bluuebunny/crossref_metadata_2025_split huggingface dataset:
A longitudinal study on associations of moderate-to-vigorous physical activity with plasma monounsaturated fatty acids in pregnancy
Authors: Xia Tong , Chen Liwei , Fei Zhe , Liu Xinyue , Dai Jin , Hinkle Stefanie N. , Zhu Yeyi , Wu Jing , Weir Natalie L. , Tsai Michael Y. , Zhang Cuilin 
Published: October 2022

BackgroundPhysical activity (PA) during pregnancy influences women and offspring’s health via fatty acids metabolism. However, studies on associations of PA with plasma monounsaturated fatty acids (MUFAs) across pregnancy are sparse. Thus, our study aimed to examine associations of PA with individual plasma phospholipid MUFAs throughout pregnancy in a prospective and longitudinal study in the United States (US).Materials and methodsThe study included 318 pregnant women from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singletons cohort. PA was measured four times: PA reported at 10–14 gestational weeks (GWs) representing PA in the past year, and at 15–26 GWs, 23–31 GWs, and 33–39 GWs representing PA since the last visit. Plasma phospholipid MUFAs were measured at the same four visits as the measurement of PA. Associations between moderate-to-vigorous PA (MVPA) and the total MUFAs and seven individual plasma phospholipid MUFAs (i.e., palmitoleic acid, 18:1n6-9 trans, 18:1n6c, cis-vaccenic acid, oleic acid, eicosenoic acid, and nervonic acid) were assessed at each visit using multivariable linear regression models adjusting for confounders.ResultsMVPA (hours/week) reported at 15–26 GWs representing MVPA since the last visit was positively associated with total MUFAs (% of total fatty acids) [adjusted β*102 (standard error (SE)*102) = 10.41 (3.19), P = 0.001] at 15–26 GWs. For individual MUFAs, MVPA reported at 15–26 GWs representing MVPA since the last visit was positively associated with oleic acid [adjusted β*102 (SE*102) = 8.56 (2.65), P = 0.001] and eicosenoic acid [adjusted β*102 (SE*102) = 0.55 (0.20), P = 0.01] at 15–26 GWs. MVPA reported at 23–31 GWs representing MVPA since the last visit was positively associated with palmitoleic acid [adjusted β*102 (SE*102) = 2.24 (0.64), P = 0.001] at 23–31 GWs. MVPA reported at 10–14 GWs and 33–39 GWs was not associated with total or individual MUFAs.ConclusionWe found novel positive associations of MVPA with individual MUFAs, such as oleic acid, eicosenoic acid, and palmitoleic acid, during middle-to-late pregnancy. These findings suggest that MVPA represents a potentially modifiable factor for plasma individual MUFA levels during pregnancy.
Circulating syndecan-1 and glypican-4 predict 12-month survival in metastatic colorectal cancer patients
Authors: Muendlein Axel , Severgnini Luciano , Decker Thomas , Heinzle Christine , Leiherer Andreas , Geiger Kathrin , Drexel Heinz , Winder Thomas , Reimann Patrick , Mayer Frank , Nonnenbroich Christoph , Dechow Tobias 
Published: October 2022

Cell surface syndecans and glypicans play important roles in the development and prognosis of colorectal cancer (CRC). Their soluble forms from proteoglycan shedding can be detected in blood and have been proposed as new prognostic biomarkers in several cancer entities. However, studies on circulating syndecan-1 (SDC1) and glypican-4 (GPC4) in CRC are limited. We, therefore, evaluated the impact of plasma SDC1 and GPC4 on the prognosis of metastatic (m)CRC patients. The present study included 93 patients with mCRC. The endpoints were progression-free survival (PFS) and overall survival (OS) at 12 months. SDC1 and GPC4 levels were measured in plasma using enzyme-linked immunosorbent assays. Plasma levels of SDC1 and GPC4 were significantly correlated. Significant correlations of these two markers were also found with carcinoembryonic antigen (CEA). Kaplan-Meier curve analyses indicated that PFS and OS probabilities significantly decreased with increasing levels of SDC1 and GPC4, respectively. Multivariable Cox regression analyses showed that both markers were significantly associated with PFS and OS independently from clinicopathological characteristics including CEA. Respective adjusted hazard ratios (HR) together with corresponding 95% confidence intervals for one standard deviation change of SDC1 were 1.32 [1.02-1.84] for PFS and 1.48 [1.01-2.15] for OS. Adjusted HRs [95% confidence intervals] of GPC4 were 1.42 [1.07-1.89] for PFS and 2.40 [1.51-3.81] for OS. Results from area under the receiver operating characteristic curve analyses suggest that GPC4 and SDC1 add additional prognostic values to CEA for OS. In conclusion, we showed significant associations of circulating SDC1 and GPC4 with poor survival of mCRC patients.
Prediction of axillary lymph node pathological complete response to neoadjuvant therapy using nomogram and machine learning methods
Authors: Zhou Tianyang , Yang Mengting , Wang Mijia , Han Linlin , Chen Hong , Wu Nan , Wang Shan , Wang Xinyi , Zhang Yuting , Cui Di , Jin Feng , Qin Pan , Wang Jia 
Published: October 2022

PurposeTo determine the feasibility of predicting the rate of an axillary lymph node pathological complete response (apCR) using nomogram and machine learning methods.MethodsA total of 247 patients with early breast cancer (eBC), who underwent neoadjuvant therapy (NAT) were included retrospectively. We compared pre- and post-NAT ultrasound information and calculated the maximum diameter change of the primary lesion (MDCPL): [(pre-NAT maximum diameter of primary lesion – post-NAT maximum diameter of preoperative primary lesion)/pre-NAT maximum diameter of primary lesion] and described the lymph node score (LNS) (1): unclear border (2), irregular morphology (3), absence of hilum (4), visible vascularity (5), cortical thickness, and (6) aspect ratio &lt;2. Each description counted as 1 point. Logistic regression analyses were used to assess apCR independent predictors to create nomogram. The area under the curve (AUC) of the receiver operating characteristic curve as well as calibration curves were employed to assess the nomogram’s performance. In machine learning, data were trained and validated by random forest (RF) following Pycharm software and five-fold cross-validation analysis.ResultsThe mean age of enrolled patients was 50.4 ± 10.2 years. MDCPL (odds ratio [OR], 1.013; 95% confidence interval [CI], 1.002–1.024; p=0.018), LNS changes (pre-NAT LNS – post-NAT LNS; OR, 2.790; 95% CI, 1.190–6.544; p=0.018), N stage (OR, 0.496; 95% CI, 0.269–0.915; p=0.025), and HER2 status (OR, 2.244; 95% CI, 1.147–4.392; p=0.018) were independent predictors of apCR. The AUCs of the nomogram were 0.74 (95% CI, 0.68–0.81) and 0.76 (95% CI, 0.63–0.90) for training and validation sets, respectively. In RF model, the maximum diameter of the primary lesion, axillary lymph node, and LNS in each cycle, estrogen receptor status, progesterone receptor status, HER2, Ki67, and T and N stages were included in the training set. The final validation set had an AUC value of 0.85 (95% CI, 0.74–0.87).ConclusionBoth nomogram and machine learning methods can predict apCR well. Nomogram is simple and practical, and shows high operability. Machine learning makes better use of a patient’s clinicopathological information. These prediction models can assist surgeons in deciding on a reasonable strategy for axillary surgery.
Gratitude among advanced cancer patients and their caregivers: The role of early palliative care
Authors: Borelli Eleonora , Bigi Sarah , Potenza Leonardo , Gilioli Fabio , Artioli Fabrizio , Porzio Giampiero , Porro Carlo Adolfo , Efficace Fabio , Bruera Eduardo , Luppi Mario , Bandieri Elena 
Published: October 2022

ObjectiveA cancer diagnosis represents a unique trauma, given its life-threatening, multidimensional, and uncertain nature. Gratitude is a construct representing the emotional state that arises when individuals recognize that a benefit has been received as a result of someone else’s action or a spiritual entity’s intervention. Based on the positive psychological wellbeing, gratitude has been associated with improved health outcomes even in the disease setting. Thus, the models of care that foster gratitude should be adopted in the clinical context. This study aims to explore whether and how gratitude may originate in patients with advanced cancer and their caregivers undergoing early palliative care (EPC).MethodsWe analyzed 251 reports from 133 patients and 118 caregivers describing their clinical experience in two EPC units. The sources of gratitude were identified and ranked based on their frequencies. Words expressing gratitude and words referring to communication and spirituality were collected by means of the Linguistic Inquiry and Word Count software and correlated.ResultsIn total, 123 (92.5%) of 133 patients’ and 97 (82.2%) of 118 caregivers’ reports, respectively, included explicit or implicit expressions of gratitude. Gratitude was associated specifically with successful physical symptom management, emotional support, improved attitude toward death, better information, humanity, and the familiar environment. The use of words of gratitude in patients’ reports was positively correlated with the use of words referring to communication (r = .215, p = .026) and spirituality (r = .612, p &lt;.001).ConclusionOur results suggest that interventions within the EPC model based on doctor–patient–caregiver communication may allow patients and caregivers to experience a feeling of gratitude, and this may represent a resource to be exploited to improve their physical and psychosocial wellbeing.
Applying machine learning to the pharmacokinetic modeling of cyclosporine in adult renal transplant recipients: a multi-method comparison
Authors: Mao Junjun , Chen Yuhao , Xu Luyang , Chen Weihuang , Chen Biwen , Fang Zhuo , Qin Weiwei , Zhong Mingkang 
Published: October 2022

Objective: The aim of this study was to identify the important factors affecting cyclosporine (CsA) blood concentration and estimate CsA concentration using seven different machine learning (ML) algorithms. We also assessed the predictability of established ML models and previously built population pharmacokinetic (popPK) model. Finally, the most suitable ML model and popPK model to guide precision dosing were determined.Methods: In total, 3,407 whole-blood trough and peak concentrations of CsA were obtained from 183 patients who underwent initial renal transplantation. These samples were divided into model-building and evaluation sets. The model-building set was analyzed using seven different ML algorithms. The effects of potential covariates were evaluated using the least absolute shrinkage and selection operator algorithms. A separate evaluation set was used to assess the ability of all models to predict CsA blood concentration. R squared (R2) scores, median prediction error (MDPE), median absolute prediction error (MAPE), and the percentages of PE within 20% (F20) and 30% (F30) were calculated to assess the predictive performance of these models. In addition, previously built popPK model was included for comparison.Results: Sixteen variables were selected as important covariates. Among ML models, the predictive performance of nonlinear-based ML models was superior to that of linear regression (MDPE: 3.27%, MAPE: 34.21%, F20: 30.63%, F30: 45.03%, R2 score: 0.68). The ML model built with the artificial neural network algorithm was considered the most suitable (MDPE: −0.039%, MAPE: 25.60%, F20: 39.35%, F30: 56.46%, R2 score: 0.75). Its performance was superior to that of the previously built popPK model (MDPE: 5.26%, MAPE: 29.22%, F20: 33.94%, F30: 51.22%, R2 score: 0.68). Furthermore, the application of the most suitable model and the popPK model in clinic showed that most dose regimen recommendations were reasonable.Conclusion: The performance of these ML models indicate that a nonlinear relationship for covariates may help to improve model predictability. These results might facilitate the application of ML models in clinic, especially for patients with unstable status or during initial dose optimization.
Total cannabidiol (CBD) concentrations and yields from traditional extraction methods: Percolation vs. maceration
Authors: Wilson Jason , Simpson Travis , Spelman Kevin 
Published: October 2022

Medicinal plants have been valued for many generations due to their biosynthetic advantages generating pharmacologically active molecules. This is especially the case when it comes to cannabinoids from Cannabis. In these experiments we mimicked typical herbal home extractions and measured the yield of total decarboxylated CBD (“total CBD”) from percolations and macerations done at the common duration of 2 weeks in duplicate independent extractions. Analysis was performed by GC-FID on triplicate samples from each extraction. Results demonstrated a significant extraction superiority of percolation over maceration. Percolation extracted 80.1% of the total CBD in the hemp biomass as compared to the 2-week time point at 63.5% recovery. Our results demonstrate a significant increase in total CBD yield from percolation, as compared to maceration. Highest solvent recovery was also through percolation, but overall solvent recovery was fairly consistent with the maceration method, after pressing. Under these conditions of extracting lipophilic cannabidiol in 95% ethanol, these data demonstrate that percolation is significantly superior to maceration in total CBD yield. These observations will likely apply to the extraction of lipophilic constituents from other herbs and botanical medicines.
Aqueous extract of Parkia biglobosa (Jacq.) R. Br. (Fabaceae) exerts antiepileptogenic, anti-amnesic, and anxiolytic-like effects in mice via mechanisms involving antioxidant and anti-inflammatory pathways
Authors: Kandeda Antoine Kavaye , Menvouta Soline , Mabou Symphorien Talom , Kouamouo Jonas , Dimo Théophile 
Published: October 2022

Parkia biglobosa (Jacq.) R. Br. (Fabaceae) is a widely distributed tree, used in traditional medicine to treat amebiasis, hookworm infection, ascariasis, asthma, sterility, dental pain, headaches, cardiac disorders, and epilepsy. To date, no study on the effect of an aqueous extract of P. biglobosa on epileptogenesis and associated neuropsychiatric disorders has been undertaken. Therefore, this study aimed to investigate antiepileptogenic-, antiamnesic-, and anxiolytic-like effects of an aqueous extract of P. biglobosa using pentylenetetrazole (PTZ)-induced kindling in mice. Animals were divided into six groups of eight mice each. Thus, a PTZ group received distilled water (10 ml/kg, per os), a positive control group received sodium valproate (300 mg/kg, p.o.), and three test groups received the aqueous extract of P. biglobosa (80, 160, and 320 mg/kg, p.o.).In addition, a control group of eight mice receiving distilled water (10 ml/kg, p.o.) was formed. The treatments were administered to mice, 60 min before administration of PTZ (20 mg/kg, i.p.). These co-administrations were performed once daily, for 22 days. The number and duration of seizures (stages 1, 2, 3, and 4 of seizures) exhibited by each mouse were assessed for 30 min during the treatment period. Twenty-four hours following the last administration of the treatments and PTZ, novel object recognition and T-maze tests were performed to assess working memory impairment in mice, while the open field test was performed to assess anxiety-like behavior. After these tests, the animals were sacrificed, and the hippocampi were collected for biochemical and histological analysis. During the period of PTZ-kindling, the extract at all doses completely (p &lt; 0.001) protected all mice against stages 3 and 4 of seizures when compared to sodium valproate, a standard antiepileptic drug. The extract also significantly (p &lt; 0.001) attenuated working memory impairment and anxiety-like behavior. In post-mortem brain analyses, the extract significantly (p &lt; 0.001) increased γ-aminobutyric acid (GABA) level and reduced oxidative stress and inflammation. Histological analysis showed that the aqueous extract attenuated neuronal degeneration/necrosis in the hippocampus. These results suggest that the extract is endowed with antiepileptogenic-, anti-amnesic-, and anxiolytic-like effects. These effects seem to be mediated in part by GABAergic, antioxidant, and anti-inflammatory mechanisms. These results suggest the merit of further studies to isolate the bioactive molecules responsible for these potentially therapeutically relevant effects of the extract.
Emissivity evaluation of human enamel and dentin
Authors: Lancaster P. E. , Carmichael F. A. , Clerehugh V. , Brettle D. S. 
Published: October 2022

Background: Human enamel and dentin temperatures have been assessed with non-contact infrared imaging devices for safety and diagnostic capacity and require an emissivity parameter to enable absolute temperature measurements. Emissivity is a ratio of thermal energy emitted from an object of interest, compared to a perfect emitter at a given temperature and wavelength, being dependent on tissue composition, structure, and surface texture. Evaluating the emissivity of human enamel and dentin is varied in the literature and warrants review. The primary aim of this study was to evaluate the emissivity of the external and internal surface of human enamel and dentin, free from acquired or developmental defects, against a known reference point. The secondary aim was to assess the emissivity value of natural caries in enamel and dentin.Method: Fourteen whole human molar teeth were paired within a thermally stable chamber at 30°C. Two additional teeth (one sound and one with natural occlusal caries–ICDAS caries score 4 and radiographic score RB4) were sliced and prepared as 1-mm-thick slices and placed on a hot plate at 30°C within the chamber. A 3M Scotch Super 33 + Black Vinyl Electrical Tape was used for the known emissivity reference-point of 0.96. All samples were allowed to reach thermal equilibrium, and a FLIR SC305 infrared camera recorded the warming sequence. Emissivity values were calculated using the Tape reference point and thermal camera software.Results: The external enamel surface mean emissivity value was 0.96 (SD 0.01, 95% CI 0.96–0.97), whereas the internal enamel surface value was 0.97 (SD 0.01, 95% CI 0.96–0.98). The internal crown-dentin mean emissivity value was 0.94 (SD 0.02, 95% CI 0.92–0.95), whereas the internal root-dentin value was 0.93 (SD 0.02, 95% CI 0.91–0.94) and the surface root-dentin had a value of 0.84 (SD 0.04, 95% CI 0.77–0.91). The mean emissivity value of the internal enamel surface with caries was 0.82 (SD 0.05, 95% CI 0.38–1.25), and the value of the internal crown-dentin with caries was 0.73 (SD 0.08, 95% CI 0.54–0.92).Conclusion: The emissivity values of sound enamel, both internal and external, were similar and higher than those of all sound dentin types in this study. Sound dentin emissivity values diminished from the crown to the root and root surface. The lowest emissivity values were recorded in caries lesions of both tissues. This methodology can improve emissivity acquisition for comparison of absolute temperatures between studies which evaluate thermal safety concerns during dental procedures and may offer a caries diagnostic aid.
ROS generated from biotic stress: Effects on plants and alleviation by endophytic microbes
Authors: Sahu Pramod Kumar , Jayalakshmi K. , Tilgam Jyotsana , Gupta Amrita , Nagaraju Yalavarthi , Kumar Adarsh , Hamid Saima , Singh Harsh Vardhan , Minkina Tatiana , Rajput Vishnu D. , Rajawat Mahendra Vikram Singh 
Published: October 2022

Aerobic living is thought to generate reactive oxygen species (ROS), which are an inevitable chemical component. They are produced exclusively in cellular compartments in aerobic metabolism involving significant energy transfer and are regarded as by-products. ROS have a significant role in plant response to pathogenic stress, but the pattern varies between necrotrophs and biotrophs. A fine-tuned systemic induction system is involved in ROS-mediated disease development in plants. In regulated concentrations, ROS act as a signaling molecule and activate different pathways to suppress the pathogens. However, an excess of these ROS is deleterious to the plant system. Along with altering cell structure, ROS cause a variety of physiological reactions in plants that lower plant yield. ROS also degrade proteins, enzymes, nucleic acids, and other substances. Plants have their own mechanisms to overcome excess ROS and maintain homeostasis. Microbes, especially endophytes, have been reported to maintain ROS homeostasis in both biotic and abiotic stresses by multiple mechanisms. Endophytes themselves produce antioxidant compounds and also induce host plant machinery to supplement ROS scavenging. The structured reviews on how endophytes play a role in ROS homeostasis under biotic stress were very meager, so an attempt was made to compile the recent developments in ROS homeostasis using endophytes. This review deals with ROS production, mechanisms involved in ROS signaling, host plant mechanisms in alleviating oxidative stress, and the roles of endophytes in maintaining ROS homeostasis under biotic stress.
Image Processing and Measurement of the Bubble Properties in a Bubbling Fluidized Bed Reactor
Authors: Jaiswal Rajan , Moldestad Britt. M. E. , Eikeland Marianne S. , Nielsen Henrik K. , Thapa Rajan Kumar 
Published: October 2022

The efficiency of a fluidized bed reactor depends on the bed fluid dynamic behavior, which is significantly influenced by the bubble properties. This work investigates the bubble properties of a bubbling fluidized bed reactor using computational particle fluid dynamic (CPFD) simulations and electrical capacitance tomography (ECT) measurements. The two-dimensional images (along the reactor horizontal and vertical planes) of the fluidized bed are obtained from the CPFD simulations at different operating conditions. The CPFD model was developed in a commercial CPFD software Barracuda Virtual Reactor 20.0.1. The bubble behavior and bed fluidization behavior are characterized form the bubble properties: average bubble diameter, bubble rise velocity, and bubble frequency. The bubble properties were determined by processing the extracted images with script developed in MATLAB. The CPFD simulation results are compared with experimental data (obtained from the ECT sensors) and correlations in the literature. The results from the CPFD model and experimental measurement depicted that the average bubble diameter increased with an increase in superficial gas velocities up to 4.2 Umf and decreased with a further increase in gas velocities due to the onset of large bubbles (potential slugging regime). The bubble rise velocity increased as it moved from the lower region to the bed surface. The Fourier transform of the transient solid volume fraction illustrated that multiple bubbles pass the plane with varying amplitude and frequency in the range of 1–6 Hz. Further, the bubble frequency increased with an increase in superficial gas velocity up to 2.5Umf and decreased with a further increase in gas velocity. The CPFD model and method employed in this work can be useful for studying the influence of bubble properties on conversion efficiency of a gasification reactor operating at high temperatures.