bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural cycles in South Pacific Gyre strength and the Southern Annular Mode
Authors: Hitt Nicholas T. , Sinclair Daniel J. , Neil Helen L. , Fallon Stewart J. , Komugabe-Dixson Aimée , Fernandez Denise , Sutton Philip J. , Hellstrom John C. 
Published: October 2022

AbstractThe South Pacific Gyre (SPG) plays a vital role in regulating Southern Hemisphere climate and ecosystems. The SPG has been intensifying since the twentieth century due to changes in large scale wind forcing. These changes result from variability in the Southern Annular Mode (SAM), causing warming along the eastern SPG which affects local ecosystems. However, our understanding of SPG variability on timescales greater than several decades is poor due to limited observations. Marine sediment cores are traditionally used to determine if recent ocean trends are anomalous, but rarely capture centennial variability in the southwest Pacific and limit our understanding of SPG variability. Here we capture centennial SPG dynamics using a novel high-resolution paleocirculation archive: radiocarbon reservoir ages (R) and local reservoir corrections (∆R) in SPG deep-sea black corals. We find black coral R and ∆R correlates with SAM reconstructions over 0–1000 cal BP and 2000–3000 cal BP. We propose this correlation indicates varying transport of well-ventilated subtropical waters resulting from SPG and SAM interactions. We reconstruct several ‘spin up’ cycles reminiscent of the recent gyre intensification, which has been attributed to anthropogenic causes. This implies gyre strength and SAM show natural co-variability on anthropogenic timescales which should factor into future climate projections.
Automation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging
Authors: Kong Hyoun-Joong , Kim Jin Youp , Moon Hye-Min , Park Hae Chan , Kim Jeong-Whun , Lim Ruth , Woo Jonghye , Fakhri Georges El , Kim Dae Woo , Kim Sungwan 
Published: October 2022

AbstractThus far, there have been no reported specific rules for systematically determining the appropriate augmented sample size to optimize model performance when conducting data augmentation. In this paper, we report on the feasibility of synthetic data augmentation using generative adversarial networks (GAN) by proposing an automation pipeline to find the optimal multiple of data augmentation to achieve the best deep learning-based diagnostic performance in a limited dataset. We used Waters’ view radiographs for patients diagnosed with chronic sinusitis to demonstrate the method developed herein. We demonstrate that our approach produces significantly better diagnostic performance parameters than models trained using conventional data augmentation. The deep learning method proposed in this study could be implemented to assist radiologists in improving their diagnosis. Researchers and industry workers could overcome the lack of training data by employing our proposed automation pipeline approach in GAN-based synthetic data augmentation. This is anticipated to provide new means to overcome the shortage of graphic data for algorithm training.
An in silico comparative transcriptome analysis identifying hub lncRNAs and mRNAs in brain metastatic small cell lung cancer (SCLC)
Authors: Mikaeili Namini Arsham , Jahangir Motahareh , Mohseni Maryam , Kolahi Ali Asghar , Hassanian-Moghaddam Hossein , Mazloumi Zeinab , Motallebi Marzieh , Sheikhpour Mojgan , Movafagh Abolfazl 
Published: October 2022

AbstractSmall cell lung cancer (SCLC) is a particularly lethal subtype of lung cancer. Metastatic lung tumours lead to most deaths from lung cancer. Predicting and preventing tumour metastasis is crucially essential for patient survivability. Hence, in the current study, we focused on a comprehensive analysis of lung cancer patients' differentially expressed genes (DEGs) on brain metastasis cell lines. DEGs are analysed through KEGG and GO databases for the most critical biological processes and pathways for enriched DEGs. Additionally, we performed protein–protein interaction (PPI), GeneMANIA, and Kaplan–Meier survival analyses on our DEGs. This article focused on mRNA and lncRNA DEGs for LC patients with brain metastasis and underlying molecular mechanisms. The expression data was gathered from the Gene Expression Omnibus database (GSE161968). We demonstrate that 30 distinct genes are up-expressed in brain metastatic SCLC patients, and 31 genes are down-expressed. All our analyses show that these genes are involved in metastatic SCLC. PPI analysis revealed two hub genes (CAT and APP). The results of this article present three lncRNAs, Including XLOC_l2_000941, LOC100507481, and XLOC_l2_007062, also notable mRNAs, have a close relation with brain metastasis in lung cancer and may have a role in the epithelial-mesenchymal transition (EMT) in tumour cells.
Utilization of ex vivo tissue model to study skin regeneration following microneedle stimuli
Authors: Liu Xue , Barresi Rebecca , Kaminer Michael , Qian Kun , Thillou Fabienne , Bataillon Michel , Liao I-Chien , Zheng Qian , Bouez Charbel 
Published: October 2022

AbstractMicroneedling is a popular skin resurfacing and rejuvenation procedure. In order to develop better adjunct products for consumers, there is a scientific need to establish greater understanding of the mechanism in which microneedling stimulates regeneration within skin. The purpose of this study is to develop a physiologically relevant ex vivo tissue model which closely mimics the actual microneedling procedure to elucidate its mechanism of action. In this study, human ex vivo skin was subjected to microneedling treatment and cultured for 6 days. Histological analysis demonstrated that the ex vivo skin was able to heal from microneedling injury throughout the culture period. Microneedling treatment stimulated proliferation and barrier renewal of the skin. The procedure also increased the levels of inflammatory cytokines and angiogenic growth factors in a dynamic and time dependent fashion. The tissue demonstrated hallmark signs of epidermal regeneration through morphological and molecular changes after the treatment. This is one of the first works to date that utilizes microneedled ex vivo skin to demonstrate its regenerative behavior. Our model recapitulates the main features of the microneedling treatment and enables the evaluation of future cosmetic active ingredients used in conjunction with microneedling.
Genesis of fecal floatation is causally linked to gut microbial colonization in mice
Authors: Aalam Syed Mohammed Musheer , Crasta Daphne Norma , Roy Pooja , Miller A. Lee , Gamb Scott I. , Johnson Stephen , Till Lisa M. , Chen Jun , Kashyap Purna , Kannan Nagarajan 
Published: October 2022

AbstractThe origin of fecal floatation phenomenon remains poorly understood. Following our serendipitous discovery of differences in buoyancy of feces from germ-free and conventional mice, we characterized microbial and physical properties of feces from germ-free and gut-colonized (conventional and conventionalized) mice. The gut-colonization associated differences were assessed in feces using DNA, bacterial-PCR, scanning electron microscopy, FACS, thermogravimetry and pycnometry. Based on the differences in buoyancy of feces, we developed levô in fimo test (LIFT) to distinguish sinking feces (sinkers) of germ-free mice from floating feces (floaters) of gut-colonized mice. By simultaneous tracking of microbiota densities and gut colonization kinetics in fecal transplanted mice, we provide first direct evidence of causal relationship between gut microbial colonization and fecal floatation. Rare discordance in LIFT and microbiota density indicated that enrichment of gasogenic gut colonizers may be necessary for fecal floatation. Finally, fecal metagenomics analysis of ‘floaters’ from conventional and syngeneic fecal transplanted mice identified colonization of > 10 gasogenic bacterial species including highly prevalent B. ovatus, an anaerobic commensal bacteria linked with flatulence and intestinal bowel diseases. The findings reported here will improve our understanding of food microbial biotransformation and gut microbial regulators of fecal floatation in human health and disease.
Long-term hospitalisations in survivors of paediatric solid tumours in France
Authors: Bejarano-Quisoboni Daniel , Pelletier-Fleury Nathalie , Allodji Rodrigue S. , Fresneau Brice , Boussac Majorie , Pacquement Hélène , Doz François , Berchery Delphine , Pluchart Claire , Bondiau Piere-Yves , Nys Julie , Jackson Angela , Demoor-Goldschmidt Charlotte , Dumas Agnes , Thomas-Teinturier Cécile , Schwartz Boris , Journy Neige , Rubino Carole , Vu-Bezin Giao , Valteau-Couanet Dominique , El-Fayech Chiraz , Dufour Christelle , Haddy Nadia , de Vathaire Florent 
Published: October 2022

AbstractThe late effects of treatments for childhood cancers may lead to severe and multiple health conditions requiring hospitalisation. We aimed to estimate the hospitalisation rate among childhood cancer survivors (CCS) in France, to compare them with the general population and to investigate the associated factors. We matched total of 5439 5-year solid CCS diagnosed before the age of 21 between 1945 and 2000 by sex, birth year and region of residence to 386,073 individuals of the French general population. After linkage with the national hospital discharge database, we estimated the relative hospitalisation rate (RHR), the absolute excess risks (AERs) and the relative bed-day ratio (RBDR) during 2006–2018. We used generalised linear models to estimate associations between hospitalisation and survivor characteristics. Overall, the RHR was 2.49 (95% confidence interval [CI] 2.46–2.52) and the RBDR was 3.49 (95% CI 3.46–3.51). We found that neoplasm-related hospitalisations had the highest AER (105.8 per 1000 person-years), followed by genitourinary system diseases (34.4 per 1000 person-years) and cardiovascular diseases (19.2 per 1000 person-years). In adjusted analysis, CCS treated with chemotherapy (risk ratio [RR] 1.62, 95% CI 1.53–1.70), radiotherapy (RR 2.11, 95% CI 1.99–2.24) or both (RR 2.59, 95% CI 2.46–2.73) had a higher risk of hospitalisation than the ones who had not received any of these treatments. CCS treated during the past decades by chemotherapy and/or radiotherapy now had a higher hospitalisation risk for all main categories of diagnosis than the general population. Prevention strategies and medical surveillance programmes may promote a long-term decrease in the hospitalisation rate among CSS.
Expression of membrane Hsp90 is a molecular signature of T cell activation
Authors: Scarneo Scott A. , Smith Aaron P. , Favret Jacob , O’Connell Robert , Pickeral Joy , Yang Kelly W. , Ferrari Guido , Loiselle David R. , Hughes Philip F. , Kulkarni Manjusha M. , Gargesha Madhusudhana , Scott Bryan , Roy Debashish , Haynes Barton F. , Kwiek Jesse J. , Haystead Timothy A. J. 
Published: October 2022

AbstractHeat shock protein 90 (Hsp90) maintains cellular proteostasis during stress and has been under investigation as a therapeutic target in cancer for over two decades. We and others have identified a membrane expressed form of Hsp90 (mHsp90) that previously appeared to be restricted to rapidly proliferating cells exhibiting a metastatic phenotype. Here, we used HS-131, a fluor-tethered mHsp90 inhibitor, to quantify the effect of T cell activation on the expression of mHsp90 in human and mouse T cells. In cell-based assays, stimulation of human T cells induced a 20-fold increase in mHsp90 expression at the plasma membrane, suggesting trafficking of mHsp90 is regulated by TCR and inflammatory mediated signaling. Following injection of HS-131 in mouse models of human rheumatoid arthritis and inflammatory bowel disease, we detected localization of the probe at sites of active disease, consistent with immune cell invasion. Moreover, despite rapid hepatobiliary clearance, HS-131 demonstrated efficacy in reducing the mean clinical score in the CIA arthritis model. Our results suggest mHsp90 expression on T cells is a molecular marker of T cell activation and potentially a therapeutic target for chronic diseases such as rheumatoid arthritis.
Sars-Cov2 world pandemic recurrent waves controlled by variants evolution and vaccination campaign
Authors: Campi Gaetano , Perali Andrea , Marcelli Augusto , Bianconi Antonio 
Published: October 2022

AbstractWhile understanding the time evolution of Covid-19 pandemic is needed to plan economics and tune sanitary policies, a quantitative information of the recurrent epidemic waves is elusive. This work describes a statistical physics study of the subsequent waves in the epidemic spreading of Covid-19 and disclose the frequency components of the epidemic waves pattern over two years in United States, United Kingdom and Japan. These countries have been taken as representative cases of different containment policies such as "Mitigation" (USA and UK) and "Zero Covid" (Japan) policies. The supercritical phases in spreading have been identified by intervals with RIC-index > 0. We have used the wavelet transform of infection and fatality waves to get the spectral analysis showing a dominant component around 130 days. Data of the world dynamic clearly indicates also the crossover to a different phase due to the enforcement of vaccination campaign. In Japan and United Kingdom, we observed the emergence in the infection waves of a long period component (~ 170 days) during vaccination campaign. These results indicate slowing down of the epidemic spreading dynamics due to the vaccination campaign. Finally, we find an intrinsic difference between infection and fatality waves pointing to a non-trivial variation of the lethality due to different gene variants.
Evaluation of machine learning algorithms for predicting direct-acting antiviral treatment failure among patients with chronic hepatitis C infection
Authors: Park Haesuk , Lo-Ciganic Wei-Hsuan , Huang James , Wu Yonghui , Henry Linda , Peter Joy , Sulkowski Mark , Nelson David R. 
Published: October 2022

AbstractDespite the availability of efficacious direct-acting antiviral (DAA) therapy, the number of people infected with hepatitis C virus (HCV) continues to rise, and HCV remains a leading cause of liver-related morbidity, liver transplantation, and mortality. We developed and validated machine learning (ML) algorithms to predict DAA treatment failure. Using the HCV-TARGET registry of adults who initiated all-oral DAA treatment, we developed elastic net (EN), random forest (RF), gradient boosting machine (GBM), and feedforward neural network (FNN) ML algorithms. Model performances were compared with multivariable logistic regression (MLR) by assessing C statistics and other prediction evaluation metrics. Among 6525 HCV-infected adults, 308 patients (4.7%) experienced DAA treatment failure. ML models performed similarly in predicting DAA treatment failure (C statistic [95% CI]: EN, 0.74 [0.69–0.79]; RF, 0.74 [0.69–0.80]; GBM, 0.72 [0.67–0.78]; FNN, 0.75 [0.70–0.80]), and all 4 outperformed MLR (C statistic [95% CI]: 0.51 [0.46–0.57]), and EN used the fewest predictors (n = 27). With Youden index, the EN had 58.4% sensitivity and 77.8% specificity, and nine patients were needed to evaluate to identify 1 DAA treatment failure. Over 60% treatment failure were classified in top three risk decile subgroups. EN-identified predictors included male sex, treatment < 8 weeks, treatment discontinuation due to adverse events, albumin level < 3.5 g/dL, total bilirubin level > 1.2 g/dL, advanced liver disease, and use of tobacco, alcohol, or vitamins. Addressing modifiable factors of DAA treatment failure may reduce the burden of retreatment. Machine learning algorithms have the potential to inform public health policies regarding curative treatment of HCV.
Facilitating time series classification by linear law-based feature space transformation
Authors: Kurbucz Marcell T. , Pósfay Péter , Jakovác Antal 
Published: October 2022

AbstractThe aim of this paper is to perform uni- and multivariate time series classification tasks with linear law-based feature space transformation (LLT). First, LLT is used to separate the training and test sets of instances. Then, it identifies the governing patterns (laws) of each input sequence in the training set by applying time-delay embedding and spectral decomposition. Finally, it uses the laws of the training set to transform the feature space of the test set. These calculation steps have a low computational cost and the potential to form a learning algorithm. For the empirical study of LLT, a widely used human activity recognition database called AReM is employed. Based on the results, LLT vastly increases the accuracy of traditional classifiers, outperforming state-of-the-art methods after the proposed feature space transformation is applied. The fastest error-free classification on the test set is achieved by combining LLT and the k-nearest neighbor (KNN) algorithm while performing fivefold cross-validation.
Association between COVID-19 stress, coping mechanisms and stress-related oral conditions among Egyptian adults: a cross-sectional study
Authors: Aly Nourhan M. , Elwan Amira H. , Elzayet Raghda M. , Hassanato Nour M. R. , Deif Mariam , Abdelaziz Wafaa E. , El Tantawi Maha 
Published: October 2022

AbstractThe present study investigated the association between COVID-19 stresses and oral conditions including gingivitis, oral hygiene, oral ulcers, and dry mouth. This was a cross-sectional study that collected data from adults in community settings in Alexandria, Egypt, between October 2021, and February 2022. Gingival condition and oral hygiene were assessed using the gingival and plaque indices. Participants were asked if they experienced oral ulcers during the past week and dry mouth during the past year. COVID-19 fears and coping were assessed using the COVID Stress Scale (CSS), and the Brief Resilience Coping Scale (BRCS), respectively. Oral health behaviors were assessed using the World Health Organization questionnaire. Regression analyses were used to assess the association between the dependent variables (clinically assessed gingival and plaque indices, reported presence of oral ulcers, and dry mouth) and explanatory variables (CSS and BRCS) after adjusting for confounders (COVID-19 status, oral health behaviors, smoking, age in years, sex, and highest educational level). The response rate was 88.8% (373/420). The mean (SD) age = 39.26 (11.45) with 74.3% females and 49.3% reporting completing high school or higher education. The mean (SD) plaque and gingival indices were 1.59 (0.66) and 1.39 (0.59), respectively. Only 20.1% reported the presence of oral ulcers and 41.6% reported xerostomia. Lower plaque score was associated with higher COVID-19 contamination fears (B = − 0.03, 95% CI − 0.05, − 0.02) and higher compulsive checking and reassurance-seeking (B = − 0.02, 95% CI − 0.03, − 0.009). Lower gingival score was associated with higher COVID-19 contamination fears (B = − 0.02, 95% CI − 0.03, − 0.002). Higher odds of reporting dry mouth were associated with greater fear of COVID-19 socioeconomic consequences (AOR = 1.05, 95% CI 1.001, 1.09), and lower coping scores (AOR = 0.93, 95% CI 0.88, 0.99). The findings suggest an association between COVID-19 specific stresses and stress-related oral conditions and shed light on the possible link between mental and oral health, emphasizing the importance of integrated planning of care services.
Measurement of the scalar curvature of high-power lasers
Authors: Toma Antonela , Postavaru Octavian 
Published: October 2022

AbstractHigh-power lasers develop high energy per unit time, and as energy curves space, we expect atomic energy levels to change. The fluorescence spectrum is a good measurement of the matrix elements involved in the Rabi oscillation and consequently allows us to determine the scalar curvature. At high Z, electrons oppose ionization even for strong intensities. Because high-power lasers address relativistic atoms, the wave functions involved must be solutions of the Dirac equation in a curved space-time. The paper can be seen as a way to check whether the Einstein’s gravitational theory is valid in the dimension of laboratory.
On the effectiveness of proton boron fusion therapy (PBFT) at cellular level
Authors: Shahmohammadi Beni Mehrdad , Islam M. Rafiqul , Kim Kyeong Min , Krstic Dragana , Nikezic Dragoslav , Yu Kwan Ngok , Watabe Hiroshi 
Published: October 2022

AbstractThe present work introduced a framework to investigate the effectiveness of proton boron fusion therapy (PBFT) at the cellular level. The framework consisted of a cell array generator program coupled with PHITS Monte Carlo package with a dedicated terminal-based code editor that was developed in this work. The framework enabled users to model large cell arrays with normal, all boron, and random boron filled cytoplasm, to investigate the underlying mechanism of PBFT. It was found that alpha particles and neutrons could be produced in absence of boron mainly because of nuclear reaction induced by proton interaction with 16O, 12C and 14N nuclei. The effectiveness of PBFT is highly dependent on the incident proton energy, source size, cell array size, buffer medium thickness layer, concentration and distribution of boron in the cell array. To quantitatively assess the effectiveness of PBFT, of the total energy deposition by alpha particle for different cases were determined. The number of alpha particle hits in cell cytoplasm and nucleus for normal and 100 ppm boron were determined. The obtained results and the developed tools would be useful for future development of PBFT to objectively determine the effectiveness of this treatment modality.
Development of the Japanese Parenting Style Scale and examination of its validity and reliability
Authors: Okubo Keisuke , Tang Yinqi , Lee Jiwon , Endo Toshihiko , Nozawa Sachiko 
Published: October 2022

AbstractParenting is an essential factor affecting child development. Therefore, several studies have focused on individual differences in parenting (i.e., parenting styles). However, there exist only a few useful scales in Japan, especially for parents who have preschool children. Therefore, a new scale for assessing parenting styles in Japan, based on the traditional theoretical framework, was developed, and examined for its validity and reliability. In Study 1, 82 original items were constructed and 1236 parents with preschool children completed these items. Next, 28 items for the Japanese Parenting Style Scale (JPSS) were selected based on factor analysis and the analyses of the graded response model. The JPSS included four factors: warmth, hostility, permissiveness, and harsh control. The results showed that each sub-scale had sufficient conceptual validity and internal consistency. In Study 2, the criterion-related validity of the JPSS was examined. A total of 1236 parents, non-participants in Study 1, completed the JPSS and other scales. The results showed sufficient criterion-related validity for the scale.
Blockchain‐enabled handover skipping for high mobility train passengers
Authors: Asad Syed Muhammad , Klaine Paulo Valente , Rais Rao Naveed Bin , Hussain Sajjad , Abbasi Qammer H. , Imran Muhammad Ali 
Published: October 2022

AbstractDue to the cell size decrements and limited sojourn time on a high speed train mobility, unnecessary handovers (HOs) occur, which can lead to higher network communication costs, and affect passengers quality of service (QoS). This paper proposes a novel blockchain‐enabled privacy preserving HO skipping framework by using train mobility dataset from the city of London. Using a complex dataset parameters, passenger traffic flows are modelled by averaging various train lines and station's footfall numbers utilising blockchain to maintain privacy. The framework stores pseudonym addresses in order to track the path of users. The proposed framework allows for a better trade‐off in terms of 2% (approx.) gain in average throughput, over 100% gain in the last‐hop signal quality, and a 50% reduction in HO costs, while also addressing the needs for resources to operate the blockchain.