bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of estrogen on spatial navigation and memory
Authors: Joue Gina , Navarro-Schröder Tobias , Achtzehn Johannes , Moffat Scott , Hennies Nora , Fuß Johannes , Döller Christian , Wolbers Thomas , Sommer Tobias 
Published: February 2024

Abstract
Rationale
Animal studies suggest that the so-called “female” hormone estrogen enhances spatial navigation and memory. This contradicts the observation that males generally out-perform females in spatial navigation and tasks involving spatial memory. A closer look at the vast number of studies actually reveals that performance differences are not so clear.

Objectives
To help clarify the unclear performance differences between men and women and the role of estrogen, we attempted to isolate organizational from activational effects of estrogen on spatial navigation and memory.

Methods
In a double-blind, placebo-controlled study, we tested the effects of orally administered estradiol valerate (E2V) in healthy, young women in their low-hormone menstrual cycle phase, compared to healthy, young men. Participants performed several first-person, environmentally rich, 3-D computer games inspired by spatial navigation and memory paradigms in animal research.

Results
We found navigation behavior suggesting that sex effects dominated any E2 effects with men performing better with allocentric strategies and women with egocentric strategies. Increased E2 levels did not lead to general improvements in spatial ability in either sex but to behavioral changes reflecting navigation flexibility.

Conclusion
Estrogen-driven differences in spatial cognition might be better characterized on a spectrum of navigation flexibility rather than by categorical performance measures or skills.
A unified approach to goodness-of-fit testing for spherical and hyperspherical data
Authors: Ebner Bruno , Henze Norbert , Meintanis Simos 
Published: February 2024

AbstractWe propose a general and relatively simple method to construct goodness-of-fit tests on the sphere and the hypersphere. The method is based on the characterization of probability distributions via their characteristic function, and it leads to test criteria that are convenient regarding applications and consistent against arbitrary deviations from the model under test. We emphasize goodness-of-fit tests for spherical distributions due to their importance in applications and the relative scarcity of available methods.
Prognostic implication of heart failure stage and left ventricular ejection fraction for patients with in-hospital cardiac arrest: a 16-year retrospective cohort study
Authors: Wang Chih-Hung , Ho Li-Ting , Wu Meng-Che , Wu Cheng-Yi , Tay Joyce , Su Pei-I. , Tsai Min-Shan , Wu Yen-Wen , Chang Wei-Tien , Huang Chien-Hua , Chen Wen-Jone 
Published: February 2024

Abstract
Background
The 2022 AHA/ACC/HFSA guidelines for the management of heart failure (HF) makes therapeutic recommendations based on HF status. We investigated whether the prognosis of in-hospital cardiac arrest (IHCA) could be stratified by HF stage and left ventricular ejection fraction (LVEF).

Methods
This single-center retrospective study analyzed the data of patients who experienced IHCA between 2005 and 2020. Based on admission diagnosis, past medical records, and pre-arrest echocardiography, patients were classified into general IHCA, at-risk for HF, pre-HF, HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction or HF with reduced ejection fraction (HFmrEF-or-HFrEF) groups.

Results
This study included 2,466 patients, including 485 (19.7%), 546 (22.1%), 863 (35.0%), 342 (13.9%), and 230 (9.3%) patients with general IHCA, at-risk for HF, pre-HF, HFpEF, and HFmrEF-or-HFrEF, respectively. A total of 405 (16.4%) patients survived to hospital discharge, with 228 (9.2%) patients achieving favorable neurological recovery. Multivariable logistic regression analysis indicated that pre-HF and HFpEF were associated with better neurological (pre-HF, OR: 2.11, 95% confidence interval [CI]: 1.23–3.61, p = 0.006; HFpEF, OR: 1.90, 95% CI: 1.00–3.61, p = 0.05) and survival outcomes (pre-HF, OR: 2.00, 95% CI: 1.34–2.97, p < 0.001; HFpEF, OR: 1.91, 95% CI: 1.20–3.05, p = 0.007), compared with general IHCA.

Conclusion
HF stage and LVEF could stratify patients with IHCA into different prognoses. Pre-HF and HFpEF were significantly associated with favorable neurological and survival outcomes after IHCA. Further studies are warranted to investigate whether HF status-directed management could improve IHCA outcomes.
Chorioretinal biomarkers in hypothalamic amenorrhea
Authors: Savastano Maria Cristina , Fossataro Claudia , Carlà Matteo Mario , Cestrone Valentina , Biagini Ilaria , Sammarco Leonardo , Giannuzzi Federico , Fasciani Romina , Apa Rosanna , Lanzone Antonio , Diterlizzi Alice , Policriti Martina , Di Stasio Enrico , Killian Raphael , Rizzo Clara , Rizzo Stanislao 
Published: February 2024

Abstract
Purpose
The aim of our study was to evaluate changes in the retinal and choriocapillaris circulations in patients with hypothalamic amenorrhea.

Methods
Prospective, cross-sectional observational study on 25 patients (50 eyes) diagnosed with hypothalamic amenorrhea and 25 age-matched healthy women. Optical coherence tomography angiography (OCTA) was used to evaluate the vessel density (VD) of superficial capillary plexus (SCP), deep capillary plexus (DCP), and choriocapillaris VD layers in whole 6.4 × 6.4-mm image and in fovea grid-based image. In patients’ group, systemic parameters were collected: body mass index (BMI), endometrial rhyme thickness, follicle stimulating hormone (FSH), luteinizing hormone (LH), prolactin, insulin, and cortisol.

Results
SCP and DCP did not show any statistical difference when comparing patients and controls (all p > 0.05). Differently, choriocapillaris VD in the whole region showed a non-significant tendency toward higher values in the patients group in both eyes (p = 0.038 for right eye [RE], p = 0.044 for left eye [LE]). Foveal choriocapillaris VD was higher in hypothalamic amenorrhea women vs. healthy controls (66.0 ± 2.4 vs. 63.7 ± 6.6%, p = 0.136 for RE; 65.0 ± 2.4 vs. 61.6 ± 7.0%, p = 0.005 for LE). Focusing on correlation with systemic parameters, SCP and DCP foveal density had a medium/high effect size with endometrial rhyme, along with DCP in the fovea area vs. cortisol and SCP in the whole area vs. FSH.

Conclusion
When comparing hypothalamic amenorrhea patients to healthy subjects, OCTA detected changes in the choriocapillaris layer, showing increased VD in the early stage of the systemic pathology, suggesting that microvascular “compaction” could be a first phase of hypoestrogenism adaptation.
Seed priming with gas plasma-activated water in Ethiopia’s “orphan” crop tef (Eragrostis tef)
Authors: Fatelnig Lena M. M. , Chanyalew Solomon , Tadesse Mahilet , Kebede Worku , Hussein Nigusu , Iza Felipe , Tadele Zerihun , Leubner-Metzger Gerhard , Steinbrecher Tina 
Published: February 2024

Abstract
Main conclusion
Seed priming with gas plasma-activated water results in an increased ageing resilience in Eragrostis tef grains compared to a conventional hydropriming protocol.

Abstract
Tef (Eragrostis tef) is a cereal grass and a major staple crop of Ethiopia and Eritrea. Despite its significant importance in terms of production, consumption, and cash crop value, tef has been understudied and its productivity is low. In this study, tef grains have undergone different priming treatments to enhance seed vigour and seedling performance. A conventional hydropriming and a novel additive priming technology with gas plasma-activated water (GPAW) have been used and tef grains were then subjected to germination performance assays and accelerated ageing. Tef priming increases the germination speed and vigour of the grains. Priming with GPAW retained the seed storage potential after ageing, therefore, presenting an innovative environmental-friendly seed technology with the prospect to address variable weather conditions and ultimately food insecurity. Seed technology opens new possibilities to increase productivity of tef crop farming to achieve a secure and resilient tef food system and economic growth in Ethiopia by sustainable intensification of agriculture beyond breeding.
Granulation tissue-like spindle cell (sarcomatoid) carcinoma of the head and neck: a deceptively bland-looking underdiagnosed malignancy
Authors: Franchi Alessandro , Agaimy Abbas 
Published: February 2024

AbstractThe diagnosis of head and neck spindle cell squamous carcinoma (SC-SCC) is often challenging. Lesions with a prominent inflammatory infiltrate and reactive vessels may have a granulation tissue-like appearance, therefore being difficult to distinguish from reactive lesions, like contact ulcers, post-intubation granulomas, inflammatory pseudotumors, or benign vascular lesions. In this study, we analyzed the clinicopathological features of a series of 17 head and neck SC-SCC with granulation tissue-like appearance. All patients, but two, were males, ranging in age between 57 and 80 years. The larynx was the most frequently affected site (n = 12), followed by the tongue (n = 4). One tumor was hypopharyngeal. Most consult cases were submitted with benign suggestion or because of unexpected recurrences of granulation tissue polyps. Histologically, all lesions consisted of an ulcerated polypoid proliferation of moderately to markedly atypical spindle cells, with a minor component of conventional invasive or in situ squamous carcinoma. At least one cytokeratin cocktail was positive in 13 cases. The staining was limited to a few neoplastic cells in most cases. Positivity for p63, p40, and cytokeratins 5/6 was detected only in the conventional squamous cell carcinoma component, when present. ALK1 was negative in all cases. Sixteen cases were tested for p53 and all showed aberrant expression (12 diffusely positive and 4 of null-phenotype). The diagnosis of granulation tissue-like SC-SCC is challenging due to the close clinical and histological overlap with several benign conditions. Since the expression of epithelial markers is limited, the use of an immunohistochemical panel including p53 is recommended.
Interpretability of deep learning models in analysis of Spanish financial text
Authors: Vaca César , Astorgano Manuel , López-Rivero Alfonso J. , Tejerina Fernando , Sahelices Benjamín 
Published: February 2024

AbstractArtificial intelligence methods based on deep learning (DL) have recently made significant progress in many different areas including free text classification and sentiment analysis. We believe that corporate governance is one of these areas, where DL can generate very valuable and differential knowledge, for example, by analyzing the biographies of independent directors, which allows for qualitative modeling of their profile in an automatic way. For this technology to be accepted it is important to be able to explain how it generates its results. In this work we have developed a six-dimensional labeled dataset of independent director biographies, implemented three recurrent DL models based on LSTM and transformers along with four ensembles, one of which is an innovative proposal based on a multi-layer perceptron (MLP), trained them using Spanish language and economics and finance terminology and performed a comprehensive test study that demonstrates the accuracy of the results. We have also performed a complete study of explainability using the SHAP methodology by comparatively analyzing the developed models. We have achieved a mean error (MAE) of 8% in the modeling of the open text biographies, which has allowed us to perform a case study of time analysis that has detected significant variations in the composition of the Standard Expertise Profile (SEP) of the boards of directors, related to the crisis of the period 2008–2013. This work shows that DL technology can be accurately applied to free text analysis in the finance and economic domain, by automatically analyzing large volumes of data to generate knowledge that would have been unattainable by other means.
Ten years of an external quality program control in clinical microbiology: a statistical analysis of the results
Authors: Morales Clara , Uzeta Martha , Ramírez Mabel , Giraldo Ramón 
Published: February 2024

AbstractExternal quality assessment data of clinical microbiology obtained over ten years by the Colombian company PROASECAL in laboratories of seven countries in Central and South America are analyzed. The objective is to describe the quality of clinical microbiology results of the participants in the study period (2010–2021). This analysis includes the results of genus and species identification and proper reporting of both Gram staining and susceptibility testing. Data from 195 laboratories, which processed 31 bacteria, were analyzed. In this study, 32 % of laboratories were classified as good because they successfully determined the genus and species, 36 % fair, 12 % poor, and 20 % critical, to which recommendations for improvement were sent as part of the reports. In the analysis conducted for concordance between Genus, Morphology, and Gram, the success rates obtained are between 83 % and 94 %. Regarding antibiograms, the performance observed in Gram-positive bacteria ranges from 57 to 98 %, while in Gram-negative bacteria, it is between 82 and 98 %. The descriptive tools to explain external quality assessment results in clinical microbiology are limited to the percentage of successes in each item to be reported. For the analysis of the population data set, in this article, we propose to use contingency tables (including estimates of sensitivity, specificity, and predictive values) and equality of proportions tests as techniques that facilitate the interpretation of the data. On the other hand, the statistical analysis described here can be used as an analysis methodology for similar studies.
Recurrent miscarriage and low-titer antiphospholipid antibodies
Authors: Chen Jian , Yue Jing , Lu Yu , Li Ting , Li Xue , Zhang Jian-Yu 
Published: February 2024

Abstract
Objective
To evaluate the clinical features and pregnancy outcomes in patients experiencing recurrent miscarriage (RM) with either low-titer or medium-high titer positivity of antiphospholipid antibodies (aPL).

Methods
A retrospective review of medical records was conducted for patients with aPL positivity and recurrent miscarriage between 2018 and 2022. The clinical features, treatment strategies, outcomes were compared between the patients with low (n = 92) and medium (n = 32) titer of aPL.

Results
A total of 118 patients, resulting in 124 obstetric episodes (pregnancies), with a mean age of 33. 15 ± 4.56 and 31.47 ± 4.41 years between the two groups. The low-titer group exhibited a higher frequency of anti-cardiolipin antibodies IgM (P < 0.001), whereas the medium-high titer group demonstrated a higher frequency of anti-β2-glycoprotein 1 antibodies IgG (P < 0.001) and IgM (P = 0.032). Moreover, the medium-high titer group displayed a significantly elevated erythrocyte sedimentation rate compared to the low-titer group (P < 0.05). In the low-titer group, 71 patients (77.2%) received appropriate treatment, resulting in 48 live births (67.6%) and 23 repeat abortions (32.4%). In the medium-high titer group, 29 patients (90.6%) received relevant treatment, leading to 23 live births (79.3%) and 6 repeat abortions (20.7%). No significant differences were observed in live births or maternal-fetal complications between the two groups (all P > 0.05).

Conclusion
Noteworthy distinctions in laboratory parameters were identified between the low-titer and medium-high titer groups. However, when appropriately treated, the fetal-maternal outcomes were comparable in both groups. Timely intervention by clinicians is imperative to enhance pregnancy outcomes in patients experiencing recurrent miscarriage with low levels of aPL.

Key Points• This study challenges the conventional belief that only the higher antiphospholipid antibodies (aPL) titers directly correlated with worse pregnancy outcomes, which emphasized the importance of patients with low titer positive aPL-positive RM.• The results underscore the need for timely intervention in women with low titer aPL-positive RM, as it leads to favorable maternal–fetal outcomes.
Convergence of successive linear programming algorithms for noisy functions
Authors: Hansknecht Christoph , Kirches Christian , Manns Paul 
Published: February 2024

AbstractGradient-based methods have been highly successful for solving a variety of both unconstrained and constrained nonlinear optimization problems. In real-world applications, such as optimal control or machine learning, the necessary function and derivative information may be corrupted by noise, however. Sun and Nocedal have recently proposed a remedy for smooth unconstrained problems by means of a stabilization of the acceptance criterion for computed iterates, which leads to convergence of the iterates of a trust-region method to a region of criticality (Sun and Nocedal in Math Program 66:1–28, 2023. https://doi.org/10.1007/s10107-023-01941-9). We extend their analysis to the successive linear programming algorithm (Byrd et al. in Math Program 100(1):27–48, 2003. https://doi.org/10.1007/s10107-003-0485-4, SIAM J Optim 16(2):471–489, 2005. https://doi.org/10.1137/S1052623403426532) for unconstrained optimization problems with objectives that can be characterized as the composition of a polyhedral function with a smooth function, where the latter and its gradient may be corrupted by noise. This gives the flexibility to cover, for example, (sub)problems arising in image reconstruction or constrained optimization algorithms. We provide computational examples that illustrate the findings and point to possible strategies for practical determination of the stabilization parameter that balances the size of the critical region with a relaxation of the acceptance criterion (or descent property) of the algorithm.
The Danish Nationwide Electrocardiogram (ECG) Cohort
Authors: Polcwiartek Christoffer , Andersen Mikkel Porsborg , Christensen Helle Collatz , Torp-Pedersen Christian , Sørensen Kathrine Kold , Kragholm Kristian , Graff Claus 
Published: February 2024

AbstractThe electrocardiogram (ECG) is a non-invasive diagnostic tool holding significant clinical importance in the diagnosis and risk stratification of cardiac disease. However, access to large-scale, population-based digital ECG data for research purposes remains limited and challenging. Consequently, we established the Danish Nationwide ECG Cohort to provide data from standard 12-lead digital ECGs in both pre- and in-hospital settings, which can be linked to comprehensive Danish nationwide administrative registers on health and social data with long-term follow-up. The Danish Nationwide ECG Cohort is an open real-world cohort including all patients with at least one digital pre- or in-hospital ECG in Denmark from January 01, 2000, to December 31, 2021. The cohort includes data on standardized and uniform ECG diagnostic statements and ECG measurements including global parameters as well as lead-specific measures of waveform amplitudes, durations, and intervals. Currently, the cohort comprises 2,485,987 unique patients with a median age at the first ECG of 57 years (25th–75th percentiles, 40–71 years; males, 48%), resulting in a total of 11,952,430 ECGs. In conclusion, the Danish Nationwide ECG Cohort represents a novel and extensive population-based digital ECG dataset for cardiovascular research, encompassing both pre- and in-hospital settings. The cohort contains ECG diagnostic statements and ECG measurements that can be linked to various nationwide health and social registers without loss to follow-up.
Modelling the Deformation of Polydomain Liquid Crystal Elastomers as a State of Hyperelasticity
Authors: Anssari-Benam Afshin , Wei Zhengxuan , Bai Ruobing 
Published: February 2024

AbstractA hyperelasticity modelling approach is employed for capturing various and complex mechanical behaviours exhibited by macroscopically isotropic polydomain liquid crystal elastomers (LCEs). These include the highly non-linear behaviour of nematic-genesis polydomain LCEs, and the soft elasticity plateau in isotropic-genesis polydomain LCEs, under finite multimodal deformations (uniaxial and pure shear) using in-house synthesised acrylate-based LCE samples. Examples of application to capturing continuous softening (i.e., in the primary loading path), discontinuous softening (i.e., in the unloading path) and auxetic behaviours are also demonstrated on using extant datasets. It is shown that our comparatively simple model, which breaks away from the neo-classical theory of liquid crystal elastomers, captures the foregoing behaviours favourably, simply as states of hyperelasticity. Improved modelling results obtained by our approach compared with the existing models are also discussed. Given the success of the considered model in application to these datasets and deformations, the simplicity of its functional form (and thereby its implementation), and comparatively low(er) number of parameters, the presented isotropic hyperelastic strain energy function here is suggested for: (i) modelling the general mechanical behaviour of LCEs, (ii) the backbone in the neo-classical theory, and/or (iii) the basic hyperelastic model in other frameworks where the incorporation of the director, anisotropy, viscoelasticity, temperature, softening etc parameters may be required.
Forecasting Methane Data Using Multivariate Long Short-Term Memory Neural Networks
Authors: Luo Ran , Wang Jingyi , Gates Ian 
Published: February 2024

AbstractOver the past few decades, Alberta has witnessed a remarkable expansion in its oil and gas sector. Unfortunately, this growth has come at a cost, as Alberta has become the fastest-growing source of pollutant emissions in greenhouse gases (GHGs), sulphur emissions, and water pollution in Canada. Among these GHGs, methane stands out as the second most prevalent GHG, possessing a global warming potential ~ 28 times higher than carbon dioxide over a span of 100 years, and ~ 80 times higher over a period of 20 years. Since 1986, the Alberta Energy Regulator (AER) has been diligently gathering data on methane concentrations. Although this data is publicly available, its analysis has not been thoroughly explored. Our study aims to investigate the impact of temperature, wind speed, and wind direction on the predictions of methane concentration time series data, utilizing a long short-term memory (LSTM) neural network model. Our findings indicate that the inclusion of climate variables enhances the predictive capabilities of the LSTM model. However, the results show that it is not obvious which variable has the most impact on the improvement although temperature appears to have a better effect on improving predictive performance compared to wind speed and direction. The results also suggest that the variance of the input data does not affect forecasting performance.