bluuebunny/crossref_metadata_2025_split huggingface dataset:
The importance of routine quality control for reproducible pulmonary measurements by in vivo micro-CT
Authors: Mambrini Martina , Mecozzi Laura , Ferrini Erica , Leo Ludovica , Bernardi Davide , Grandi Andrea , Sverzellati Nicola , Ruffini Livia , Silva Mario , Stellari Franco Fabio 
Published: June 2022

AbstractMicro-computed tomography (CT) imaging provides densitometric and functional assessment of lung diseases in animal models, playing a key role either in understanding disease progression or in drug discovery studies. The generation of reliable and reproducible experimental data is strictly dependent on a system’s stability. Quality controls (QC) are essential to monitor micro-CT performance but, although QC procedures are standardized and routinely employed in clinical practice, detailed guidelines for preclinical imaging are lacking. In this work, we propose a routine QC protocol for in vivo micro-CT, based on three commercial phantoms. To investigate the impact of a detected scanner drift on image post-processing, a retrospective analysis using twenty-two healthy mice was performed and lung density histograms used to compare the area under curve (AUC), the skewness and the kurtosis before and after the drift. As expected, statistically significant differences were found for all the selected parameters [AUC 532 ± 31 vs. 420 ± 38 (p < 0.001); skewness 2.3 ± 0.1 vs. 2.5 ± 0.1 (p < 0.001) and kurtosis 4.2 ± 0.3 vs. 5.1 ± 0.5 (p < 0.001)], confirming the importance of the designed QC procedure to obtain a reliable longitudinal quantification of disease progression and drug efficacy evaluation.
Mycobacterium avium subsp. paratuberculosis exploits miRNA expression to modulate lipid metabolism and macrophage polarisation pathways during infection
Authors: Wright Kathryn , Mizzi Rachel , Plain Karren M. , Purdie Auriol C. , de Silva Kumudika 
Published: June 2022

AbstractPathogenic mycobacteria including Mycobacterium avium subsp. paratuberculosis (MAP), the causative agent of Johne’s disease, manipulate host macrophages to persist and cause disease. In mycobacterial infection, highly plastic macrophages, shift between inflammatory M1 and permissive M2 phenotypes which alter the disease outcome and allow bacteria to survive intracellularly. Here we examine the impact of MAP infection on polarised macrophages and how increased lipid availability alters macrophage phenotype and bacterial persistence. Further, we assess if host microRNA (miRNA) are sensitive to macrophage polarisation state and how MAP can drive their expression to overcome innate responses. Using in vitro MAP infection, we find that increasing lipid availability through supplementing culture media with exogenous lipid increases cellular nitric oxide production. Lipid-associated miRs -19a, -129, -24, and -24-3p are differentially expressed following macrophage polarisation and lipid supplementation and are further regulated during MAP infection. Collectively, our results highlight the importance of host lipid metabolism in MAP infection and demonstrate control of miRNA expression by MAP to favour intracellular persistence.
Meat quality in broiler chickens fed on cowpea (Vigna unguiculata [L.] Walp) seeds
Authors: Ciurescu Georgeta , Idriceanu Lavinia , Gheorghe Anca , Ropotă Mariana , Drăghici Reta 
Published: June 2022

AbstractThe study aimed to evaluate the effects of a diet containing untreated cowpea (CWP; Aura 26 variety) seeds as a protein source on quality parameters of chickens’ breast (PM;Pectoralis major) and thigh muscles (BF;Biceps femoris). A total of 240 Ross 308 broiler chickens were randomly allotted to two groups: a control group fed with soybean meal (SBM) and an experimental group fed with CWP included at 200 g/kg as a replacement of SBM. Each group consisted of six pens as replicates, with 20 chicks per pen. At 6 weeks of age, twelve birds/group were slaughtered. Compared to SBM group, the group fed CWP had higher (P < 0.0001) lightness (L*) and redness (a*) values of PM and BF muscles, the latter had also higher yellowness (b*, P < 0.0001). The collagen and protein contents were significantly higher in CWP group in both PM and BF muscles, while fat was lower (P < 0.001) only in BF muscle. The use of CWP into broilers’ diets did not negatively impact the textural properties, i.e., hardness, adhesiveness, cohesiveness, springiness, gumminess, chewiness, and resilience of PM and BF, showing similar values in both groups. Also, PM and BF muscles of birds fed CWP had significantly higher (P < 0.05) levels of C:18:3n-3 and C:20:5n-3 compared with birds fed SBM. The n-6/n-3 PUFA ratio was significantly lower in CWP group (11.72 and 7.00) compared to SBM (13.47 and 12.63) for both PM and BF muscles. These results indicate that CWP can be considered a promising protein source for broiler chickens’ feed.
Blood gas levels, cardiovascular strain and cognitive performance during surgical mask and filtering face piece application
Authors: Grimm Katharina , Niederer Daniel , Nienhaus Albert , Groneberg David A. , Engeroff Tobias 
Published: June 2022

AbstractMask induced airway resistance and carbon dioxide rebreathing is discussed to impact gas exchange and to induce discomfort and impairments in cognitive performance. N = 23 healthy humans (13 females, 10 males; 23.5 ± 2.1 years) participated in this randomized crossover trial (3 arms, 48-h washout periods). During interventions participants wore either a surgical face mask (SM), a filtering face piece (FFP2) or no mask (NM). Interventions included a 20-min siting period and 20 min steady state cycling on an ergometer at 77% of the maximal heart rate (HR). Hemodynamic data (HR, blood pressure), metabolic outcomes (pulse derived oxygen saturation, capillary carbon dioxide (pCO2), and oxygen partial pressure (pO2), lactate, pH, base excess), subjective response (ability to concentrate, arousal, perceived exertion) and cognitive performance (Stroop Test) were assessed. Compared to NM, both masks increased pCO2 (NM 31.9 ± 3.3 mmHg, SM = 35.2 ± 4.0 mmHg, FFP2 = 34.5 ± 3.8 mmHg, F = 12.670, p < 0.001) and decreased pH (NM = 7.42 ± 0.03, SM = 7.39 ± 0.03, FFP2 = 7.39 ± 0.04, F = 11.4, p < 0.001) during exercise. The FFP2 increased blood pressure during exercise (NM = 158 ± 15 mmHg, SM = 159 ± 16 mmHg, FFP2 = 162 ± 17 mmHg, F = 3.21, p = 0.050), the SM increased HR during sitting (NM = 70 ± 8 bpm, SM = 74 ± 8 bpm, FFP2 = 73 ± 8 bpm, F = 4.70, p = 0.014). No mask showed any comparative effect on other hemodynamic, metabolic, subjective, or cognitive outcomes. Mask wearing leads to slightly increased cardiovascular stress and elevated carbon dioxide levels during exercise but did not affect cognitive performance or wellbeing.
Disease relevance of rare VPS13B missense variants for neurodevelopmental Cohen syndrome
Authors: Zorn Malte , Kühnisch Jirko , Bachmann Sebastian , Seifert Wenke 
Published: June 2022

AbstractAutosomal recessive Cohen syndrome is a neurodevelopmental disorder characterized by postnatal microcephaly, intellectual disability, and a typical facial gestalt. Genetic variants in VPS13B have been found to cause Cohen syndrome, but have also been linked to autism, retinal disease, primary immunodeficiency, and short stature. While it is well established that loss-of-function mutations of VPS13B cause Cohen syndrome, the relevance of missense variants for the pathomechanism remains unexplained. Here, we investigate their pathogenic effect through a systematic re-evaluation of clinical patient information, comprehensive in silico predictions, and in vitro testing of previously published missense variants. In vitro analysis of 10 subcloned VPS13B missense variants resulted in full-length proteins after transient overexpression. 6/10 VPS13B missense variants show reduced accumulation at the Golgi complex in the steady state. The overexpression of these 6/10 VPS13B missense variants did not rescue the Golgi fragmentation after the RNAi-mediated depletion of endogenous VPS13B. These results thus validate 6/10 missense variants as likely pathogenic according to the classification of the American College of Medical Genetics through the integration of clinical, genetic, in silico, and experimental data. In summary, we state that exact variant classification should be the first step towards elucidating the pathomechanisms of genetically inherited neuronal diseases.
A high-throughput HPLC method for simultaneous quantification of pyrethroid and pyriproxyfen in long-lasting insecticide-treated nets
Authors: Walker Kyle J. , Williams Christopher T. , Oladepo Folasade O. , Lucas John , Malone David , Paine Mark J. I. , Ismail Hanafy M. 
Published: June 2022

AbstractLong-lasting insecticide-treated nets (LLINs) play a crucial role in preventing malaria transmission. LLINs should remain effective for at least three years, even after repeated washings. Currently, monitoring insecticides in LLINs is cumbersome, costly, and requires specialized equipment and hazardous solvents. Our aim was to develop a simple, high-throughput and low-resource method for measuring insecticides in LLINs. To extract insecticides, polyethylene-LLIN samples were heated at 85 °C for 45 min in a non-hazardous solvent mix containing dicyclohexylphthalate as an internal standard. The extraction solvent was reduced from 50 to 5 ml using a 0.2 g sample, 90% smaller than the recommended sample size. By optimizing HPLC chromatography, we simultaneously detected pyrethroid and pyriproxyfen insecticides with high sensitivity in LLIN's extract. The method can quantify levels ≥ 0.0015% permethrin, 0.00045% alpha-cypermethrin and 0.00025% pyriproxyfen (w/w) in polyethylene, allowing for insecticide tracking before and after the use of LLINs. This method can be used to assess LLINs with 1% pyriproxyfen (pyriproxyfen-LLIN) or 2% permethrin (Olyset® Net), 1% pyriproxyfen and 2% permethrin (Olyset® Duo), or 0.55% pyriproxyfen and 0.55% alpha-cypermethrin (Royal Gaurd®). One can run 120 samples (40 nets) simultaneously with high precision and accuracy, improving throughput and reducing labour, costs, and environmental impact.
Deep learning based analysis of microstructured materials for thermal radiation control
Authors: Sullivan Jonathan , Mirhashemi Arman , Lee Jaeho 
Published: June 2022

AbstractMicrostructured materials that can selectively control the optical properties are crucial for the development of thermal management systems in aerospace and space applications. However, due to the vast design space available for microstructures with varying material, wavelength, and temperature conditions relevant to thermal radiation, the microstructure design optimization becomes a very time-intensive process and with results for specific and limited conditions. Here, we develop a deep neural network to emulate the outputs of finite-difference time-domain simulations (FDTD). The network we show is the foundation of a machine learning based approach to microstructure design optimization for thermal radiation control. Our neural network differentiates materials using discrete inputs derived from the materials’ complex refractive index, enabling the model to build relationships between the microtexture’s geometry, wavelength, and material. Thus, material selection does not constrain our network and it is capable of accurately extrapolating optical properties for microstructures of materials not included in the training process. Our surrogate deep neural network can synthetically simulate over 1,000,000 distinct combinations of geometry, wavelength, temperature, and material in less than a minute, representing a speed increase of over 8 orders of magnitude compared to typical FDTD simulations. This speed enables us to perform sweeping thermal-optical optimizations rapidly to design advanced passive cooling or heating systems. The deep learning-based approach enables complex thermal and optical studies that would be impossible with conventional simulations and our network design can be used to effectively replace optical simulations for other microstructures.
Phonemes based detection of parkinson’s disease for telehealth applications
Authors: Pah Nemuel D. , Motin Mohammod A. , Kumar Dinesh K. 
Published: June 2022

AbstractDysarthria is an early symptom of Parkinson’s disease (PD) which has been proposed for detection and monitoring of the disease with potential for telehealth. However, with inherent differences between voices of different people, computerized analysis have not demonstrated high performance that is consistent for different datasets. The aim of this study was to improve the performance in detecting PD voices and test this with different datasets. This study has investigated the effectiveness of three groups of phoneme parameters, i.e. voice intensity variation, perturbation of glottal vibration, and apparent vocal tract length (VTL) for differentiating people with PD from healthy subjects using two public databases. The parameters were extracted from five sustained phonemes; /a/, /e/, /i/, /o/, and /u/, recorded from 50 PD patients and 50 healthy subjects of PC-GITA dataset. The features were statistically investigated, and then classified using Support Vector Machine (SVM). This was repeated on Viswanathan dataset with smartphone-based recordings of /a/, /o/, and /m/ of 24 PD and 22 age-matched healthy people. VTL parameters gave the highest difference between voices of people with PD and healthy subjects; classification accuracy with the five vowels of PC-GITA dataset was 84.3% while the accuracy for other features was between 54% and 69.2%. The accuracy for Viswanathan’s dataset was 96.0%. This study has demonstrated that VTL obtained from the recording of phonemes using smartphone can accurately identify people with PD. The analysis was fully computerized and automated, and this has the potential for telehealth diagnosis for PD.
Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies
Authors: Saednia Khadijeh , Lagree Andrew , Alera Marie A. , Fleshner Lauren , Shiner Audrey , Law Ethan , Law Brianna , Dodington David W. , Lu Fang-I , Tran William T. , Sadeghi-Naini Ali 
Published: June 2022

AbstractComplete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic factor for breast cancer (BC) patients and is correlated with improved survival. However, pCR rates are variable to standard NAC, depending on BC subtype. This study investigates quantitative digital histopathology coupled with machine learning (ML) to predict NAC response a priori. Clinicopathologic data and digitized slides of BC core needle biopsies were collected from 149 patients treated with NAC. The nuclei within the tumor regions were segmented on the histology images of biopsy samples using a weighted U-Net model. Five pathomic feature subsets were extracted from segmented digitized samples, including the morphological, intensity-based, texture, graph-based and wavelet features. Seven ML experiments were conducted with different feature sets to develop a prediction model of therapy response using a gradient boosting machine with decision trees. The models were trained and optimized using a five-fold cross validation on the training data and evaluated using an unseen independent test set. The prediction model developed with the best clinical features (tumor size, tumor grade, age, and ER, PR, HER2 status) demonstrated an area under the ROC curve (AUC) of 0.73. Various pathomic feature subsets resulted in models with AUCs in the range of 0.67 and 0.87, with the best results associated with the graph-based and wavelet features. The selected features among all subsets of the pathomic and clinicopathologic features included four wavelet and three graph-based features and no clinical features. The predictive model developed with these features outperformed the other models, with an AUC of 0.90, a sensitivity of 85% and a specificity of 82% on the independent test set. The results demonstrated the potential of quantitative digital histopathology features integrated with ML methods in predicting BC response to NAC. This study is a step forward towards precision oncology for BC patients to potentially guide future therapies.
Application of a water jet for cleaning grease and improving the surface adhesion properties of galvanized steel wire ropes
Authors: Miao Xiaojin , Zhang Chunlei , Wu Meiping , Ma Chenglong , Wang Quanlong 
Published: June 2022

AbstractTraditional cleaning processes may be banned in the near future because of the hazards they pose to the environment. In this study, a water jet was used to clean grease residues from steel wires for the first time. The EDS and SEM results of the steel wire rope surfaces and supplementary water jet impact experiments on galvanized steel plates revealed that when the pressure was lower than 50 MPa and the traverse speed was higher than 600 mm/min, the water jet caused minimal damage to the coating. When the pressure was 5 MPa, the cleaning ratio was between 45 and 60%, and the level of cleaning increased with increasing pressure. Two proposed concepts of exposure ratio and nonexposed area were applied to quantitatively analyze the theoretical upper and lower limits for grease that could be cleaned from two typical structures. The results showed that the lower and upper cleaning limits for structure 7 × 3 were 38.1% and 83.3%, while the lower and upper limits for structure 1 × 3 + 5 × 7 were 35.5% and 59.2%, respectively. This result explains why the grease content of structure 7 × 3 was lower than that of structure 1 × 3 + 5 × 7 after cleaning. In addition, the adhesion test results showed that adhesion to the two kinds of steel wire ropes after cleaning was increased by 126% and 145.71%, respectively, which means that additional processes for improving adhesion could be omitted after using a water jet for cleaning. This is an advantage that traditional cleaning processes do not offer.
Evaluation of the clinical impact of bone marrow cultures in current medical practice
Authors: Sharvit Gal , Schwartz Daniel , Heering Gabriel , Shulman Alexander , Avigdor Abraham , Rahav Galia , Toren Amos , Nagler Arnon , Canaani Jonathan 
Published: June 2022

AbstractThe clinical yield and benefit of performing bone marrow cultures for various clinical indications has been challenged and their clinical necessity remains debatable. We sought to assess the clinical yield and benefit of performing routine bone marrow cultures and determine whether various clinical, laboratory, and imaging parameters were predictive of a diagnostic bone marrow culture. This was a single center retrospective analysis of all patients who underwent a bone marrow study comprising bone marrow cultures from January 1, 2012, through March 1, 2018. Baseline clinical data were extracted from the institution's electronic medical records system. The analyzed cohort consisted of 139 patients with a median age of 46 years (range 4 months to 85 years). The most common indication for a bone marrow study was workup of a fever of unknown origin (105 patients, 76%) while investigation for infection in immunocompromised patients accounted for 22 cases (16%) and suspected tuberculosis was the reason for acquisition of bone marrow cultures in 6 patients (4%). Only 3 patients had positive bone marrow cultures, yielding in 2 patients a diagnosis of Mycobacterium avium and in one patient a microbiologically unclassifiable fungal infection. A univariate analysis revealed that mean age, hemoglobin level, platelet count, c-reactive protein levels, gender, indication for bone marrow study, yield of blood cultures, and contribution of imaging studies and bone marrow pathology results were not significantly different between patients with diagnostic and non-diagnostic bone marrow cultures. Mean white blood cell count was found to be significantly lower in patients with diagnostic bone marrow cultures (2.4 × 103/µL versus 8.7 × 103/µL; P = 0.038). We conclude that for most patients, performance of bone marrow cultures holds limited clinical value.
Reduced arterial elasticity after anabolic–androgenic steroid use in young adult males and mice
Authors: Melsom H. S. , Heiestad C. M. , Eftestøl E. , Torp M. K. , Gundersen K. , Bjørnebekk A. K. , Thorsby P. M. , Stensløkken K. O. , Hisdal J. 
Published: June 2022

AbstractHigh-doses of anabolic–androgenic steroids (AAS) is efficient for building muscle mass, but pose a risk of cardiovascular side effects. Little is known of the effect of AAS on vasculature, but previous findings suggest unfavorable alterations in vessel walls and vasoreactivity. Here, long-term effect of AAS on vascular function and morphology were examined in male weightlifters, and in a mimicking animal model. Arterial elasticity and morphology were tested with ultrasound, pulse wave velocity (PWV) and carotid intima media thickness (cIMT) in 56 current male AAS users, and 67 non-exposed weightlifting controls (WLC). Female mice were treated with testosterone for 14 days and echocardiography were applied to evaluate vascular function and morphology. Male AAS users had higher PWV (p = 0.044), reduced carotid artery compliance (p = 0.0005), and increased cIMT (p = 0.041) compared to WLC. Similar functional changes were found in the ascending aorta of mice after 7- (p = 0.043) and 14 days (p = 0.001) of testosterone treatment. This animal model can be used to map molecular mechanisms responsible for complications related to AAS misuse. Considering the age-independent stiffening of major arteries and the predictive power of an increase in PWV and cIMT, the long-term users of AAS are at increased risk of severe cardiovascular events.
A potential oral microbiome signature associated with coronary artery disease in Tunisia
Authors: Bouzid Fériel , Gtif Imen , Alfadhli Suad , Charfeddine Salma , Ghorbel Walid , Abdelhédi Rania , Benmarzoug Riadh , Abid Leila , Bouayed Abdelmoula Nouha , Elloumi Inés , Masmoudi Saber , Rebai Ahmed , Kharrat Najla 
Published: June 2022

Abstract
The coronary artery disease (CAD) is a chronic inflammatory disease involving genetic as well as environmental factors. Recent evidence suggests that the oral microbiome has a significant role in triggering atherosclerosis. The present study assessed the oral microbiome composition variation between coronary patients and healthy subjects in order to identify a potential pathogenic signature associated with CAD. We performed metagenomic profiling of salivary microbiomes by 16S ribosomal RNA (rRNA) next-generation sequencing. Oral microbiota profiling was performed for 30 individuals including 20 patients with CAD and ten healthy individuals without carotid plaques or previous stroke or myocardial infarction.
We found that oral microbial communities in patients and healthy controls are represented by similar global core oral microbiome. The predominant taxa belonged to Firmicutes (genus Streptococcus, Veillonella, Granulicatella, Selenomonas), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Rothia), Bacteroidetes (genus Prevotella, Porphyromonas), and Fusobacteria (genus Fusobacterium, Leptotrichia). More than 60% relative abundance of each sample for both CAD patients and controls is represented by three major genera including Streptococcus (24.97 and 26.33%), Veillonella (21.43 and 19.91%), and Neisseria (14.23 and 15.33%).
Using penalized regression analysis, the bacterial genus Eikenella was involved as the major discriminant genus for both status and Syntax score of CAD. We also reported a significant negative correlation between Syntax score and Eikenella abundance in coronary patients’ group (Spearman rho = −0.68, P=0.00094).
In conclusion, the abundance of Eikenella in oral coronary patient samples compared with controls could be a prominent pathological indicator for the development of CAD.