bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production of medium‐chain‐length PHA in octanoate‐fed enrichments dominated by Sphaerotilus sp.
Authors: Vermeer Chris M. , Depaz Lena , van den Berg Emily , Koelmans Tom , Kleerebezem Robbert 
Published: December 2022

AbstractMedium‐chain‐length polyhydroxyalkanoate (mcl‐PHA) production by using microbial enrichments is a promising but largely unexplored approach to obtain elastomeric biomaterials from secondary resources. In this study, several enrichment strategies were tested to select a community with a high mcl‐PHA storage capacity when feeding octanoate. On the basis of analysis of the metabolic pathways, the hypothesis was formulated that mcl‐PHA production is more favorable under oxygen‐limited conditions than short‐chain‐length PHA (scl‐PHA). This hypothesis was confirmed by bioreactor experiments showing that oxygen limitation during the PHA accumulation experiments resulted in a higher fraction of mcl‐PHA over scl‐PHA (i.e., a PHA content of 76 wt% with an mcl fraction of 0.79 with oxygen limitation, compared to a PHA content of 72 wt% with an mcl‐fraction of 0.62 without oxygen limitation). Physicochemical analysis revealed that the extracted PHA could be separated efficiently into a hydroxybutyrate‐rich fraction with a higher Mw and a hydroxyhexanoate/hydroxyoctanoate‐rich fraction with a lower Mw. The ratio between the two fractions could be adjusted by changing the environmental conditions, such as oxygen availability and pH. Almost all enrichments were dominated by Sphaerotilus sp. This is the first scientific report that links this genus to mcl‐PHA production, demonstrating that microbial enrichments can be a powerful tool to explore mcl‐PHA biodiversity and to discover novel industrially relevant strains.
Description and nomenclature of organ subdivisions in the Terminologia Anatomica and in anatomical education: Comparison with cancer classifications
Authors: Gocht Andreas , Schumacher Udo 
Published: December 2022

AbstractTerminology is the basis for communication among medical professionals. For anatomists, their daily work is based on the Terminologia Anatomica (TA), while pathologists cite the Tumor Node Metastasis (TNM) classification when referring to the anatomical boundaries and regions of malignant tumors. Terminologia Anatomica and clinical‐based classifications, including the TMN classification of tumors, use a world‐wide standardized nomenclature, which has been revised regularly to incorporate new anatomical discoveries and clinically relevant structures. In medical education, students are familiarized with medical nomenclatures in anatomy textbooks and online learning platforms. Sometime, descriptions and illustrations in anatomy teaching materials put a different focus on the importance of anatomical subdivisions and their borders than is found in cancer classifications. This discrepancy contrasts with the efforts of medical societies to define and implement clinically relevant anatomical structures, including organ subdivisions and their boundaries, in daily clinical practice. Here, we illustrate this problem using the larynx and pancreas as examples. Anatomy education should coordinate teaching content with the requirements of the clinical disciplines.
Synthesis of New Ester Derivatives of Salicylic Acid and Evaluation of Their COX Inhibitory Potential
Authors: Koca Mehmet , Anıl Barış , Nişancı Bilal , Bayır Yasin , Ercan Zeynep , Özakar Emrah 
Published: December 2022

AbstractSalicylic acid is an NSAID with serious side effects on the GIS. The side effects of salicylic acid on the GIS are slightly reduced by acetylating salicylic acid. 12 new ester analogs of salicylic acid were synthesized with high yields in this study. The chemical structures of the synthesized compounds were characterized by 1H‐NMR, 13C‐NMR, and HRMS spectra. The inhibitory potential of the compounds was evaluated on COXs by in vitro and in silico studies. The COX2 inhibitory activity of the most potent inhibitor MEST1 (IC50: 0.048 μM) was found to be much higher than the COX2 inhibitory activity of aspirin (IC50: 2.60 μM). In docking studies, the strongest inhibitor among the compounds synthesized was predicted to be MEST1, with the lowest binding energy. Docking studies revealed that MEST1 extends from the hydrophobic channel to the top of the cyclooxygenase active site, forming various interactions with residues in the binding pocket.
Protective Mechanism of Ethyl Gallate against Intestinal Ischemia‐Reperfusion Injury in Mice by in Vivo and in Vitro Studies Based on Transcriptomics
Authors: Fan Shuyuan , Feng Xiaoyan , Li Kun , Li Bin , Diao Yunpeng 
Published: December 2022

AbstractIntestinal ischemia‐reperfusion injury (IIRI) is a common clinical disease that can be life‐threatening in severe cases. This study aimed to investigate the effects of ethyl gallate (EG) on IIRI and its underlying mechanisms. A mouse model was established to mimic human IIRI by clamping the superior mesenteric artery. Transcriptomics techniques were used in conjunction with experiments to explore the potential mechanisms of EG action. Intestinal histomorphological damage, including intestinal villi damage and mucosal hemorrhage, was significantly reversed by EG. EG also alleviated the oxidative stress, inflammation, and intestinal epithelial apoptosis caused by IIRI. 2592 up‐regulated genes and 2754 down‐regulated genes were identified after EG treatment, and these differential genes were enriched in signaling pathways, including fat digestion and absorption, and extracellular matrix (ECM) receptor interactions. In IIRI mouse intestinal tissue, expression of the differential protein matrix metalloproteinase 9 (MMP9), as well as its co‐protein NF‐κB‐p65, was significantly increased, while EG inhibited the expression of MMP9 and NF‐κB‐p65. In Caco‐2 cells in an established oxygen‐glucose deprivation/reperfusion model (OGD/R), EG significantly reversed the decrease in intestinal barrier trans‐epithelial electrical resistance (TEER). However, in the presence of MMP9 inhibitors, EG did not reverse the decreasing trend in TEER. This study illustrates the protective effect and mechanism of action of EG on IIRI and, combined with in vivo and in vitro experiments, it reveals that MMP9 may be the main target of EG action. This study provides new scientific information on the therapeutic effects of EG on IIRI.
Cladiella Octocorals: Enormous Sources of Secondary Metabolites with Diverse Structural and Biological Properties
Authors: Du Ye‐Qing , Liang Lin‐Fu , Guo Yue‐Wei 
Published: December 2022

AbstractMarine octocorals belonging to the genus Cladiella, usually encountered on reefs in the Indo‐Pacific region, have been proven to be rich sources of diverse secondary metabolites with intriguing structural features and promising bioactivities. In this review, 155 compounds from six unambiguously identified C. krempfi, C. australis, C. pachyclados, C. hirsuta, C. tuberculosa, C. conifera, together with several unidentified Cladiella spp. are summarized covering the literatures from 2006 to August 2022. It is noteworthy that diterpenoids dominated the secondary metabolite profile of this genus counting for 78 %. Structurally, the majority of these diterpenes belonged to eunicellan family characterized by different patterns of ether linkage. The impacts of these chemical compositions on an array of potential pharmacological activities were also reviewed, giving an overview of the potential application of Cladiella secondary metabolites.
Use of the MSJCC: A content analysis of ACA journals
Authors: Gantt‐Howrey Alexandra , Becnel Alexander , Shi Yun , Lau Jared 
Published: December 2022

AbstractUsing quantitative content analysis, we examined the prevalence and use of the Multicultural Social Justice Counseling Competencies (MSJCC) in 21 ACA journals between June 2015 and July 2021. We found that only 7.62% of the articles (n = 2860) referenced the MSJCC. Implications for counselor educators are discussed.
Wireless electromechanical enantio‐responsive valves
Authors: Salinas Gerardo , Malacarne Filippo , Bonetti Giorgia , Cirilli Roberto , Benincori Tiziana , Arnaboldi Serena , Kuhn Alexander 
Published: December 2022

AbstractMicrofluidic valves based on chemically responsive materials have gained considerable attention in recent years. Herein, a wireless enantio‐responsive valve triggered by bipolar electrochemistry combined with chiral recognition is reported. A conducting polymer actuator functionalized with the enantiomers of an inherently chiral oligomer was used as bipolar valve to cover a tube loaded with a dye and immersed in a solution containing chiral analytes. When an electric field is applied, the designed actuator shows a reversible cantilever‐type deflection, allowing the release of the dye from the reservoir. The tube can be opened and closed by simply switching the polarity of the system. Qualitative results show the successful release of the colorant, driven by chirality and redox reactions occurring at the bipolar valve. The device works well even in the presence of chemically different chiral analytes in the same solution. These systems open up new possibilities in the field of microfluidics, including also controlled drug delivery applications.
Multi‐layer features ensemble soft sensor regression model based on stacked autoencoder and vine copula
Authors: Chen Hongmin , Li Shaojun 
Published: December 2022

AbstractIt is crucial in industrial processes to consider key variables to ensure safe operation and high product quality. Moreover, these variables are difficult to obtain using traditional measurement methods; hence, it makes sense to develop soft sensor regression models to process the variable prediction. However, there are numerous variables integrating noisy and redundant information in complex industrial processes. Using such variables in traditional regression models may result in reducing the model's efficiency and performance. Thus, this paper proposes a multi‐layer feature ensemble soft sensor regression method using a stacked auto‐encoder (SAE) and vine copula (ESAE–VCR) to address these problems. To do so, the number of neurons in the hidden layer of the SAE is determined by the principal component analysis (PCA). The multi‐layer features of the process variables are extracted using a stacked AE, and the regression models are established for each feature layer. A linear regression ensemble method is used to combine the regression models with the multi‐layer features to obtain the final predictive model that will estimate the values of the key variables. The effectiveness and practicality of the ESAE–VCR are validated by comparing them with several common soft measurement methods in two examples. In the numerical example, the ESAE–VCR yields an accuracy of prediction (R2) of 0.9898 and a root mean square error (RMSE) of 0.1804. In the industrial example, the ESAE–VCR yields an R2 of 0.9908 and an RMSE of 0.1205.
A comparative study of different data representations under CNN and a novel integrated FDD architecture
Authors: Ren Jia , Tang Lijuan , Zou Hongrui 
Published: December 2022

AbstractIn recent years, deep‐learning‐based fault detection and diagnosis (FDD) methods have received extensive attention. As we all know, different input forms have a great impact on the final performance. In this paper, three categories and seven representation methods are discussed: numeric representations, image mapping representations (radar chart mapping and Gramian angular summation field (GASF) mapping), and signal transforming representations (fast Fourier transform (FFT) and wavelet). The tests on the Tennessee Eastman process (TEP) dataset prove that the FFT method has achieved the best performance on average. Based on this, a general FDD integration framework is proposed to integrate multiple base learners together to make decisions by weighted voting or maximum voting. Finally, the comparison between our proposed method and other five typical models (FFT, a GASF and a multi‐scale neural network (GASF–MSNN), convolutional neural network (CNN), Long Short‐Term Memory (LSTM), and Support Vector Machine (SVM)) illustrates the effectiveness of our method for FDD on the TEP. The proposed integrated method provides an effective platform for deep‐learning‐based FDD.
Assessing axial and temporal effects of the leaf sheath on the flexural stiffness of large‐grain stems
Authors: Hale Jared , Webb Spencer , Hale Nathan , Stubbs Christopher , Cook Douglas 
Published: December 2022

AbstractThe leaf sheath of many plants has been observed to influence both stiffness and ultimate strength. For example, the sheath has been observed to be closely related to “greensnap” (or “brittle‐snap”) failure of Zea mays. The goal of this study was to develop a method for assessing longitudinal and temporal patterns of sheath influence on flexural stiffness. This metric was chosen because it has been shown to be predictive of ultimate bending strength. A three‐point bending test method was developed for assessing the longitudinal and temporal influence of the sheath on flexural stiffness of Zea mays. Comparisons between pairs of tests at the same location (sheath present vs. absent) were performed. Four types of maize were tested. The sheath had a statistically significant influence on bending. Sheath influence appears to be closely related to maturity since both spatial and temporal patterns of influence mirror the sigmoidal maturation patterns previously observed in maize stalks. The paired nature of this method increases statistical significance and allows for multiple tests along the length of the stalk. Results indicate that the influence of the sheath changes over the life span of the Zea mays in parallel with maturation patterns. However, further studies will be needed to confirm this hypothesis more broadly and to study additional issues such as heritability and the influence of genotype and environment on sheath effects. Due to the common architecture of Poacea plants, this method can be used to provide new insights on sheath influences of various species.
White gastric mucosa during endoscopy as a new endoscopic feature of chronic ischemic gastritis: A case report
Authors: Ichita Chikamasa , Sasaki Akiko , Isogai Naoko , Sumida Chihiro , Nishino Takashi , Kubota Jun , Shionoya Kento , Kimura Karen 
Published: December 2022

AbstractChronic ischemic gastritis (CIG) requires early diagnosis and treatment as complications of thromboembolism can be fatal. Although computed tomography (CT) is useful in the diagnosis of CIG, it is difficult to diagnose from a patient's history, endoscopic findings, and tissue biopsy. Identification of the key findings that motivate computed tomography is an important issue. We report a case of CIG diagnosed by endoscopic findings of white patches of mucosa over time. A 63‐year‐old man presented with epigastric pain. He had a history of repeated gastric ulcers of an undetermined cause. We performed upper endoscopy and observed the appearance of multiple white patches on the gastric mucosa. Central vessel stenosis was considered, and aortic computed tomography revealed complete occlusion of the superior mesenteric artery and stenosis of the celiac artery. We carried out a surgical bypass and found no postoperative endoscopic mucosal changes or abdominal pain. White patch changes in the gastric mucosa over time during endoscopy may indicate CIG. This finding may help in the future diagnosis of CIG.
EdgeMesh: A hybrid distributed training mechanism for heterogeneous edge devices
Authors: Xu Fei , Feng Jianqiang , Zhang Zhuoya , Ning Linpeng , Jia Yuxi 
Published: December 2022

AbstractThe proliferation of large‐scale distributed Internet of Things (IoT) applications has resulted in a surge in demand for network models such as deep neural networks (DNNs) to be trained and inferred at the edge. Due to the central data transmission mechanism, heterogeneity of edge devices, and resource constraints, the existing single data‐parallel, and model‐parallel distributed training mechanisms frequently fail to fully utilize the computing power of edge devices, network topology and bandwidth resources. In light of the shortcomings mentioned earlier, this article proposes EdgeMesh, a hybrid parallel training mode based on the Mesh‐Tensorflow framework, consisting of an adaptive meshing strategy and a dynamic model convolutional partitioning strategy. The computing power of IoT edge devices significantly speeds up the DNN training process. In a resource‐constrained environment, each node only supports a subset of the model's parallel computing tasks, reducing communication and memory overhead while retaining high scalability. Experiments show that when compared to single‐machine training and data parallel mode, EdgeMesh distributed training mechanism can reduce the average delay by 3.2 times and average memory overhead by 43% while maintaining model accuracy. The computing power of IoT edge devices effectively accelerates the DNN training process.
Estimation of grain yield in wheat using source–sink datasets derived from RGB and thermal infrared imaging
Authors: Li Rui , Wang Dunliang , Zhu Bo , Liu Tao , Sun Chengming , Zhang Zujian 
Published: December 2022

AbstractTimely and efficient monitoring of crop aboveground biomass (AGB) and grain yield (GY) forecasting before harvesting are critical for improving crop yields and ensuring food security in precision agriculture. The purpose of this study is to explore the potential of fusing source–sink‐level color, texture, and temperature values extracted from RGB images and thermal images based on proximal sensing technology to improve grain yield prediction. High‐quality images of wheat from flowering to maturity under different treatments of nitrogen application were collected using proximal sensing technology over a 2‐year trial. Numerous variables based on source and sink organs were extracted from the acquired subsample images, including 30 color features, 10 texture features, and two temperature values. The principal component analysis (PCA), least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE) were used to screen variables. Support vector regression (SVR) and random forest (RF) were applied to establish AGB estimation models, and the GY prediction models were built by RF. The source dataset and sink dataset performed differently on AGB and GY estimation, but the combined source–sink dataset performed best for estimating both AGB and GY. Based on the source–sink dataset, the LASSO‐RF model was the best combination for predicting AGB and GY, with the coefficient of determination (R2) of 0.85 and 0.86, root mean square error (RMSE) of 1179.09 and 609.61 kg ha−1, and the ratio of performance to deviation (RPD) of 2.10 and 2.45, respectively. This study demonstrates that the multivariate eigenvalues of both source and sink organs have the potential to predict wheat yield and that the combination of machine learning models and variable selection methods can significantly affect the accuracy of yield prediction models and achieve effective monitoring of crop growth at late reproductive stages.
A new option for mortality–interest rates
Authors: Lin Tzuling , Tsai Cary Chi‐Liang 
Published: December 2022

AbstractWe propose a new type of mortality–interest option related to a new random variable, the force of mortality–interest denoted as , the addition of the force of mortality and the force of interest. We assume moves approximately linearly, design the new mortality–interest option, and then derive closed‐form formulas for its expected values. We show that using the new mortality–interest options, an annuity provider and a life insurer can, respectively, hedge the longevity and mortality risks with interest rate risk; a financial intermediary selling the new options can benefit from natural hedges resulted from two‐side businesses with the annuity provider and life insurer.
Practice patterns for positive sentinel lymph node in head and neck melanoma
Authors: Berania Ilyes , Tzelnick Sharon , de Almeida John R. , McKinnon Gregory , Goldstein David P. 
Published: December 2022

AbstractBackgroundAn international survey was conducted to investigate the preferences for completion lymph node dissection (CLND) in head and neck melanomas.MethodsA questionnaire was sent through the American Society of Head & Neck Surgery (AHNS) and Canadian Society of Otolaryngology‐Head and Neck Surgery (CSO).ResultsHundred and forty‐nine surgeons completed the survey. Response rate was 6.3% and 9.7% from AHNS and CSO members, respectively. When presented the scenario of a 47‐year‐old male with a clinical T3bN0 cheek melanoma, with 1/1 positive sentinel lymph node (SLN) with nodal deposit <2 mm, 72 of respondents (48.3%) would perform a CLND. Reasons for CLND included multiples positive SLN (64.1%), size of nodal deposits (54.2%), and perceived lack of compliance to follow‐up (54.2%). Surgeons with access to immunotherapy treatment were less likely to recommend CLND (p = 0.025).ConclusionsFollowing SLN biopsy, nearly half of the surveyed head and neck surgeons would recommend CLND, which contrasts with the current melanoma practice patterns in other anatomic locations. However, compared with an earlier study in the literature it does seem that there has been a shift away from completion neck dissection. Further investigation into understanding practice variations is warranted.
A distinct impact of repeated morphine exposure on synaptic plasticity at Schaffer collateral‐CA1, temporoammonic‐CA1, and perforant pathway‐dentate gyrus synapses along the longitudinal axis of the hippocampus
Authors: Anvari Sohrab , Foolad Forough , Javan Mohammad , Mirnajafi‐Zadeh Javad , Fathollahi Yaghoub 
Published: December 2022

AbstractWe aimed to study how morphine affects synaptic transmission in the dentate gyrus and CA1 regions along the hippocampal long axis. For this, recording and measuring of field excitatory postsynaptic potentials (fEPSPs) were utilized to test the effects of repeated morphine exposure on paired‐pulse evoked responses and long‐term potentiation (LTP) at Schaffer collateral‐CA1 (Sch‐CA1), temporoammonic‐CA1 (TA‐CA1) and perforant pathway‐dentate gyrus (PP‐DG) synapses in transverse slices from the dorsal (DH), intermediate (IH), and ventral (VH) hippocampus in adult male rats. After repeated morphine exposure, the expression of opioid receptors and the α1 and α5 GABAA subunits were also examined. We found that repeated morphine exposure blunt the difference between the DH and the VH in their basal levels of synaptic transmission at Sch‐CA1 synapses that were seen in the control groups. Significant paired‐pulse facilitation of excitatory synaptic transmission was observed at Sch‐CA1 synapses in slices taken from all three hippocampal segments as well as at PP‐DG synapses in slices taken from the VH segment in the morphine‐treated groups as compared to the control groups. Interestingly, significant paired‐pulse inhibition of excitatory synaptic transmission was observed at TA‐CA1 synapses in the DH slices from the morphine‐treated group as compared to the control group. While primed‐burst stimulation (a protocol reflecting normal neuronal firing) induced a robust LTP in hippocampal subfields in all control groups, resulting in a decaying LTP at TA‐CA1 synapses in the VH slices and at PP‐DG synapses in both the IH and VH slices taken from the morphine‐treated rats. In the DH of morphine‐treated rats, we found increased levels of the mRNAs encoding the α1 and α5 GABAA subunits as compared to the control group. Taken together, these findings suggest the potential mechanisms through which repeated morphine exposure causes differential changes in circuit excitability and synaptic plasticity in the dentate gyrus and CA1 regions along the hippocampal long axis.