bluuebunny/crossref_metadata_2025_split huggingface dataset:
Piezocatalytic inactivation of water bacterium and heterotrophism -An overview
Authors: Ali Ahsan , Chen Longbin , Nasir Muhammad Salman , Wu Chao , Guo Baolin , Yang Yaodong 
Published: June 2022

Abstract
Seeking advanced techniques to fight against emerging contaminants is a need of time to overcome severe human risks. Piezoelectric materials paved the way to solve this problem as a new type of catalytic technique, including an advanced oxidation process. Piezocatalysis, which can produce reactive oxygen species in response to applied stress, has remarkably progressed to degrade organic pollutants and pathogens in the past few years. However, the relationship between bacteria and organic compounds through the heterotrophic process was the dominant factor contributing to an acceleration in water contamination. Reactive oxygen species can initiate the reaction with interaction with a diverse range of targets, and it demonstrated the strong bacterial antagonism in response to the piezocatalytic process under ultrasound. Unlike regular antibiotics for antimicrobial resistance, engineered piezoelectric materials could be the potential alternative to many conventional treatments for pathogens. This review thoroughly studied the basic information that supports further understanding of the mechanism and influence factors involved in these catalytic processes. Neglected relation of bacteria with organic dyes evaluated to understand the chain of mutual contaminants relation. Based on reviewing the materials, bacteria, related physiochemical dependences, and piezocatalytic advances, we provide the prospects for the possible development of health-related applications.
Systematic assessment and optimizing algorithm of tumor mutational burden calculation and their implications in clinical decision-making
Authors: Sun Daqiang , Xu Meilin , Pan Chaohu , Tang Hongzhen , Wu Dongfang , Luo Haitao 
Published: June 2022

Abstract
Tumor mutation burden (TMB) has been validated as a biomarker to predict the response of immune checkpoint inhibitors (ICIs) treatment in various cancers. However, the effects of different sequencing platforms, cancer types, and calculation algorithms on TMB as well as its cut-off value for predicting immunotherapy efficacy in the East Asian population still need to be further investigated. In this study, the data of 4126 samples generated by targeted panel sequencing or whole-exome sequencing (WES) in different platforms and public sequencing data from 3680 samples that contained targeted panel sequencing, WES and whole-genome sequencing (WGS) were obtained. The impact of different sequencing platforms and methods on TMB calculation was assessed. No significant bias was found in TMB calculated by different platforms. However, TMB calculated from WGS was significantly lower than those calculated from targeted panel sequencing and WES. The distribution of TMB at different sequencing depths and tumor purity were analyzed. There was no significant difference in the distribution of TMB when the sequencing depth was greater than 500, the tumor purity estimated by hematoxylin-eosin (HE) staining was between 0.1 to 0.8 or estimated by next-generation sequencing (NGS) was greater than 0.4. In addition, the somatic-germline-zygosity (SGZ) algorithm was optimized to calculate TMB from tumor-only sequencing samples in the East Asian population. The correlation coefficient of TMB calculated with the optimized SGZ algorithm and paired normal-tumor sequencing is 0.95. Furthermore, the optimal cut-off value of TMB in East Asian lung cancer patients treated with ICIs was determined to be 7.19 mut/Mb instead of 10 mut/Mb through the ROC curve and Log-rank analysis in the training cohort and validated in the test cohort. Patients with TMB ≥ 7.19 mut/Mb had better outcomes than patients with TMB <7.19 mut/Mb. In conclusion, this study systematically analyzed the factors that influenced the TMB calculation and optimized the SGZ algorithm to calculate TMB from tumor-only sequencing samples in the East Asian population. More importantly, the cut-off value of TMB for predicting immunotherapy efficacy was determined to be 7.19 mut/Mb instead of 10 mut/Mb in East Asian lung cancer patients, which can help in clinical decision-making.
Autologous hematopoietic stem cell transplantation improves long term survival – data from a national registry
Authors: Blank Norbert , Schmalzing Marc , Moinzadeh Pia , Oberste Max , Siegert Elise , Müller-Ladner Ulf , Riemekasten Gabriela , Günther Claudia , Kötter Ina , Zeidler Gabriele , Pfeiffer Christiane , Juche Aaron , Jandova Ilona , Ehrchen Jan , Susok Laura , Schmeiser Tim , Sunderkoetter Cord , Distler Jörg H. W. , Worm Margitta , Kreuter Alexander , Keyzer Gernot , Lorenz Hanns-Martin , Krieg Thomas , Hunzelmann Nicolas , Henes Joerg 
Published: June 2022

Abstract
BackgroundCurrent recommendations on the management of systemic sclerosis (SSc) suggest that autologous hematopoietic stem cell therapy (HSCT) can be a rescue therapy for patients with rapidly progressive SSc. Objectives To assess safety and efficacy of HSCT for patients with SSc and to compare these with non-HSCT patient in a control cohort with adjusted risk factors.MethodsA retrospective analysis of data from the multicentric German network for systemic scleroderma (DNSS) with 5000 patients with SSc. Control groups consisted of all patients with diffuse cutaneous (dc)-SSc (group A) and an adjusted high risk cohort of male patients with Scl70-positive dc-SSc (group B).ResultsEighty SSc patients received an HSCT 4.1 ± 4.8 years after SSc diagnosis. Among them 86.3% had dc-SSc, 43.5% were males, and 71.3% were positive for Scl70 antibodies. The control group A showed a significant underrepresentation of these risk factors for mortality. When the survival of the control group B was compared with the HSCT group, a lower mortality of the latter was observed instead. Within 5 years after HSCT, we observed an improvement of the mRSS from 17.6 ± 11.5 to 11.0 ± 8.5, and an improvement of the DLCO from 54.6 ± 17.8% to 60.0 ± 18.5%. We did not see differences in transplant-related mortality between patients who received HSCT within 3 years after SSc diagnosis or later.ConclusionOur analysis of real life data show that the distribution of risk factors for mortality is critical when HSCT cohorts are compared with non-HSCT control groups.
A novel triplex real-time PCR method for the simultaneous authentication of meats and antlers from sika deer (Cervus nippon) and red deer (Cervus elaphus)
Authors: Liu Guo-Qiang , Luo Jian-Xing , Xu Wei-Liang , Li Chun-Dong , Guo Liang 
Published: June 2022

Abstract
Deer products have been used as a traditional Chinese medicine for over 2000 years. Due to the high price, the meats and antlers are often adulterated with low-value materials. The present study developed a triplex real-time PCR assay to simultaneously identify the DNA from sika deer and red deer in deer products. The triplex real-time PCR approach showed high specificity for 16 animal species, and the method simultaneously amplified an endogenous control to eliminate false-negative results. The absolute limits of detection for raw meat, meat product, and antlers were 0.05–0.025 pg, 0.05–0.025 pg, and 0.1–0.025 pg, respectively, for sika deer and 0.05–0.025 pg, 0.5–0.25 pg, and 2.5–0.25 pg, respectively, for red deer. This approach could determine 0.1% (w/w) adulteration. In conclusion, the established triplex real-time PCR assay displayed high specificity and sensitivity and can be used for authentic animal products from sika deer and red deer.
Gastrodin Regulates GLUR2 Internalization and Reduces BDNF Expression in the Cerebellum of Diabetic Rats
Authors: Liang Yu-bo , Wang Yao-yi , Wu Xing-yan , Liu Yi-dan , Mu Zhi-hao , Zhang Ying , Zhang Chao , Fan Ying-jing , Che Shu-li , Qian Zhong-yi , Cui Ge , Zhang Ying , Miao Yi-he , Zou Ying-ying 
Published: June 2022

Abstract
Cognitive dysfunction is a serious neurological complication of diabetes mellitus (DM). Recent studies have found that in addition to the hippocampus, the cerebellum is also involved in regulating cognitive functions such as learning and memory through long-term depression (LTD), but the molecular mechanism of cognitive impairment resulted from cerebellum dysfunction in diabetes has not been fully elucidated. Moreover, gastrodin has been supposed to reduce the incidence of Alzheimer's disease and improve function in the central nervous system. This study aimed to evaluate the changes of LTD-related factors including GluR2, p-GluR2, PKC, BDNF, and TrkB in the cerebellar cortex of diabetic rats by western blotting and double immunofluorescence, and to explore the therapeutic effect of gastrodin. We found that there was neuronal necrosis and neuronophagia in the cerebellar cortex of diabetic rats, the protein expression levels of GluR2 and PKC in Purkinje cells were significantly decreased, and p-GluR2, BNDF and TrkB were significantly increased. After treatment with gastrodin, the damage of Purkinje cells was ameliorated, and the expression of the above factors was restored to a certain extent. Arising from the above, Thus, diabetes may cause cerebellar LTD by affecting the internalization of GluR2, thereby causing cognitive dysfunction. Gastrodin ameliorates cerebellar neuronal damage and restores the expression levels of GluR2 and BDNF in diabetic rats.
The effects of the E3 ubiquitin–protein ligase UBR7 of Frankliniella occidentalis on the ability of insects to acquire and transmit TSWV
Authors: Shi Jun-Xia , Zhou Jun-Xian , Jiang Fan , Li Zhi-Hong , Zhu Shuifang 
Published: June 2022

Abstract
The interactions between plant viruses and vector insects are complex. In recent years, RNA Sequencing data have been used to elucidate the key genes of tomato spotted wilt orthotospovirus (TSWV) and Frankliniella occidentalis (F. occidentalis). However, very little is known about the key genes involved in thrip acquisition and transmission of TSWV. On the basis of the transcriptome data of F. occidentalis with TSWV, we verified the complete sequence of the E3 ubiquitin-protein ligase UBR7 gene (UBR7), which was closely related to virus transmission. Additionally, we found that UBR7 belongs to the E3 ubiquitin–protein ligase family, which was highly expressed in adulthood of F. occidentalis. The transmission efficiency of F. occidentalis decreased with low URB7 expression, while the acquisition efficiency was not affected. Moreover, the direct interaction between UBR7 and the nucleocapsid (N) protein of TSWV was investigated through surface plasmon resonance and GST pull-down. In conclusion, we found that UBR7 is a key protein for TSWV transmission of F. occidentalis, which directly interacts with TSWV N. This study provides a new direction for the development of green pesticides targeting E3 ubiquitin to control TSWV and F. occidentalis.
Interpretation of global tsunami height distribution due to the 2022 Hunga Tonga-Hunga Ha’apai volcanic eruption
Authors: Yamashita Kei , Kakinuma Taro 
Published: June 2022

Abstract
Tsunamis generated by atmospheric pressure waves due to a volcanic eruption were investigated based on both the proposed estimation formulas and numerical calculations. First, assuming linear shallow water conditions, estimation formulas were proposed for the maximum possible amplitude and the resonance distance. Second, the fundamental properties of tsunamis generated by atmospheric pressure waves were examined numerically using both the nondispersion and weak dispersion models. Based on the numerical results, a ridge and shelf can amplify tsunamis due to atmospheric pressure waves beyond the limits of the Proudman resonance. The estimated and numerically determined maximum possible amplitudes agreed well when the dispersion of tsunamis was not large. Third, the distribution maps of the maximum possible amplitude and the resonance distance for various traveling velocities of atmospheric pressure waves were generated using the proposed formulas. The maximum tsunami amplitude depends on both the length of the excitation area and the resonance distance along the path of atmospheric pressure waves. The worldwide distribution of both the tsunami height and the appearance time of the maximum tide level fluctuations due to the 2022 Tonga volcanic eruption and several historical eruptions were interpreted based on the distribution maps. In the historical large eruptions, the period of the atmospheric pressure waves was shorter; thus, the dispersion effect was larger, resulting in a smaller tsunami amplitude.
The ecological dimension of global trade: origin and recipient regions of biological invasion costs
Authors: Hudgins Emma , Cuthbert Ross , Haubrock Phillip , Taylor Nigel , Kourantidou Melina , Nguyen Dat , Bang Alok , Turbelin Anna , Moodley Desika , Briski Elizabeta , Kotronaki Syrmalenia , Courchamp Franck 
Published: June 2022

Abstract
Globalization challenges sustainability by intensifying the ecological and economic impacts of biological invasions. These impacts may be unevenly distributed worldwide, with costs disproportionately incurred by a few regions. Here, we identify how invasion economic costs are distributed among origin and recipient regions at country and continent levels, and determine socio-economic and biodiversity-related predictors of invasion cost dynamics. Flows of invasive alien species causing costs originated from several regions, most frequently flowing to Europe, whereas monetary costs predominantly flowed from Asia to North America. High cost flows between countries were related to various environmental and socio-economic factors, such as shared biomes, high GDP and a common language. This characterization of ‘sender’ and ‘receiver’ regions of invasive alien species and their associated cost can inform biosecurity planning and the prioritization of control efforts across invasion routes, to achieve more sustainable economies and societies, while protecting biodiversity.
Federated Learning aided Breast Cancer Detection with Intelligent Heuristic-based Deep Learning Framework
Authors: kathole atul b 
Published: June 2022

Abstract
Breast cancer is the second largest cause of female cancer death and one of the most hazardous diseases that leads to a higher mortality rate. Breast cancer is initialized with the malignant stage, where the abnormal growth of cancerous lumps is initiated from the breast cells. Periodic clinical checks and self-tests assist in early identification and thus progress the survival rates considerably. One of the eminent medical approaches is breast cancer recognition, which offers scientists and researchers huge complications. Breast cancer detection at an early stage permits the patients to receive suitable treatment, which increases the chances of survival. Thus, this paper utilizes a new form of artificial intelligence training called Federated Learning (FL), especially for breast cancer detection, the most eminent technique in the last few years. FL permits individual hospitals to benefit from the rich datasets of multiple non-affiliated hospitals without centralizing the data in one place. Hence, FL utilizes numerous collaborators for building a strong deep-learning model using a large dataset. In this paper, a hybridization of this type of training with a meta-heuristic and deep learning is aimed to be proposed for breast cancer diagnosis. This model encloses diverse steps that include (a) image collection, (b) feature extraction, and (c) classification phase. Initially, the mammogram images related to breast cancer are collected with the concept of FL from the affected individuals. The federated learning helps in reducing the processing time and ensures better performance of the proposed model. The obtained images are considered for the feature extraction phase. The Densenet architecture is used to extract the features used in the classification phase with the help of Enhanced Recurrent Neural Networks (E-RNN) for detecting breast cancer. Here, the performance is enhanced by tuning the certain parameter in the RNN network using a hybrid optimization algorithm called Hybrid Dragon-Rider Optimization (HDRO) with Dragonfly Algorithm (DA) and Red deer algorithm (RDA) to achieve accurate classification results. The experimental results demonstrate the effectiveness of the suggested breast cancer diagnosis model compared with conventional approaches using diverse quantitative measures.
Numerical simulation of pollution transport and hydrodynamic characteristics through the river confluence using FLOW 3D
Authors: Chabokpour Jafar , Azamathulla Hazi Md 
Published: June 2022

Abstract
The current study tried to investigate the hydrodynamic characteristics and the pollution mixing and dispersion from the sub-branch through the river confluence using the numerical model of Flow3D. A numerical model was used with length, width, and height of (7 × 1 × 1) m. Also, the nested mesh was used in the junction to refine the modeling and result depiction. It was observed that if there is a water level difference on both sides of the junction, the mixing will occur much faster, and only longitudinal mixing will prevail downstream of the junction. Therefore, it was concluded that to reduce the contamination effect through the river networks, the water level in the main channel should be higher than the sub-branch. In the flow separation zone, several clockwise vortices were observed, which become weaker by moving towards the outer wall of the channel. Also, the most significant velocity vectors and also the highest contaminant concentration was observed in this region. Moreover, the vertical distribution of pollution concentration showed that the contaminant concentration would be higher at large distances above the channel bed. The highest values of turbulent intensity and turbulent kinetic energy were also observed in flow recirculation zone. It was concluded that by increase of concentration gradient through the shear layers, the required mixing length for complete transverse pollution mixing would be decreased.
Densification of activated sludge for better settling performances: experimental characterization in batch column and model parameters calibration
Authors: Roche Clément , Medina Maria Elena Valle , Schmitt Philippe , Pallarès Anne , Pallarès Gwenaël , Meilliez Mélanie , Laurent Julien 
Published: June 2022

AbstractConventional activated sludge (CAS) and densified sludge obtained using hydro-cyclone selective wasting were compared at a full-scale water resources recovery facility. The densified tested sludge, containing around 30–50% of aerobic granules, showed enhanced settleability with low and stable sludge volume index (SVI) compared to CAS, which suffered recurrent filamentous bulking. Further in-depth batch settling tests were carried out using a 40 cm diameter column fitted with ultrasonic transducers to monitor both sludge blanket height and vertical velocity profiles. Hindered settling and compression parameters were calibrated from the experiment for latter modelling use. Test sludge displayed more than doubled settling velocities compared to CAS, with hindered settling velocities remaining &gt;3 m·h−1 even at high solids concentrations of 6.85 g·L−1. The compression regime was attained at much higher critical concentration for the test sludge. It also displayed enhanced thickening properties, with concentrations obtained after 30 min of settling being 20.9 and 8.5 g·L−1 respectively for test and control sludge. This allows for a substantial reduction of recirculation rates in practice. These results open perspectives in optimizing existing plant operation as well as clarifier design and modelling using densified sludge.
Combinatorial Chemistry and Natural Products: Determination of the Biological Activity of On­Bead, Double Cleavable Teicoplanin Aglycone (TD)
Authors: Sizemore Christine F. , Seneci Pierfausto , Kocis Petr , Wertman Kenneth F. , Islam Khalid 
Published: June 2022

Abstract:
Teicoplanin aglycone (TD), a derivative of the naturally occurring antibiotic, was coupled to Tentagel resin beads using a releasable linker technique. The biological properties of the compound were examined in growth inhibition assays after cleavage of the linker under different pH conditions. The results show that combinatorial techniques on solid-phase can be used for large, complex molecules, and that the biological method described may be generally useful for high volume screening of large combinatorial chemical libraries.
Neuropharmacology of Organoselenium Compounds in Mental Disorders
and Degenerative Diseases
Authors: Birmann Paloma T. , Casaril Angela M. , Abenante Laura , Penteado Filipe , Brüning César A. , Savegnago Lucielli , Lenardão Eder J. 
Published: June 2022

Abstract:
Neurodegenerative and mental disorders are a public health burden with pharma-cological treatments of limited efficacy. Organoselenium compounds are receiving great at-tention in medicinal chemistry mainly because of their antioxidant and immunomodulatory activities, with a multi-target profile that can favor the treatment of multifactorial diseases. Therefore, the purpose of this review is to discuss recent preclinical studies about orga-noselenium compounds as therapeutic agents for the management of mental (e.g., depres-sion, anxiety, bipolar disorder, and schizophrenia) and neurodegenerative diseases (e.g., Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and multiple sclero-sis). We have summarized around 70 peer-reviewed articles from 2016 to the present that used in silico, in vitro, and/or in vivo approaches to assess the neuropharmacology of seleni-um-containing compounds. Among the diversity of organoselenium molecules investigated in the last five years, diaryl diselenides, Ebselen-derivatives, and Se-containing heterocycles are the most representative. Ultimately, this review is expected to provide disease-oriented information regarding the neuropharmacology of organoselenium compounds that can be useful for the design, synthesis, and pharmacological characterization of novel bioactive molecules that can potentially be clinically viable candidates.
Recent Progress on the Role of Fibronectin in Tumor Stromal Immunity and Immunotherapy
Authors: Peng Zheng , Lv Xiaolan , Huang Shigao 
Published: June 2022

Abstract:As a major component of the stromal microenvironment of various solid tumors, the ex-tracellular matrix (ECM) has attracted increasing attention in cancer-related studies. ECM in the tumor stroma not only provides an external barrier and framework for tumor cell adhesion and movement, but also acts as an active regulator that modulates the tumor microenvironment, includ-ing stromal immunity. Fibronectin (Fn), as a core component of the ECM, plays a key role in the assembly and remodeling of the ECM. Hence, understanding the role of Fn in the modulation of tumor stromal immunity is of great importance for cancer immunotherapy. Hence, in-depth studies on the underlying mechanisms of Fn in tumors are urgently needed to clarify the current under-standing and issues and to identify new and specific targets for effective diagnosis and treatment purposes. In this review, we summarize the structure and role of Fn, its potent derivatives in tumor stromal immunity, and their biological effects and mechanisms in tumor development. In addition, we discuss the novel applications of Fn in tumor treatment. Therefore, this review can provide pro-spective insight into Fn immunotherapeutic applications in tumor treatment.