bluuebunny/crossref_metadata_2025_split huggingface dataset:
Valorization of Brewer’s Spent Grain Using Biological Treatments and its Application in Feeds for European Seabass (Dicentrarchus labrax)
Authors: Fernandes Helena , Salgado José Manuel , Ferreira Marta , Vršanská Martina , Fernandes Nélson , Castro Carolina , Oliva-Teles Aires , Peres Helena , Belo Isabel 
Published: May 2022

Brewer’s spent grain (BSG) is the main brewery industry by-product, with potential applications in the feed and food industries due to its carbohydrate composition. In addition, the lignocellulosic nature of BSG makes it an adequate substrate for carbohydrases production. In this work, solid-state fermentation (SSF) of BSG was performed with Aspergillus ibericus, a non-mycotoxin producer fungus with a high capacity to hydrolyze the lignocellulosic matrix of the agro-industrial by-products. SSF was performed at different scales to produce a crude extract rich in cellulase and xylanase. The potential of the crude extract was tested in two different applications: -(1) - the enzymatic hydrolysis of the fermented BSG and (2) - as a supplement in aquafeeds. SSF of BSG increased the protein content from 25% to 29% (w/w), while the fiber content was reduced to 43%, and cellulose and hemicellulose contents were markedly reduced to around 15%. The scale-up of SSF from 10 g of dry BSG in flasks to 50 g or 400 g in tray-type bioreactors increased 55% and 25% production of cellulase and xylanase, up to 323 and 1073 U g−1 BSG, respectively. The optimum temperature and pH of maximal activities were found to be 55°C and pH 4.4 for xylanase and 50°C and pH 3.9 for cellulase, cellulase being more thermostable than xylanase when exposed at temperatures from 45°C to 60°C. A Box–Behnken factorial design was applied to optimize the hydrolysis of the fermented BSG by crude extract. The crude extract load was a significant factor in sugars release, highlighting the role of hydrolytic enzymes, while the load of fermented BSG, and addition of a commercial β-glucosidase were responsible for the highest phenolic compounds and antioxidant activity release. The lyophilized crude extract (12,400 and 1050 U g−1 lyophilized extract of xylanase and cellulase, respectively) was also tested as an enzyme supplement in aquafeed for European seabass (Dicentrarchus labrax) juveniles. The dietary supplementation with the crude extract significantly improved feed and protein utilization. The processing of BSG using biological treatments, such as SSF with A. ibericus, led to the production of a nutritionally enriched BSG and a crude extract with highly efficient carbohydrases capable of hydrolyzing lignocellulosic substrates, such as BSG, and with the potential to be used as feed enzymes with remarkable results in improving feed utilization of an important aquaculture fish species.
Echocardiographic Evaluation of Initial Ambrisentan Plus Phosphodiesterase Type 5 Inhibitor on Right Ventricular Pulmonary Artery Coupling in Severe Pulmonary Arterial Hypertension Patients
Authors: Lan Wei-Fang , Deng Yan , Wei Bin , Huang Kai , Dai Ping , Xie Shan-Shan , Wu Dan-dan 
Published: May 2022

Introductionambrisentan and phosphodiesterase type 5 inhibitor (PDE5i) have been approved for treating patients with pulmonary arterial hypertension (PAH). Echocardiographic right ventricular pulmonary artery coupling (RVPAC) has been shown to be a valid non-invasive and alternative measurement method to assess the predicted outcomes in PAH patients. The aim of this study was to study the effect and clinical correlates of initial ambrisentan plus PDE5i combination therapy on RVPAC in patients with severe PAH.Method and ResultsWe retrospectively studied and analyzed comprehensive clinical data, hemodynamics, and echocardiography in 27 patients with severe PAH before and after 6 months of initial combination therapy. Compared with the baseline, significant improvements in RVPAC ratios were observed, including RVFAC/PASP (0.31 ± 0.10 vs. 0.44 ± 0.15%/mmHg, p &lt; 0.001), TAPSE/PASP (0.15 ± 0.05 vs. 0.21 ± 0.06 mm/mmHg, p = 0.001), S’/PASP (0.10 ± 0.03 vs. 0.14 ± 0.05 cm/s∙mmHg, p = 0.001), and RVSV/RVESV (0.79 ± 0.22 vs. 1.02 ± 0.20, p &lt; 0.001). Functional status indices [World Health Organization functional classifications (WHO-FC) and 6 min walk distance (6MWD) and N-terminal pro B-type natriuretic peptide (NT-proBNP) levels] showed significant improvements. Right heart catheterization (RHC) evaluations for hemodynamic measurements between baseline and the 6–12 month follow-up were sPAP (96 ± 22 vs. 86 ± 24 mmHg, p = 0.002), mPAP (64 ± 18 vs. 56 ± 17 mmHg, p &lt; 0.001) and TPVR (17.3 ± 6.7 vs. 12.1 ± 5.4 WU, p = 0.001). Simultaneously, significant associations between RVPAC ratios and NT-proBNP levels and WHO-FC and 6MWD were observed.ConclusionAmbrisentan plus PDE-5i combination therapy resulted in a significant improvement in RVPAC in severe PAH. Importantly, RVPAC parameters correlated with known prognostic markers of PAH.
Perceptions of Environmental Influence and Environmental Information-Seeking Behavior Among People With Asthma and COPD
Authors: Parikh Shivani , Henderson Kelly , Gondalia Rahul , Kaye Leanne , Remmelink Esther , Thompson Alesha , Barrett Meredith 
Published: May 2022

Environmental exposures and socioeconomic status (SES) are associated with asthma and chronic obstructive pulmonary disease (COPD) morbidity and mortality. Despite efforts to reduce the impact of environmental exposures through regulation and education, knowledge gaps remain. We sought to understand how adults with asthma and COPD perceive and seek information about environmental factors, and how these responses varied by disease or socioeconomic characteristics. Participants with self-reported asthma or COPD enrolled in a digital platform for respiratory disease self-management, consisting of sensors to track medication use and a companion smartphone app, completed an electronic survey exploring perceptions of environmental factors. Using mixed-method analyses, we evaluated differences in responses by disease (asthma vs. COPD), education (≤ vs. &gt; some college), annual household income (&lt; vs. ≥ $50,000), and mean annual residential air pollutant exposure (&gt; vs. ≤80th percentile). Survey responses from 698 participants [500 asthma (72%) and 198 COPD (28%)] were analyzed. A high percentage of participants perceived that environmental factors could influence their symptoms, including: pollen (93% for asthma vs. 86% for COPD), mold (89 vs. 85%), second-hand smoke (89 vs. 83%), and air pollution (84% for both). Participants reported seeking environmental information daily from an average of three sources, preferring mobile apps and television (TV) programs. Significant differences were identified by disease.ConclusionParticipants with asthma and COPD perceive a relationship between their respiratory symptoms and their environment and regularly seek out environmental information. This information can help inform digital health development for respiratory education and self-management.
The Association Between Serum Estradiol Levels on hCG Trigger Day and Live Birth Rates in Non-PCOS Patients: A Retrospective Cohort Study
Authors: Xu Xiaoyuan , Yang Aimin , Han Yan , Wang Wei , Hao Guimin , Cui Na 
Published: May 2022

ObjectiveTo retrospectively analyze the association of serum estradiol (E2) levels on human chorionic gonadotropin (hCG) trigger day and live birth rates (LBRs) in women undergoing fresh embryo transfer and not exhibiting polycystic ovary syndrome.DesignRetrospective cohort study.MethodsAnalysis of 13,950 patients who had fresh embryo transfer between December 2013 and December 2019. The main outcome measurement was LBRs. Multivariable regression analysis was performed to investigate associations between E2 levels on the hCG trigger day and LBRs. Stratification analysis was performed to test for effect modification in subgroups. Furthermore, a two-piecewise linear regression model was established to find nonlinear relationships.ResultsMultivariable regression analysis showed a significant association between serum E2 levels on the hCG trigger day and LBRs, adjusting for covariates [relative risk (RR) 1.027, 95% confidence interval (CI) 1.007, 1.049]. Stratification analysis showed that the LBRs were positively associated (RR 1.052, 95% CI 1.004, 1.102) with every 1 ng/ml increase of serum E2 on the hCG trigger day for the subgroup with low antral follicle counts on the trigger day. Specifically, a two-piecewise linear regression model showed that there was a positive association (RR 1.188, 95% CI 1.057, 1.334) between serum E2 and LBR for every increase of 1 ng/ml E2 when the concentration of serum E2 was lower than 2.1 ng/ml. However, there was no significant association (RR 1.002, 95% CI 0.971, 1.032) between E2 levels and LBRs when the concentration of E2 was higher than the 2.1ng/ml inflection point.ConclusionsSerum E2 levels on the hCG trigger day were segmentally connected with LBRs.
Multi-Parametric Diffusion Tensor Imaging of The Optic Nerve for Detection of Dysthyroid Optic Neuropathy in Patients With Thyroid-Associated Ophthalmopathy
Authors: Liu Ping , Luo Ban , Zhai Lin-han , Wu Hong-Yu , Wang Qiu-Xia , Yuan Gang , Jiang Gui-Hua , Chen Lang , Zhang Jing 
Published: May 2022

ObjectiveTo evaluate the microstructural changes of the orbital optic nerve in thyroid-associated ophthalmopathy (TAO) patients with or without dysthyroid optic neuropathy (DON) using diffusion tensor imaging (DTI) and investigate whether DTI can be used to detect DON.Materials and Methods59 bilateral TAO patients with (n= 23) and without DON (non-DON, n= 36) who underwent pretreatment DTI were included and 118 orbits were analyzed. The clinical features of all patients were collected. DTI parameters, including mean, axial, and radial diffusivity (MD, AD, and RD, respectively) and fractional anisotropy (FA) of the intra-orbital optic nerve for each orbit were calculated and compared between the DON and non-DON groups. ROC curves were generated to evaluate the diagnostic performance of single or combined DTI parameters. Correlations between DTI parameters and ophthalmological characteristics were analyzed using correlation analysis.ResultsCompared with non-DON, the DON group showed decreased FA and increased MD, RD, and AD (P &lt; 0.01). In the differentiation of DON from non-DON, the MD was optimal individually, and the combination of the four parameters had the best diagnostic performance. There were significant correlations between the optic nerve’s four DTI metrics and the visual acuity and clinical active score (P &lt; 0.05). In addition, optic nerve FA was significantly associated with the amplitude of visual evoked potentials (P = 0.022).ConclusionsDTI is a promising technique in assessing microstructural changes of optic nerve in patients with DON, and it facilitates differentiation of DON from non-DON eyes in patients with TAO.
Prognostic Biomarker KIF18A and Its Correlations With Immune Infiltrates and Mitosis in Glioma
Authors: Tao Bing-Yan , Liu Yu-Yang , Liu Hong-Yu , Zhang Ze-Han , Guan Yun-Qian , Wang Hui , Shi Ying , Zhang Jun 
Published: May 2022

Background: Glioma is globally recognised as one of the most frequently occurring primary malignant brain tumours, making the identification of glioma biomarkers critically significant. The protein KIF18A (Kinesin Family Member 18A) is a member of the kinesin superfamily of microtubule-associated molecular motors and has been shown to participate in cell cycle and mitotic metaphase and anaphase. This is the first investigation into the expression of KIF18A and its prognostic value, potential biological functions, and effects on the immune system and mitosis in glioma patients.Methods: Gene expression and clinicopathological analysis, enrichment analysis, and immune infiltration analysis were based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. Statistical analysis was conducted in R software. Clinical samples were used to evaluate the expression of KIF18A via immunohistochemical staining. In addition, the expression level of KIF18A was validated on U87 cell line.Results: Our results highlighted that KIF18A plays a key role as an independent prognostic factor in patients with glioma. KIF18A was highly expressed in glioma tissues, and KIF18A expression was associated with age, World Health Organization grade, isocitrate dehydrogenase (IDH) status, 1p/19q codeletion, primary therapy outcome, and overall survival (OS). Enrichment analysis revealed that KIF18A is closely correlated with the cell cycle and mitosis. Single sample gene set enrichment analysis (ssGSEA) analysis revealed that KIF18A expression was related to the immune microenvironment. The increased expression of KIF18A in glioma was verified in clinical samples and U87 cell line.Conclusion: The identification of KIF18A as a new biomarker for glioma could help elucidate how changes in the glioma cell and immune microenvironment promote glioma malignancy. With further analysis, KIF18A may serve as an independent prognostic indicator for human glioma.
Association Between Endometriosis and Subsequent Risk of Sjögren’s Syndrome: A Nationwide Population-Based Cohort Study
Authors: Chao Yung-Hsiang , Liu Chin-Hsiu , Pan Yu-An , Yen Fu-Shun , Chiou Jeng-Yuan , Wei James Cheng-Chung 
Published: May 2022

ObjectiveThe relationship between endometriosis and the ensuing risk of Sjögren’s syndrome has remained unclear. This study aims to present epidemiological evidence for this connection.MethodsThis is a retrospective cohort study of endometriosis patients (ICD-9-CM 617.0-617.9 and 621.3) and matched comparison group between 2000 and 2012 in the National Taiwan Insurance Research Database. After age matching, we analyzed the association between endometriosis and Sjögren’s syndrome (ICD-9-CM 710.2). We used the Cox proportional hazard model to examine the hazard ratio of incidental Sjögren’s syndrome. Subgroup analyses on age, comorbidities, and disease duration were also performed.ResultsA total of 73,665 individuals were included in this study. We identified 14733 newly diagnosed endometriosis patients and 58,932 non-endometriosis comparison group. The adjusted hazard ratio (HR) for incidental Sjögren’s syndrome was 1.45 (95% confidence interval CI=1.27-1.65) in the endometriosis group, compared to the non-endometriosis comparison group. In subgroup analysis, the adjusted HR was 1.53 (95% CI=1.25-1.88) in the age group of 20-39 and 1.41 (95% CI =1.18-1.68) in the age of 40-64. Time-vary analysis showed that endometriosis who have a follow-up time of fewer than five years (adjusted HR=1.57, 95% CI=1.32-1.87) have a significantly highest risk of having subsequent Sjögren’s syndrome.ConclusionThis population-based cohort study indicated that having a history of endometriosis puts patients at an increased risk of getting Sjögren’s syndrome afterward, especially in the age group of 20-39 and within the first five years after the diagnosis of endometriosis. Clinicians should recognize this possible association in managing endometriosis or Sjögren’s syndrome patients.
Cardiovascular Risk in Myositis Patients Compared to the General Population: Preliminary Data From a Single-Center Cross-Sectional Study
Authors: Oreska Sabina , Storkanova Hana , Kudlicka Jaroslav , Tuka Vladimir , Mikes Ondrej , Krupickova Zdislava , Satny Martin , Chytilova Eva , Kvasnicka Jan , Spiritovic Maja , Hermankova Barbora , Cesak Petr , Rybar Marian , Pavelka Karel , Senolt Ladislav , Mann Herman , Vencovsky Jiri , Vrablik Michal , Tomcik Michal 
Published: May 2022

BackgroundIdiopathic inflammatory myopathies (IIM) are associated with systemic inflammation, limited mobility, and glucocorticoid therapy, all of which can lead to metabolism disturbances, atherogenesis, and increased cardiovascular (CV) risk. The aim of this study was to assess the CV risk in IIM patients and healthy controls (HC), and its association with disease-specific features.MethodsThirty nine patients with IIM (32 females; mean age 56; mean disease duration 4.8 years; dermatomyositis: n = 16, polymyositis: n = 7, immune-mediated necrotizing myopathy: n = 8, anti-synthetase syndrome: n = 8) and 39 age-/sex-matched HC (32 females, mean age 56) without rheumatic diseases were included. In both groups, subjects with a history of CV disease (angina pectoris, myocardial infarction, cerebrovascular, and peripheral arterial vascular events) were excluded. Muscle involvement, disease activity, and tissue damage were evaluated (Manual Muscle Test-8, Myositis Intention to Treat Activity Index, Myositis Damage Index). Comorbidities and current treatment were recorded. All participants underwent examinations of carotid intima-media thickness (CIMT), pulse wave velocity (PWV), ankle-brachial index (ABI), and body composition (by densitometry and bioelectric impedance). The risk of fatal CV events was evaluated by the Systematic COronary Risk Evaluation (SCORE, charts for the European population) and its modifications.ResultsCompared to HC, there was no significant difference in IIM patients regarding blood pressure, ABI, PWV, CIMT, and the risk of fatal CV events by SCORE or SCORE2, or subclinical atherosclerosis (CIMT, carotid plaques, ABI, and PWV). The calculated CV risk scores by SCORE, SCORE2, and SCORE multiplied by the coefficient 1.5 (mSCORE) were reclassified according to the results of carotid plaque presence and CIMT; however, none of them was demonstrated to be significantly more accurate. Other significant predictors of CV risk in IIM patients included age, disease duration and activity, systemic inflammation, lipid profile, lean body mass, and blood pressure.ConclusionsNo significant differences in CV risk factors between our IIM patients and HC were observed. However, in IIM, CV risk was associated with age, disease duration, duration of glucocorticoid therapy, lipid profile, and body composition. None of the currently available scoring tools (SCORE, SCORE2, mSCORE) used in this study seems more accurate in estimating CV risk in IIM.
Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy
Authors: Micsonai András , Moussong Éva , Murvai Nikoletta , Tantos Ágnes , Tőke Orsolya , Réfrégiers Matthieu , Wien Frank , Kardos József 
Published: May 2022

Intrinsically disordered proteins lack a stable tertiary structure and form dynamic conformational ensembles due to their characteristic physicochemical properties and amino acid composition. They are abundant in nature and responsible for a large variety of cellular functions. While numerous bioinformatics tools have been developed for in silico disorder prediction in the last decades, there is a need for experimental methods to verify the disordered state. CD spectroscopy is widely used for protein secondary structure analysis. It is usable in a wide concentration range under various buffer conditions. Even without providing high-resolution information, it is especially useful when NMR, X-ray, or other techniques are problematic or one simply needs a fast technique to verify the structure of proteins. Here, we propose an automatized binary disorder–order classification method by analyzing far-UV CD spectroscopy data. The method needs CD data at only three wavelength points, making high-throughput data collection possible. The mathematical analysis applies the k-nearest neighbor algorithm with cosine distance function, which is independent of the spectral amplitude and thus free of concentration determination errors. Moreover, the method can be used even for strong absorbing samples, such as the case of crowded environmental conditions, if the spectrum can be recorded down to the wavelength of 212 nm. We believe the classification method will be useful in identifying disorder and will also facilitate the growth of experimental data in IDP databases. The method is implemented on a webserver and freely available for academic users.
Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer’s Disease and Mild Cognitive Impairment
Authors: Dong Ningxin , Fu Changyong , Li Renren , Zhang Wei , Liu Meng , Xiao Weixin , Taylor Hugh M. , Nicholas Peter J. , Tanglay Onur , Young Isabella M. , Osipowicz Karol Z. , Sughrue Michael E. , Doyen Stephane P. , Li Yunxia 
Published: May 2022

ObjectiveAlzheimer’s Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment. We used a machine learning tool to predict performance in neuropsychological tests in AD and MCI based on functional connectivity using a whole-brain connectome, in an attempt to identify network substrates of cognitive deficits in AD.MethodsNeuropsychological tests, baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 149 MCI, and 85 AD patients; and 140 cognitively unimpaired geriatric participants. A novel machine learning tool, Hollow Tree Super (HoTS) was utilized to extract feature importance from each machine learning model to identify brain regions that were associated with deficit and absence of deficit for 11 neuropsychological tests.Results11 models attained an area under the receiver operating curve (AUC-ROC) greater than 0.65, while five models had an AUC-ROC ≥ 0.7. 20 parcels of the Human Connectome Project Multimodal Parcelation Atlas matched to poor performance in at least two neuropsychological tests, while 14 parcels were associated with good performance in at least two tests. At a network level, most parcels predictive of both presence and absence of deficit were affiliated with the Central Executive Network, Default Mode Network, and the Sensorimotor Networks. Segregating predictors by the cognitive domain associated with each test revealed areas of coherent overlap between cognitive domains, with the parcels providing possible markers to screen for cognitive impairment.ConclusionApproaches such as ours which incorporate whole-brain functional connectivity and harness feature importance in machine learning models may aid in identifying diagnostic and therapeutic targets in AD.