bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pilot observation using ultrasonography and vowel articulation to investigate the influence of suspected obstructive sleep apnea on upper airway
Authors: Saha Shumit , Rattansingh Anand , Martino Rosemary , Viswanathan Keerthana , Saha Anamika , Montazeri Ghahjaverestan Nasim , Yadollahi Azadeh 
Published: March 2024

AbstractFailure to employ suitable measures before administering full anesthesia to patients with obstructive sleep apnea (OSA) who are undergoing surgery may lead to developing complications after surgery. Therefore, it is very important to screen OSA before performing a surgery, which is currently done by subjective questionnaires such as STOP-Bang, Berlin scores. These questionnaires have 10–36% specificity in detecting sleep apnea, along with no information given on anatomy of upper airway, which is important for intubation. To address these challenges, we performed a pilot study to understand the utility of ultrasonography and vowel articulation in screening OSA. Our objective was to investigate the influence of OSA risk factors in vowel articulation through ultrasonography and acoustic features analysis. To accomplish this, we recruited 18 individuals with no risk of OSA and 13 individuals with high risk of OSA and asked them to utter vowels, such as /a/ (as in “Sah”), /e/ (as in “See”). An expert ultra-sonographer measured the parasagittal anterior–posterior (PAP) and transverse diameter of the upper airway. From the recorded vowel sounds, we extracted 106 features, including power, pitch, formant, and Mel frequency cepstral coefficients (MFCC). We analyzed the variation of the PAP diameters and vowel features from "See: /i/" to "Sah /a/" between control and OSA groups by two-way repeated measures ANOVA. We found that, there was a variation of upper airway diameter from “See” to “Sah” was significantly smaller in OSA group than control group (OSA: ∆12.8 ± 5.3 mm vs. control: ∆22.5 ± 3.9 mm OSA, p < 0.01). Moreover, we found several vowel features showed the exact same or opposite trend as PAP diameter variation, which led us to build a machine learning model to estimate PAP diameter from vowel features. We found a correlation coefficient of 0.75 between the estimated and measured PAP diameter after applying four estimation models and combining their output with a random forest model, which showed the feasibility of using acoustic features of vowel sounds to monitor upper airway diameter. Overall, this study has proven the concept that ultrasonography and vowel sounds analysis may be useful as an easily accessible imaging tool of upper airway.
Synthesis of biologically active Shiga toxins in cell-free systems
Authors: Ramm Franziska , Kaser Danny , König Irina , Fellendorf Juliane , Wenzel Dana , Zemella Anne , Papatheodorou Panagiotis , Barth Holger , Schmidt Herbert 
Published: March 2024

AbstractShiga toxins (Stx) produced by pathogenic bacteria can cause mild to severe diseases in humans. Thus, the analysis of such toxins is of utmost importance. As an AB5 toxin, Stx consist of a catalytic A-subunit acting as a ribosome-inactivating protein (RIP) and a B-pentamer binding domain. In this study we synthesized the subunits and holotoxins from Stx and Stx2a using different cell-free systems, namely an E. coli- and CHO-based cell-free protein synthesis (CFPS) system. The functional activity of the protein toxins was analyzed in two ways. First, activity of the A-subunits was assessed using an in vitro protein inhibition assay. StxA produced in an E. coli cell-free system showed significant RIP activity at concentrations of 0.02 nM, whereas toxins synthesized in a CHO cell-free system revealed significant activity at concentrations of 0.2 nM. Cell-free synthesized StxA2a was compared to StxA2a expressed in E. coli cells. Cell-based StxA2a had to be added at concentrations of 20 to 200 nM to yield a significant RIP activity. Furthermore, holotoxin analysis on cultured HeLa cells using an O-propargyl-puromycin assay showed significant protein translation reduction at concentrations of 10 nM and 5 nM for cell-free synthesized toxins derived from E. coli and CHO systems, respectively. Overall, these results show that Stx can be synthesized using different cell-free systems while remaining functionally active. In addition, we were able to use CFPS to assess the activity of different Stx variants which can further be used for RIPs in general.
Optimization of pacing parameters to entrain slow wave activity in the pig jejunum
Authors: Nagahawatte Nipuni D. , Avci Recep , Paskaranandavadivel Niranchan , Cheng Leo K. 
Published: March 2024

AbstractPacing has been proposed as a therapy to restore function in motility disorders associated with electrical dysrhythmias. The spatial response of bioelectrical activity in the small intestine to pacing is poorly understood due to a lack of high-resolution investigations. This study systematically varied pacing parameters to determine the optimal settings for the spatial entrainment of slow wave activity in the jejunum. An electrode array was developed to allow simultaneous pacing and high-resolution mapping of the small intestine. Pacing parameters including pulse-width (50, 100 ms), pulse-amplitude (2, 4, 8 mA) and pacing electrode orientation (antegrade, retrograde, circumferential) were systematically varied and applied to the jejunum (n = 15 pigs). Pulse-amplitudes of 4 mA (p = 0.012) and 8 mA (p = 0.002) were more effective than 2 mA in achieving spatial entrainment while pulse-widths of 50 ms and 100 ms had comparable effects (p = 0.125). A pulse-width of 100 ms and a pulse-amplitude of 4 mA were determined to be most effective for slow wave entrainment when paced in the antegrade or circumferential direction with a success rate of greater than 75%. These settings can be applied in chronic studies to evaluate the long-term efficacy of pacing, a critical aspect in determining its therapeutic potential.
Social and economic variables explain COVID-19 diffusion in European regions
Authors: Cancedda Christian , Cappellato Alessio , Maninchedda Luigi , Meacci Leonardo , Peracchi Sofia , Salerni Claudia , Baralis Elena , Giobergia Flavio , Ceri Stefano 
Published: March 2024

AbstractAt the beginning of 2020, Italy was the country with the highest number of COVID-19 cases, not only in Europe, but also in the rest of the world, and Lombardy was the most heavily hit region of Italy. The objective of this research is to understand which variables have determined the prevalence of cases in Lombardy and in other highly-affected European regions. We consider the first and second waves of the COVID-19 pandemic, using a set of 22 variables related to economy, population, healthcare and education. Regions with a high prevalence of cases are extracted by means of binary classifiers, then the most relevant variables for the classification are determined, and the robustness of the analysis is assessed. Our results show that the most meaningful features to identify high-prevalence regions include high number of hours spent in work environments, high life expectancy, and low number of people leaving from education and neither employed nor educated or trained.
Deep learning-based label-free imaging of lymphatics and aqueous veins in the eye using optical coherence tomography
Authors: Gong Peijun , Tang Xiaolan , Chen Junying , You Haijun , Wang Yuxing , Yu Paula K. , Yu Dao-Yi , Cense Barry 
Published: March 2024

AbstractWe demonstrate an adaptation of deep learning for label-free imaging of the micro-scale lymphatic vessels and aqueous veins in the eye using optical coherence tomography (OCT). The proposed deep learning-based OCT lymphangiography (DL-OCTL) method was trained, validated and tested, using OCT scans (23 volumetric scans comprising 19,736 B-scans) from 11 fresh ex vivo porcine eyes with the corresponding vessel labels generated by a conventional OCT lymphangiography (OCTL) method based on thresholding with attenuation compensation. Compared to conventional OCTL, the DL-OCTL method demonstrates comparable results for imaging lymphatics and aqueous veins in the eye, with an Intersection over Union value of 0.79 ± 0.071 (mean ± standard deviation). In addition, DL-OCTL mitigates the imaging artifacts in conventional OCTL where the OCT signal modelling was corrupted by the tissue heterogeneity, provides ~ 10 times faster processing based on a rough comparison and does not require OCT-related knowledge for correct implementation as in conventional OCTL. With these favorable features, DL-OCTL promises to improve the practicality of OCTL for label-free imaging of lymphatics and aqueous veins for preclinical and clinical imaging applications.
Narrow bandwidth, low-emittance positron beams from a laser-wakefield accelerator
Authors: Streeter M. J. V. , Colgan C. , Carderelli J. , Ma Y. , Cavanagh N. , Los E. E. , Ahmed H. , Antoine A. F. , Audet T. , Balcazar M. D. , Calvin L. , Kettle B. , Mangles S. P. D. , Najmudin Z. , Rajeev P. P. , Symes D. R. , Thomas A. G. R. , Sarri G. 
Published: March 2024

AbstractThe rapid progress that plasma wakefield accelerators are experiencing is now posing the question as to whether they could be included in the design of the next generation of high-energy electron-positron colliders. However, the typical structure of the accelerating wakefields presents challenging complications for positron acceleration. Despite seminal proof-of-principle experiments and theoretical proposals, experimental research in plasma-based acceleration of positrons is currently limited by the scarcity of positron beams suitable to seed a plasma accelerator. Here, we report on the first experimental demonstration of a laser-driven source of ultra-relativistic positrons with sufficient spectral and spatial quality to be injected in a plasma accelerator. Our results indicate, in agreement with numerical simulations, selection and transport of positron beamlets containing $$N_{e+}\ge 10^5$$

N

e
+

≥

10
5

positrons in a 5% bandwidth around 600 MeV, with femtosecond-scale duration and micron-scale normalised emittance. Particle-in-cell simulations show that positron beams of this kind can be guided and accelerated in a laser-driven plasma accelerator, with favourable scalings to further increase overall charge and energy using PW-scale lasers. The results presented here demonstrate the possibility of performing experimental studies of positron acceleration in a laser-driven wakefield accelerator.
Multiannual patterns of genetic structure and mating type ratios highlight the complex bloom dynamics of a marine planktonic diatom
Authors: Ruggiero Maria Valeria , Buffoli Marina , Wolf Klara K. E. , D’Alelio Domenico , Di Tuccio Viviana , Lombardi Ernestina , Manfellotto Francesco , Vitale Laura , Margiotta Francesca , Sarno Diana , John Uwe , Ferrante Maria Immacolata , Montresor Marina 
Published: March 2024

AbstractUnderstanding the genetic structure of populations and the processes responsible for its spatial and temporal dynamics is vital for assessing species’ adaptability and survival in changing environments. We investigate the genetic fingerprinting of blooming populations of the marine diatom Pseudo-nitzschia multistriata in the Gulf of Naples (Mediterranean Sea) from 2008 to 2020. Strains were genotyped using microsatellite fingerprinting and natural samples were also analysed with Microsatellite Pool-seq Barcoding based on Illumina sequencing of microsatellite loci. Both approaches revealed a clonal expansion event in 2013 and a more stable genetic structure during 2017–2020 compared to previous years. The identification of a mating type (MT) determination gene allowed to assign MT to strains isolated over the years. MTs were generally at equilibrium with two notable exceptions, including the clonal bloom of 2013. The populations exhibited linkage equilibrium in most blooms, indicating that sexual reproduction leads to genetic homogenization. Our findings show that P. multistriata blooms exhibit a dynamic genetic and demographic composition over time, most probably determined by deeper-layer cell inocula. Occasional clonal expansions and MT imbalances can potentially affect the persistence and ecological success of planktonic diatoms.
Machine learning insights into thrombo-ischemic risks and bleeding events through platelet lysophospholipids and acylcarnitine species
Authors: Harm Tobias , Fu Xiaoqing , Frey Moritz , Dittrich Kristina , Brun Adrian , Castor Tatsiana , Borst Oliver , Müller Karin Anne Lydia , Geisler Tobias , Rath Dominik , Lämmerhofer Michael , Gawaz Meinrad Paul 
Published: March 2024

AbstractCoronary artery disease (CAD) often leads to adverse events resulting in significant disease burdens. Underlying risk factors often remain inapparent prior to disease incidence and the cardiovascular (CV) risk is not exclusively explained by traditional risk factors. Platelets inherently promote atheroprogression and enhanced platelet functions and distinct platelet lipid species are associated with disease severity in patients with CAD. Lipidomics data were acquired using mass spectrometry and processed alongside clinical data applying machine learning to model estimates of an increased CV risk in a consecutive CAD cohort (n = 595). By training machine learning models on CV risk measurements, stratification of CAD patients resulted in a phenotyping of risk groups. We found that distinct platelet lipids are associated with an increased CV or bleeding risk and independently predict adverse events. Notably, the addition of platelet lipids to conventional risk factors resulted in an increased diagnostic accuracy of patients with adverse CV events. Thus, patients with aberrant platelet lipid signatures and platelet functions are at elevated risk to develop adverse CV events. Machine learning combining platelet lipidome data and common clinical parameters demonstrated an increased diagnostic value in patients with CAD and might improve early risk discrimination and classification for CV events.
Exploring the impact of stress on the electronic structure and optical properties of graphdiyne nanoribbons for advanced optoelectronic applications
Authors: Liu Qiaohan , Feng Naixing , Zou Yi , Fan Chuanqiang , Wang Jingang 
Published: March 2024

AbstractGraphdiyne (GDY), a two-dimensional carbon material with sp- and sp2-hybridization, is recognized for its unique electronic properties and well-dispersed porosity. Its versatility has led to its use in a variety of applications. The precise control of this material's properties is paramount for its effective utilization in nano-optical devices. One effective method of regulation, which circumvents the need for additional disturbances, involves the application of external stress. This technique provides a direct means of eliciting changes in the electronic characteristics of the material. For instance, when subjected to uniaxial stress, electron transfer occurs at the triple bond. This results in an armchair-edged graphdiyne nanoribbon (A(3)-GDYNR) with a planar width of 2.07 nm, which exhibits a subtle plasmon effect at 500 nm. Conversely, a zigzag-edged graphdiyne nanoribbon (Z(3)-GDYNR) with a planar width of 2.86 nm demonstrates a pronounced plasmon effect within the 250–1200 nm range. This finding suggests that the zigzag nanoribbon surpasses the armchair nanoribbon in terms of its plasmon effect. First principles calculations and ab initio molecular dynamics further confirmed that under applied stress Z(3)-GDYNR exhibits less deformation than A(3)-GDYNR, indicating superior stability. This work provides the necessary theoretical basis for understanding graphene nanoribbons (GDYNRs).
Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules
Authors: Murgas Kevin A. , Elkin Rena , Riaz Nadeem , Saucan Emil , Deasy Joseph O. , Tannenbaum Allen R. 
Published: March 2024

AbstractMelanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities. Analysis identified six distinct gene modules corresponding to sets of genes interacting in response to immunotherapy. One module alone, overlapping with the nuclear factor kappa-B pathway (NFkB), was associated with improved patient survival and a positive clinical response to immunotherapy. This analysis demonstrates the usefulness of dynamic Ollivier-Ricci curvature as a general method for identifying information-sharing gene modules in cancer.
Obstetric infections and clinical characteristics of maternal sepsis: a hospital-based retrospective cohort study
Authors: Kvalvik Sedina Atic , Zakariassen Sofie Branæs , Overrein Sofie , Rasmussen Svein , Skrede Steinar , Baghestan Elham 
Published: March 2024

AbstractSepsis is responsible for 50% of intrahospital maternal deaths worldwide. Incidence is increasing in both low and middle-, and high-income countries. There is little data on incidence and clinical outcomes of obstetric infections including maternal sepsis in the Nordic countries. The aims of this study are to give estimates of the occurrence of obstetric infections and maternal sepsis in a Norwegian hospital cohort, assess the quality of management of maternal sepsis cases, and evaluate the usefulness of diagnostic codes to identify maternal sepsis retrospectively. We conducted a retrospective cohort study of pregnant, labouring, post-abortion, and postpartum women. We assessed the accuracy of the diagnostic code most frequently applied for maternal sepsis, O85. We found 7.8% (95% confidence interval 7.1–8.5) infection amongst pregnant, labouring, and postpartum women. The incidence of maternal sepsis was 0.3% (95% confidence interval 0.2–0.5), and the majority of sepsis cases were recorded in the postpartum period. Two thirds of women were given broad-spectrum antibiotics at the time sepsis was diagnosed, but only 15.4% of women with puerperal sepsis were given antimicrobials in accordance with national guidelines. When used retrospectively, obstetric infection codes are insufficient in identifying both maternal and puerperal sepsis, with only 20.3% positive predictive value for both conditions. In conclusion, obstetric infections contribute significantly to maternal morbidity in Norway’s second largest maternity hospital. This study provides incidences of maternal infections for hospitalised patients in temporal relation to pregnancy, labour, abortion and the postpartum period, knowledge which is valuable for planning of health care services and allocation of resources. In addition, the study highlights areas where improvement is needed in clinical handling of maternal sepsis. There is need for studies on the management quality and use of correct diagnostic codes in this patient category.
Optimal duration and timing of basic-life-support-only intervention for patients with out-of-hospital cardiac arrest
Authors: Takei Yutaka , Toyama Gen , Takahashi Tsukasa , Omatsu Kentaro 
Published: March 2024

AbstractTo elucidate the relationship between the interval from cardiopulmonary resuscitation initiation to return of spontaneous circulation (ROSC) and neurologically favourable 1-month survival in order to determine the appropriate duration of basic life support (BLS) without advanced interventions. This population-based cohort study included patients aged ≥ 18 years with 9132 out-of-hospital cardiac arrest of presumed cardiac origin who were bystander-witnessed and had achieved ROSC between 2018 and 2020. Patients were classified into two groups based on the resuscitation methods as the “BLS-only” and the “BLS with administered epinephrine (BLS-AE)” groups. Receiver operating characteristic (ROC) curve analysis indicated that administering BLS for 9 min yielded the best neurologically outcome for patients with a shockable rhythm [sensitivity, 0.42; specificity, 0.27; area under the ROC curve (AUC), 0.60] in the BLS-only group. Contrastingly, for patients with a non-shockable rhythm, performing BLS for 6 min yielded the best neurologically outcome (sensitivity, 0.65; specificity, 0.43; AUC, 0.63). After propensity score matching, multivariate analysis revealed that BLS-only resuscitation [6.44 (5.34–7.77)] was associated with neurologically favourable 1-month survival. This retrospective study revealed that BLS-only intervention had a significant impact in the initial minutes following CPR initiation. Nevertheless, its effectiveness markedly declined thereafter. The optimal duration for effective BLS-only intervention varied depending on the patient's initial rhythm. Consequently, advanced interventions should be administered within the first few minutes to counteract the diminishing effectiveness of BLS-only intervention.
Predicting early Alzheimer’s with blood biomarkers and clinical features
Authors: AlMansoori Muaath Ebrahim , Jemimah Sherlyn , Abuhantash Ferial , AlShehhi Aamna 
Published: March 2024

AbstractAlzheimer’s disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.