bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rising premature menopause and variations by education level in India
Authors: Babbar Karan , Singh Vanita , Sivakami M. 
Published: August 2024

AbstractThe proportion of women experiencing premature menopause is on the rise in India, particularly in the age groups of 30–39 years. Consequently, there is a need to understand the factors influencing the prevalence of premature menopausal status among women. Our study uses the data from 180,743 women gathered during the latest Indian version of the Demography Health Survey (National Family Health Survey-5). Our results suggest that close to 5% of women in rural areas and 3% of women in urban areas experience premature menopause, and this figure varies across Indian States. The regression results show that surgical menopause, lower levels of education, poorer wealth index, rural residence, female sterilization, and insurance coverage are key drivers of premature menopause. One of the striking factors is that the prevalence of premature menopause among those with the lowest levels of education (6.85%) is around seven times higher than those with the highest level of education (0.94%). We conducted a decomposition analysis to delve into the factors contributing to this inequality. The results show that undergoing a hysterectomy (surgical menopause) account for 73% of the gap in premature menopausal rates between women with the lowest and highest levels of education. This indicates that women with poor education are more likely to undergo hysterectomy at a younger age. This finding warrants further exploration as we would expect that women from lower socio-economic background would have limited access to surgical care, however, our results suggest otherwise. This perhaps indicates a lack of awareness, lack of alternative treatment options, and over-reliance on surgical care while neglecting conservative management. Our results have implications for addressing the diverse needs of the increasing number of women in their post-menopause phase and for focusing on conservative treatment options for these women.
High-resolution mapping of urban Aedes aegypti immature abundance through breeding site detection based on satellite and street view imagery
Authors: Knoblauch Steffen , Su Yin Myat , Chatrinan Krittin , de Aragão Rocha Antonio Augusto , Haddawy Peter , Biljecki Filip , Lautenbach Sven , Resch Bernd , Arifi Dorian , Jänisch Thomas , Morales Ivonne , Zipf Alexander 
Published: August 2024

AbstractIdentification of Aedes aegypti breeding hotspots is essential for the implementation of targeted vector control strategies and thus the prevention of several mosquito-borne diseases worldwide. Training computer vision models on satellite and street view imagery in the municipality of Rio de Janeiro, we analyzed the correlation between the density of common breeding grounds and Aedes aegypti infestation measured by ovitraps on a monthly basis between 2019 and 2022. Our findings emphasized the significance (p ≤ 0.05) of micro-habitat proxies generated through object detection, allowing to explain high spatial variance in urban abundance of Aedes aegypti immatures. Water tanks, non-mounted car tires, plastic bags, potted plants, and storm drains positively correlated with Aedes aegypti egg and larva counts considering a 1000 m mosquito flight range buffer around 2700 ovitrap locations, while dumpsters, small trash bins, and large trash bins exhibited a negative association. This complementary application of satellite and street view imagery opens the pathway for high-resolution interpolation of entomological surveillance data and has the potential to optimize vector control strategies. Consequently it supports the mitigation of emerging infectious diseases transmitted by Aedes aegypti, such as dengue, chikungunya, and Zika, which cause thousands of deaths each year.
Measurement of hepatic glucose (18F-fluorodeoxyglucose) uptake with positron emission tomography-magnetic resonance imaging in fumonisin B intoxicated rabbit bucks
Authors: Szabó András , Emri Miklós , Tóth Zoltán , Fajtai Dániel , Donkó Tamás , Petneházy Örs , Kőrösi Dénes , Repa Imre , Takács Alíz , Kisiván Tímea , Gerencsér Zsolt , Ali Omeralfaroug , Turbók Janka , Bóta Brigitta , Gömbös Patrik , Romvári Róbert , Kovács Melinda 
Published: August 2024

AbstractRabbit bucks (bodyweight 5 kg) underwent dietary intoxication with fumonisin B series mycotoxins (FB1 + FB2 + FB3, 15 mg/kg diet) for 14 days to test the applicability of positron emission tomography-magnetic resonance (PET MR) hybrid imaging in characterizing experimentally induced mild hepatotoxicosis. 18F-fluorodeoxyglucose (18F-FDG) radiotracer-aided imaging was performed before and after FBs administration on identical animals, and at both time points, blood was sampled for haematology and clinical chemistry. Kinetic PET image analysis revealed time-activity curves with uptake maxima below 1 min in the liver, renal cortex, portal vein, lung and coarctatio aortae. In the frame of static PET image analysis, based on the standardized uptake value (SUV), the so-called metabolic liver volume (MLV, liver volume defined by over 0.9 × average liver SUV) and the total liver glycolysis (TLG, MLV multiplied by the SUVmean) were calculated. Mycotoxicosis increased total liver glycolysis (p < 0.04) after 14 days and liver tissue TLG inhomogeneity was minimal. Pearson correlation between TLG and alkaline phosphatase (ALP) was positive (0.515), while negative with LDH and AST (− 0.721 and − 0.491, respectively). Results indicate a slight hepatic mycotoxin effect and significantly increased glucose uptake intensity, which has been sensitively detected with molecular imaging (18F-FDG PET MRI) in the rabbit model.
Antox targeting AGE/RAGE cascades to restore submandibular gland viability in rat model of type 1 diabetes
Authors: Ahmad Marwa M. , Hassan Heba A. , Saadawy Sara F. , Ahmad Enssaf Ahmad , Elsawy Naser Ahmed Mahmoud , Morsy Manal Mohammad 
Published: August 2024

AbstractDiabetes mellitus (DM) is a chronic disorder of glucose metabolism that threatens several organs, including the submandibular (SMG) salivary glands. Antox (ANX) is a strong multivitamin with significant antioxidant benefits. The goal of this study was to demonstrate the beneficial roles of ANX supplementation in combination with insulin in alleviating diabetic SMG changes. For four weeks, 30 rats were divided into equal five groups (n = 6): (1) control group; (2) diabetic group (DM), with DM induced by streptozotocin (STZ) injection (50 mg/kg i.p.); (3) DM + ANX group: ANX was administrated (10 mg/kg/day/once daily/orally); (4) DM + insulin group: insulin was administrated 1U once/day/s.c.; and (5) DM + insulin + ANX group: co-administrated insulin. The addition of ANX to insulin in diabetic rats alleviated hyposalivation and histopathological alterations associated with diabetic rats. Remarkably, combined ANX and insulin exerted significant antioxidant effects, suppressing inflammatory and apoptotic pathways associated with increased salivary advanced glycation end-product (AGE) production and receptor for advanced glycation end-product expression (RAGE) activation in diabetic SMG tissues. Combined ANX and insulin administration in diabetic rats was more effective in alleviating SMG changes (functions and structures) than administration of insulin alone, exerting suppressive effects on AGE production and frustrating RAGE downstream pathways.
Adhesion of pancreatic tumor cell clusters by desmosomal molecules enhances early liver metastases formation
Authors: Dietrich Niclas , Castellanos-Martinez Ramon , Kemmling Julia , Heuser Arnd , Schnoor Michael , Schinner Camilla , Spindler Volker 
Published: August 2024

AbstractDesmosomes are intercellular adhesion complexes providing mechanical coupling and tissue integrity. Previously, a correlation of desmosomal molecule expression with invasion and metastasis formation in several tumor entities was described together with a relevance for circulating tumor cell cluster formation. Here, we investigated the contribution of the desmosomal core adhesion molecule desmoglein-2 (DSG2) to the initial steps of liver metastasis formation by pancreatic cancer cells using a novel ex vivo liver perfusion mouse model. We applied the pancreatic ductal adenocarcinoma cell line AsPC-1 with and without a knockout (KO) of DSG2 and generated mouse lines with a hepatocyte-specific KO of the known interacting partners of DSG2 (DSG2 and desmocollin-2). Liver perfusion with DSG2 KO AsPC-1 cells led to smaller circulating cell clusters and a reduced number of cells adhering to murine livers compared to control cells. While this was independent of the expression levels of desmosomal adhesion molecules in hepatocytes, we show that increased cluster size of cancer cells, which correlates with stronger cell–cell adhesion and expression of desmosomal molecules, is a major factor contributing to the early phase of metastatic spreading. In conclusion, impaired desmosomal adhesion results in reduced circulating cell cluster size, which is relevant for seeding and attachment of metastatic cells to the liver.
A label-free quantification method for assessing sex from modern and ancient bovine tooth enamel
Authors: Kotli Paula , Morgenstern David , Bocquentin Fanny , Khalaily Hamoudi , Horwitz Liora Kolska , Boaretto Elisabetta 
Published: August 2024

AbstractIdentification of the sex of modern, fossil and archaeological animal remains offers many insights into their demography, mortality profiles and domestication pathways. However, due to many-factors, sex determination of osteological remains is often problematic. To overcome this, we have developed an innovative protocol to determine an animal’s sex from tooth enamel, by applying label-free quantification (LFQ) of two unique AmelY peptides ‘LRYPYP’ (AmelY;[M+2]$$^{2+}$$

2
+

404.7212 m/z) and ‘LRYPYPSY’ (AmelY;[M+2]$$^{2+}$$

2
+

529.7689 m/z) that are only present in the enamel of males. We applied this method to eight modern cattle (Bos taurus) of known sex, and correctly assigned them to sex. We then applied the same protocol to twelve archaeological Bos teeth from the Neolithic site of Beisamoun, Israel (8-th–7-th millennium BC) and determined the sex of the archaeological samples. Since teeth are usually better preserved than bones, this innovative protocol has potential to facilitate sex determination in ancient and modern bovine remains that currently cannot be sexed.
Acetylcholine and choline in honey bee (Apis mellifera) worker brood food are seasonal and age-dependent
Authors: Siefert Paul , Lau Helene , Leutz Vivien , Leonhardt Sara Diana , Schneider Gaby , Klein Jochen , Grünewald Bernd 
Published: August 2024

AbstractNursing honeybees produce brood food with millimolar concentrations of acetylcholine (ACh), which is synthesized through head gland secretions mixed with honey stomach contents. While we previously demonstrated the necessity of ACh for proper larval development, the dynamics of ACh levels throughout ontogenesis and their seasonal variations have remained unclear until now. Our HPLC analysis reveals dependencies of choline and ACh levels on larval development days (LDDs), influenced by seasonal (April–September) variations. Median ACh concentrations peak on LDD 2, declining significantly toward cell capping, while choline levels are lowest during the initial LDDs, rising markedly toward cell capping. Seasonal patterns show peak ACh levels from April to June and a low in August, paralleling choline's peak in July and low in August. This seasonality holds consistently across multiple years (2020–2022) and colonies, despite potential variations in colony performance and environmental conditions. Our analysis found no correlation between temperature, sunshine, precipitation, or favourable foraging days and ACh/choline levels, suggesting the involvement of additional factors. These findings underscore the seasonal fluctuation of ACh levels and its potential implications for the genetic programs governing winter bee development.
Exploring the predictive factors of heart disease using rare association rule mining
Authors: Darrab Sadeq , Broneske David , Saake Gunter 
Published: August 2024

AbstractCardiovascular diseases continue to be the leading cause of mortality worldwide, claiming a significant number of lives each year. Despite the advancements in predictive models, including logistic regression, neural networks, and random forests, these techniques often lack transparency and interpretability, limiting their practical application in clinical settings. To address this challenge, this research introduces EPFHD-RARMING, an innovative approach designed to enhance the understanding and predictability of heart disease through the discovery of rare and meaningful patterns. EPFHD-RARMING utilizes rare association rule mining to uncover hidden and unexpected rules that identify critical factors contributing to heart disease. This method is particularly adept at identifying high-risk patterns in individuals who appear healthy but may develop heart disease under certain conditions, thus facilitating early intervention and preventive measures. By integrating these insights with established feature engineering techniques, EPFHD-RARMING enhances its practical utility, enabling medical professionals to proactively manage patient care and tailor interventions to individual risk profiles. This study demonstrates the effectiveness of EPFHD-RARMING in providing a deeper, actionable understanding of the complex dynamics of heart disease. The model’s ability to identify and interpret rare patterns holds significant promise for advancing medical analytics and improving patient outcomes. Moreover, the applicability of EPFHD-RARMING extends beyond the healthcare domain, offering valuable insights in various fields where the discovery of rare patterns is critical, such as finance, marketing, and cybersecurity. This study conducts a comprehensive evaluation, which demonstrates the superior performance of EPFHD-RARMING compared to traditional predictive models in identifying key factors contributing to heart disease, in terms of interestingness, explainability, and comprehensiveness of insights. The results underscore the potential of this innovative approach to revolutionize our understanding and prediction of heart disease, ultimately contributing to more effective and personalized healthcare solutions. This research emphasizes the importance of rare association rule mining in medical analytics and paves the way for future studies to explore and utilize these techniques across diverse domains.
Incorporating body mass index into esophageal manometry metrics and mean nocturnal baseline impedance for the evaluation of gastro-esophageal reflux disease
Authors: Tong Meng-Han , Zhang Ming-Jie , Wang Li-Xia , Zhang Zhi-Feng , Duan Zhi-Jun 
Published: August 2024

AbstractThis study aims to enhance the effectiveness of high resolution manometry (HRM) and pH-impedance monitoring metrics in distinguishing between gastro-esophageal reflux disease (GERD) and non-GERD. A retrospective propensity score matching (PSM) study was conducted on 643 patients with GERD symptoms. PSM matched 134 GERD patients with 134 non-GERD controls. Body mass index (BMI), intra-esophageal pressure (IEP) and intra-gastric pressure (IGP) were significantly higher in the GERD group compared to the non-GERD group. BMI was correlated with IEP and IGP positively. IGP was positively correlated with esophagogastric (EGJ) pressure (EGJ-P) in participants with EGJ type 1 and 2, but not in participants with EGJ type 3. BMI was correlated with distal MNBI negatively. Logistic regression showed BMI as an independent risk factor for GERD. Receiver operating characteristic curve (ROC) and decision curve analysis (DCA) showed that BMI adjusted EGJ contractile integral (EGJ-CI) and BMI adjusted MNBI were superior to the corresponding original ones in predicting GERD susceptibility. According to the findings, BMI and IGP are the main factors contributing to the development of GERD. BMI affects IEP through the adaptive response of EGJ-P to IGP. Incorporating BMI into the calculations of EGJ-CI and MNBI can improve their ability in predicting GERD susceptibility.
Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit
Authors: Forte Alessandro , Gawne Thomas , Alaa El-Din Karim K. , Humphries Oliver S. , Preston Thomas R. , Crépisson Céline , Campbell Thomas , Svensson Pontus , Azadi Sam , Heighway Patrick , Shi Yuanfeng , Chin David A. , Smith Ethan , Baehtz Carsten , Bouffetier Victorien , Höppner Hauke , Amouretti Alexis , McGonegle David , Harmand Marion , Collins Gilbert W. , Wark Justin S. , Polsin Danae N. , Vinko Sam M. 
Published: August 2024

AbstractResonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe2O3, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds.
Neural Decoding of Spontaneous Overt and Intended Speech
Authors: Dash Debadatta , Ferrari Paul , Wang Jun 
Published: August 2024

Purpose:
The aim of this study was to decode intended and overt speech from neuromagnetic signals while the participants performed spontaneous overt speech tasks without cues or prompts (stimuli).

Method:
Magnetoencephalography (MEG), a noninvasive neuroimaging technique, was used to collect neural signals from seven healthy adult English speakers performing spontaneous, overt speech tasks. The participants randomly spoke the words yes or no at a self-paced rate without cues. Two machine learning models, namely, linear discriminant analysis (LDA) and one-dimensional convolutional neural network (1D CNN), were employed to classify the two words from the recorded MEG signals.

Results:
LDA and 1D CNN achieved average decoding accuracies of 79.02% and 90.40%, respectively, in decoding overt speech, significantly surpassing the chance level (50%). The accuracy for decoding intended speech was 67.19% using 1D CNN.

Conclusions:
This study showcases the possibility of decoding spontaneous overt and intended speech directly from neural signals in the absence of perceptual interference. We believe that these findings make a steady step toward the future spontaneous speech-based brain–computer interface.
Get REAL: Development and Validation of the Rubric for the Evaluation of Apps for Learning
Authors: Weber Melanie Ann , Anzilotti Mia , Gormley Reece , Huber Christina , McGarvey Alyssa , McKee Grace , Ogden Claire , Seinfeld Hannah , Wank Julia , Olszewski Arnold 
Published: August 2024

Purpose:
Technology, including educational applications (apps), is commonly used in schools by teachers and speech-language pathologists. Nonetheless, very little research has examined the efficacy of these apps for student learning or how to choose appropriate apps for instruction. Several previous rubrics to evaluate the instructional quality of apps have been published, yet limitations such as user training and time to administer have limited their use. The purpose of this study was to develop a comprehensive yet easy-to-use rubric for evaluating educational apps.

Method:
An iterative process guided the development and assessment of the Rubric for the Evaluation of Apps for Learning (REAL). Prior rubrics were synthesized to develop a comprehensive list of items. These items were condensed for simplicity purposes. A focus group and a survey of teachers and speech-language pathologists validated the rubric items and informed revisions. Multiple rounds of interrater reliability calculations and rubric revisions resulted in a final draft of the rubric, included here.

Results:
The final version of REAL passed validation and demonstrated evidence of interrater reliability among familiar users (Fleiss' κ = .71–.77) and those with no prior experience using the rubric (Fleiss' κ = .46). The majority of practitioners (90%) reported that they would use the rubric in their practice. REAL was used to rate 10 apps teaching phonics and 10 apps teaching social skills; scores are presented for demonstration purposes and indicate a wide range of rankings.

Conclusions:
REAL is a feasible, comprehensive rubric for evaluating the quality of educational apps, for which there may be little to no published research evidence. Practitioners may be overwhelmed with the number of commercially available apps. REAL provides a tool to help them make decisions that benefit the children they serve.
Ultra‐low loss 2‐core fibre for expanding submarine cable capacity
Authors: Hasegawa Takemi 
Published: August 2024

Abstract2‐core fibre for submarine cable is becoming the first commercial application of multi‐core fibre, which should enable to expand the capacity beyond the current limitation of submarine cable size. For successful commercial applications of 2‐core fibre, it is important to minimise the complexities in manufacturing, splicing, and fibre handling. The 2‐core fibre design for minimum complexity is reviewed.
How wind forecast updates are balanced in coupled European intraday markets
Authors: Boehnke Florian , Kolkmann Sven , Leisen Robin , Weber Christoph 
Published: August 2024

AbstractThe market coupling of adjacent market zones is a key element in terms of coping with rising levels of uncertainty in the European energy system due to the adoption of more volatile renewable energy sources. An adequate analysis of this issue yet requires an appropriate consideration of uncertainty along with a detailed modelling of market coupling. Thus, we present a novel approach combining a comprehensive unit commitment and dispatch model with a sophisticated methodology to reflect the uncertainty of wind power generation by considering forecast updates for the German market region in the market clearing process. Subsequently, we investigate the impact of uncertainty on cross‐border electricity flows in a European case study. Our results show that all adjacent market zones and all relevant technologies significantly contribute to balancing forecast updates in Germany, underlining the benefits of intraday market coupling. Further, we observe that a joint and unrestricted intraday market is the most cost‐efficient market solution. Finally, our analyses show that more extensive market coupling is indispensable for the further integration of renewable energy sources in the future.