose Reference Levels (DRLs) among 102 Computed Tomography (CT) technologists working in various Iranian hospitals. A questionnaire including 20 multiple-choice and open-format questions was divided into demographic information, general radiation protection knowledge, and DRL knowledge.
Regarding radiation protection knowledge concerning CT, about 56.9% of participants exhibited awareness of the dose display on the CT machine’s console, and about 78.4% selected the correct dosimetric units expressed CT dose. Unexpectedly, 90.2% of participants failed to define the concept of dose optimization. A significant association (p < 0.05) was established between technologists’ radiation protection and DRL knowledge and a degree of education, type of hospital, and job experience. In addition, the findings reveal a correlation between radiographers’ DRL knowledge and their propensity to enroll in training courses. 26.5% of participants exhibited awareness of DRLs in CT practice, while 49% and 76.5% of participants were unable to correctly identify DRLs concept and function. To reduce patient dose in accordance with the As Low As Reasonably Achievable (ALARA) radiation protection principle, CT technologists must improve their knowledge of radiation dose and local DRLs should be defined at least at the local level.
Clinical Grading Scales and Neuroprognostication in Acute Brain Injury
Authors: Reyes-Esteves Sahily , Kumar Monisha , Kasner Scott E. , Witsch Jens 
Published: October 2023

AbstractPrediction of neurological clinical outcome after acute brain injury is critical because it helps guide discussions with patients and families and informs treatment plans and allocation of resources. Numerous clinical grading scales have been published that aim to support prognostication after acute brain injury. However, the development and validation of clinical scales lack a standardized approach. This in turn makes it difficult for clinicians to rely on prognostic grading scales and to integrate them into clinical practice. In this review, we discuss quality measures of score development and validation and summarize available scales to prognosticate outcomes after acute brain injury. These include scales developed for patients with coma, cardiac arrest, ischemic stroke, nontraumatic intracerebral hemorrhage, subarachnoid hemorrhage, and traumatic brain injury; for each scale, we discuss available validation studies.