bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sick leave one year after COVID-19 infection: a nationwide cohort study during the first wave in Sweden
Authors: Abzhandadze Tamar , Westerlind Emma , Palstam Annie , Sunnerhagen Katharina S. , Persson Hanna C. 
Published: January 2024

AbstractThis study aimed to investigate the patterns of sick leave, as well as factors associated with sick leave due to COVID-19 during one year after the COVID-19 diagnosis, and sex-related aspects on sick leave. This nationwide study involved 11,902 individuals who received sickness benefits for COVID-19 during the first wave of the pandemic. Data from three Swedish registries were analyzed for sick leave that commenced between March 1 and August 31, 2020, with a follow-up period of 12 months. Sick leave due to COVID-19 was counted as the number of days with sickness benefits and required to include at least one registered COVID-19 diagnosis. The median duration of sick leave was 35 days, and 347 (2.9%) individuals continued their sick leave during the entire follow-up period. Furthermore, 1 year later, the cumulative incidence of sick leave was slightly higher in males (3.5%) compared to females (2.7%). Older age, being single with no children, diagnosed with the virus, medium income level, history of sick leave, and need for inpatient care were significantly associated with a higher duration of sick leave due to COVID-19, both in the total population and when stratified by sex. These results indicated that three out of 100 (3%) patients were still on sick leave 1 year after their COVID-19 diagnosis. Aspects regarding the importance of sick leave duration differed between males and females and comprised sociodemographic characteristics and need for inpatient care. The results indicated the complexity of sick leave due to COVID-19.
A multi-stage anticipated surprise model with dynamic expectation for economic decision-making
Authors: Chan Ho Ka , Toyoizumi Taro 
Published: January 2024

AbstractThere are many modeling works that aim to explain people’s behaviors that violate classical economic theories. However, these models often do not take into full account the multi-stage nature of real-life problems and people’s tendency in solving complicated problems sequentially. In this work, we propose a descriptive decision-making model for multi-stage problems with perceived post-decision information. In the model, decisions are chosen based on an entity which we call the ‘anticipated surprise’. The reference point is determined by the expected value of the possible outcomes, which we assume to be dynamically changing during the mental simulation of a sequence of events. We illustrate how our formalism can help us understand prominent economic paradoxes and gambling behaviors that involve multi-stage or sequential planning. We also discuss how neuroscience findings, like prediction error signals and introspective neuronal replay, as well as psychological theories like affective forecasting, are related to the features in our model. This provides hints for future experiments to investigate the role of these entities in decision-making.
Deep learning-based identification of eyes at risk for glaucoma surgery
Authors: Wang Ruolin , Bradley Chris , Herbert Patrick , Hou Kaihua , Ramulu Pradeep , Breininger Katharina , Unberath Mathias , Yohannan Jithin 
Published: January 2024

AbstractTo develop and evaluate the performance of a deep learning model (DLM) that predicts eyes at high risk of surgical intervention for uncontrolled glaucoma based on multimodal data from an initial ophthalmology visit. Longitudinal, observational, retrospective study. 4898 unique eyes from 4038 adult glaucoma or glaucoma-suspect patients who underwent surgery for uncontrolled glaucoma (trabeculectomy, tube shunt, xen, or diode surgery) between 2013 and 2021, or did not undergo glaucoma surgery but had 3 or more ophthalmology visits. We constructed a DLM to predict the occurrence of glaucoma surgery within various time horizons from a baseline visit. Model inputs included spatially oriented visual field (VF) and optical coherence tomography (OCT) data as well as clinical and demographic features. Separate DLMs with the same architecture were trained to predict the occurrence of surgery within 3 months, within 3–6 months, within 6 months–1 year, within 1–2 years, within 2–3 years, within 3–4 years, and within 4–5 years from the baseline visit. Included eyes were randomly split into 60%, 20%, and 20% for training, validation, and testing. DLM performance was measured using area under the receiver operating characteristic curve (AUC) and precision-recall curve (PRC). Shapley additive explanations (SHAP) were utilized to assess the importance of different features. Model prediction of surgery for uncontrolled glaucoma within 3 months had the best AUC of 0.92 (95% CI 0.88, 0.96). DLMs achieved clinically useful AUC values (> 0.8) for all models that predicted the occurrence of surgery within 3 years. According to SHAP analysis, all 7 models placed intraocular pressure (IOP) within the five most important features in predicting the occurrence of glaucoma surgery. Mean deviation (MD) and average retinal nerve fiber layer (RNFL) thickness were listed among the top 5 most important features by 6 of the 7 models. DLMs can successfully identify eyes requiring surgery for uncontrolled glaucoma within specific time horizons. Predictive performance decreases as the time horizon for forecasting surgery increases. Implementing prediction models in a clinical setting may help identify patients that should be referred to a glaucoma specialist for surgical evaluation.
Predicting the subjective intensity of imagined experiences from electrophysiological measures of oscillatory brain activity
Authors: Arnold Derek H. , Saurels Blake W. , Anderson Natasha , Andresen Isabella , Schwarzkopf Dietrich S. 
Published: January 2024

AbstractMost people can conjure images and sounds that they experience in their minds. There are, however, marked individual differences. Some people report that they cannot generate imagined sensory experiences at all (aphantasics) and others report that they have unusually intense imagined experiences (hyper-phantasics). These individual differences have been linked to activity in sensory brain regions, driven by feedback. We would therefore expect imagined experiences to be associated with specific frequencies of oscillatory brain activity, as these can be a hallmark of neural interactions within and across regions of the brain. Replicating a number of other studies, relative to a Resting-State we find that the act of engaging in auditory or in visual imagery is linked to reductions in the power of oscillatory brain activity across a broad range of frequencies, with prominent peaks in the alpha band (8–12 Hz). This oscillatory activity, however, did not predict individual differences in the subjective intensity of imagined experiences. For audio imagery, these were rather predicted by reductions within the theta (6–9 Hz) and gamma (33–38 Hz) bands, and by increases in beta (15–17 Hz) band activity. For visual imagery these were predicted by reductions in lower (14–16 Hz) and upper (29–32 Hz) beta band activity, and by an increase in mid-beta band (24–26 Hz) activity. Our data suggest that there is sufficient ground truth in the subjective reports people use to describe the intensity of their imagined sensory experiences to allow these to be linked to the power of distinct rhythms of brain activity. In future, we hope to combine this approach with better measures of the subjective intensity of imagined sensory experiences to provide a clearer picture of individual differences in the subjective intensity of imagined experiences, and of why these eventuate.
Association between gestational weight gain and chronic disease risks in later life
Authors: Kamihara Yuki , Ogawa Kohei , Morisaki Naho , Arata Naoko , Wada Seiji 
Published: January 2024

AbstractTo assess the association between gestational weight gain (GWG) and the risk of developing chronic diseases in later life, this historical cohort study of 318 non-overweight women was conducted between April 2017 and November 2020 at a hospital in Tokyo. Data about GWG in the last pregnancy and the development of any chronic diseases of the subjects were retrieved from the women’s Maternal and Child Health Handbooks and through a questionnaire survey, respectively. The outcomes were chronic diseases, such as diabetes mellitus (DM), hypertension, hyperlipidemia, and being overweight (body mass index [BMI] ≥ 25 kg/m2). Association between GWG and outcomes were assessed using a logistic regression analysis.There were significant positive linear associations between GWG and the risks of developing DM, hypertension, and being overweight (P = 0.013, 0.050, and 0.017, respectively). After adjusting for later-life BMI, a significant association between GWG and DM (P = 0.025) remained, but the association between GWG and hypertension disappeared. GWG was significantly associated with DM, hypertension, and being overweight later in life. Although the association between GWG and DM was partially independent of BMI later in life, the association between GWG and hypertension was influenced by being overweight later in life.
Radiation-induced changes in energy metabolism result in mitochondrial dysfunction in salivary glands
Authors: Buss Lauren G. , Rheinheimer Brenna A. , Limesand Kirsten H. 
Published: January 2024

AbstractSalivary glands are indirectly damaged during radiotherapy for head and neck cancer, resulting in acute and chronic hyposalivation. Current treatments for radiation-induced hyposalivation do not permanently restore function to the gland; therefore, more mechanistic understanding of the damage response is needed to identify therapeutic targets for lasting restoration. Energy metabolism reprogramming has been observed in cancer and wound healing models to provide necessary fuel for cell proliferation; however, there is limited understanding of alterations in energy metabolism reprogramming in tissues that fail to heal. We measured extracellular acidification and oxygen consumption rates, assessed mitochondrial DNA copy number, and tested fuel dependency of irradiated primary salivary acinar cells. Radiation treatment leads to increases in glycolytic flux, oxidative phosphorylation, and ATP production rate at acute and intermediate time points. In contrast, at chronic radiation time points there is a significant decrease in glycolytic flux, oxidative phosphorylation, and ATP production rate. Irradiated salivary glands exhibit significant decreases in spare respiratory capacity and increases in mitochondrial DNA copy number at days 5 and 30 post-treatment, suggesting a mitochondrial dysfunction phenotype. These results elucidate kinetic changes in energy metabolism reprogramming of irradiated salivary glands that may underscore the chronic loss of function phenotype.
Unsupervised learning-based approach for detecting 3D edges in depth maps
Authors: Aggarwal Ayush , Stolkin Rustam , Marturi Naresh 
Published: January 2024

Abstract3D edge features, which represent the boundaries between different objects or surfaces in a 3D scene, are crucial for many computer vision tasks, including object recognition, tracking, and segmentation. They also have numerous real-world applications in the field of robotics, such as vision-guided grasping and manipulation of objects. To extract these features in the noisy real-world depth data, reliable 3D edge detectors are indispensable. However, currently available 3D edge detection methods are either highly parameterized or require ground truth labelling, which makes them challenging to use for practical applications. To this extent, we present a new 3D edge detection approach using unsupervised classification. Our method learns features from depth maps at three different scales using an encoder–decoder network, from which edge-specific features are extracted. These edge features are then clustered using learning to classify each point as an edge or not. The proposed method has two key benefits. First, it eliminates the need for manual fine-tuning of data-specific hyper-parameters and automatically selects threshold values for edge classification. Second, the method does not require any labelled training data, unlike many state-of-the-art methods that require supervised training with extensive hand-labelled datasets. The proposed method is evaluated on five benchmark datasets with single and multi-object scenes, and compared with four state-of-the-art edge detection methods from the literature. Results demonstrate that the proposed method achieves competitive performance, despite not using any labelled data or relying on hand-tuning of key parameters.
Classification of tropical cyclone rain patterns using convolutional autoencoder
Authors: Kim Dasol , Matyas Corene J. 
Published: January 2024

AbstractHeavy rainfall produced by tropical cyclones (TCs) frequently causes wide-spread damage. TCs have different patterns of rain depending on their development stage, geographical location, and surrounding environmental conditions. However, an objective system for classifying TC rain patterns has not yet been established. This study objectively classifies rain patterns of North Atlantic TCs using a Convolutional Autoencoder (CAE). The CAE is trained with 11,991 images of TC rain rates obtained from satellite precipitation estimates during 2000−2020. The CAE consists of an encoder which compresses the original TC rain image into low-dimensional features and a decoder which reconstructs an image from the compressed features. Then, TC rain images are classified by applying a k-means method to the compressed features from the CAE. We identified six TC rain patterns over the North Atlantic and confirmed that they exhibited unique characteristics in their spatial patterns (e.g., area, asymmetry, dispersion) and geographical locations. Furthermore, the characteristics of rain patterns in each cluster were closely related to storm intensity and surrounding environmental conditions of moisture supply, vertical wind shear, and land interaction. This classification of TC rain patterns and further investigations into their evolution and spatial variability can improve forecasts and help mitigate damage from these systems.
Starch mediates and cements densely magnetite-coating of talc, giving an efficient nano-catalyst for three-component synthesis of imidazo[1,2-c]quinazolines
Authors: Hosseinzadeh Hedyeh , Rad-Moghadam Kurosh , Mehrdad Morteza , Rouhi Somayeh 
Published: January 2024

AbstractHot-water-soluble starch (HWSS) was used as a powerful cementing material to produce nano-size conglomerates of talc and magnetite nanoparticles. Coordination of HWSS hydroxyl groups to iron atoms at surface of magnetite leads to grafting and encapsulation of its nanoparticles. The resulting nano-complex showed a higher loading capacity on talc than pristine magnetite nanoparticles. Only a minute amount of HWSS was detected in the fabricated nano-composite Talc\HWSS@Fe3O4. XPS study suggests a considerable interaction between HWSS and Fe3O4 nanoparticles, upon which some of the Fe+3 atoms on surface of Fe3O4 are reduced into Fe+2 atoms. ATR FT-IR spectra of the nano-composite revealed significant delamination of talc sheets on interaction with HWSS-coated Fe3O4 nanoparticles. The nano-composite displayed an efficient catalytic activity in the synthesis of new imidazo[1,2-c]quinazoline derivatives via Grobke–Blackburn–Bienaymé three-component reaction of 4-aminoquinazoline, arylaldehydes and isocyanide. The efficiency of the method was exemplified by synthesizing 7 new products in fairly high yields (68–83%) within short reaction times (24–30 min) using a catalytic amount of the catalyst under solvent-free condition at 120 °C. Clean and fast synthesis of the products and convenient separation of the robust nano-catalyst are the prominent advantages of the present method. The nano-catalyst was properly characterized.
Development and immunological evaluation of an mRNA-based vaccine targeting Naegleria fowleri for the treatment of primary amoebic meningoencephalitis
Authors: Naveed Muhammad , Ali Urooj , Aziz Tariq , Jabeen Khizra , Arif Muhammad Hammad , Alharbi Metab , Alasmari Abdullah F. , Albekairi Thamer H. 
Published: January 2024

AbstractMore than 95% of patients fall victim to primary amoebic meningoencephalitis (PAM), a fatal disease attacking the central nervous system. Naegleria fowleri, a brain-eating microorganism, is PAM's most well-known pathogenic ameboflagellate. Despite the use of antibiotics, the fatality rate continues to rise as no clinical trials have been conducted against this disease. To address this, we mined the UniProt database for pathogenic proteins and selected assumed epitopes to create an mRNA-based vaccine. We identified thirty B-cell and T-cell epitopes for the vaccine candidate. These epitopes, secretion boosters, subcellular trafficking structures, and linkers were used to construct the vaccine candidate. Through predictive modeling and confirmation via the Ramachandran plot (with a quality factor of 92.22), we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: 0.394, instability index: 38.99, antigenicity: 0.8). The theoretical model of immunological simulations indicated favorable responses from both innate and adaptive immune cells, with memory cells expected to remain active for up to 350 days post-vaccination, while the antigen was eliminated from the body within 24 h. Notably, strong interactions were observed between the vaccine construct and TLR-4 (− 11.9 kcal/mol) and TLR-3 (− 18.2 kcal/mol).
Molecular detection and identification of hemotropic Mycoplasma species in dogs and their ectoparasites in Iran
Authors: Beus Kimia , Goudarztalejerdi Ali , Sazmand Alireza 
Published: January 2024

AbstractHemotropic Mycoplasma species are vector-borne bacteria that attach and grow on the surface of erythrocytes in various mammals, yet reports of canine hemoplasmosis in Iran are scarce. The aim of this study was molecular detection and identification of hemoplasmas in the blood of dogs (n = 370) from five provinces of Iran and ectoparasites infesting them including Ctenocephalides canis and Pulex irritans fleas, Rhipicephalus sanguineus sensu lato ticks, Heterodoxus spiniger lice and Hippobosca longipennis keds. Hemotropic Mycoplasma spp. pathogens were detected using genus-specific conventional PCRs, and subsequently identified using species-specific PCRs for Mycoplasma haemocanis (Mhc), and Candidatus Mycoplasma haematoparvum (CMhp). Sanger sequencing was then performed to confirm the species. Correlation of infection and risk factors (geographical area, keeping condition, body condition, sex, age, ectoparasite infestation) were analyzed. In total, 210 dogs (56.7%) were tested PCR-positive for hemotropic Mycoplasma spp. Species-specific PCR and sequencing revealed infection with Mhc in 17.8%, with CMhp in 7.02% and co-infection in 31.9% of dogs. Flea infestation, poor body condition, and being older than 3-years-old correlated with hemoplasmosis. In ectoparasites, DNA of hemoplasmas were detected only in fleas i.e. Mhc in P. irritans, CMhp in P. irritans and C. canis, and co-infection in C. canis. To our knowledge, this is the first large-scale molecular epidemiology study of canine hemoplasmosis in Iran. Considering the high prevalence of canine hemoplasmosis all over the country including potentially zoonotic CMhp, effective ectoparasite control strategies, regular examination of dogs, successful chemoprophylaxis and public awareness strategies are advocated.
Surgical site infection after trochanteric and subtrochanteric fractures: a single centre retrospective analysis
Authors: Sator Thomas , Binder Harald , Payr Stephan , Pichler Lorenz , Frenzel Stephan , Hajdu Stefan , Presterl Elisabeth , Tiefenboeck Thomas Manfred 
Published: January 2024

AbstractSurgical site infection (SSI) following osteosynthesis of trochanteric or subtrochanteric fractures is a rare but serious complication with incidence rate ranging from 1 to 3%. SSIs are associated with higher mortality and increased length of hospital stay resulting in higher healthcare costs and loss of life quality. In this retrospective analysis all patients with SSI following osteosynthesis of trochanteric or subtrochanteric fractures at the Department of Trauma Surgery were identified. We included all surgical procedures performed from 1992 to 2018, using data from electronic health records and SSI-Trauma-Registry. The aim was to describe epidemiological data, as well as to identify parameters correlating with the occurrence of SSI and mortality. Of 2753 patients, 53 (1.9%) developed SSI. Longer operative time was demonstrated among patients with SSI (P = 0.008). Mortality during the first postoperative year was significantly higher in the SSI group (32.1% vs. 19.1%; P = 0.018), with detection of methicillin-sensitive (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA; HR 4.13, CI 95% 1.24–13.80; P = 0.021) or Enterococcus spp. (HR 5.58, CI 95% 1.67–18.65; P = 0.005) being independent risk factors. Male sex (HR 2.25, 95% CI 1.86–2.73; P < 0.001) and higher mean age (HR 1.05, 95% CI 1.04–1.06; P < 0.001) were found to be predictors for 1-year mortality in non-infected patients. SSI rate was low with 1.9% and longer duration of surgery was associated with infection. Patients with SSI had a higher 1-year mortality, with detection of MSSA, MRSA and enterococci significantly increasing the risk of dying. Male sex and higher age were risk factors for one-year mortality in patients without SSI.
NTRK2 expression in gastrointestinal stromal tumors with a special emphasis on the clinicopathological and prognostic impacts
Authors: Sasa Keita , Son Raku , Oguchi Akiko , Ashizawa Karin , Hasegawa Nobuhiko , Kubota Daisuke , Suehara Yoshiyuki , Takagi Tatsuya , Okubo Taketo , Akaike Keisuke , Sugimoto Kiichi , Takahashi Makoto , Sakamoto Kazuhiro , Hashimoto Takashi , Mine Shinji , Fukunaga Tetsu , Ishijima Muneaki , Hayashi Takuo , Yao Takashi , Murakawa Yasuhiro , Saito Tsuyoshi 
Published: January 2024

AbstractGastrointestinal stromal tumors (GISTs) are typically characterized by activating mutations of the KIT proto-oncogene receptor tyrosine kinase (KIT) or platelet-derived growth factor receptor alpha (PDGFRA). Recently, the neurotrophic tyrosine receptor kinase (NTRK) fusion was reported in a small subset of wild-type GIST. We examined trk IHC and NTRK gene expressions in GIST. Pan-trk immunohistochemistry (IHC) was positive in 25 (all 16 duodenal and 9 out of 16 small intestinal GISTs) of 139 cases, and all pan-trk positive cases showed diffuse and strong expression of c-kit. Interestingly, all of these cases showed only trkB but not trkA/trkC expression. Cap analysis of gene expression (CAGE) analysis identified increased number of genes whose promoters were activated in pan-trk/trkB positive GISTs. Imbalanced expression of NTRK2, which suggests the presence of NTRK2 fusion, was not observed in any of trkB positive GISTs, despite higher mRNA expression. TrkB expression was found in duodenal GISTs and more than half of small intestinal GISTs, and this subset of cases showed poor prognosis. However, there was not clear difference in clinical outcomes according to the trkB expression status in small intestinal GISTs. These findings may provide a possible hypothesis for trkB overexpression contributing to the tumorigenesis and aggressive clinical outcome in GISTs of duodenal origin.