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Prediction of the biogas production using GA and ACO input features selection method for ANN model

Information Processing in Agriculture 2019年第3期6卷 349-356页

作者： tanja beltramo Michael Klocke Bernd Hitzmann Institute of Food Science and Biotechnology University of HohenheimStuttgart 70599Germany Leibniz Institute for Agricultural Engineering and Bioeconomy Potsdam 14469Germany

This paper presents a fast and reliable approach to analyze the biogas production process with respect to the biogas production *** experimental data used for the developed models included 15 process variables measured at an agricultural biogas plant in *** this context,the concentration of volatile fatty acids,total solids,volatile solids acid detergent fibre,acid detergent lignin,neutral detergent fibre,ammonium nitrogen,hydraulic retention time,and organic loading rate were *** neural networks(ANN)were established to predict the biogas production *** ant colony optimization and genetic algorithms were implemented to perform the variable *** identified the significant process variables,reduced the model dimension and improved the prediction capacity of the ANN *** best prediction of the biogas production rate was obtained with an error of prediction of 6.24%and a coefficient of determination of R2=0.9.

关键词： Ant colony optimization Artificial neural networks Biogas Genetic algorithm

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Identification and Expression of Some Plant Cell Wall-Degrading Enzymes Present in Three Ontogenetics Stages of Thecaphora frezii, a Peanut (<i>Arachis hypogaea</i>L.) Pathogenic Fungus

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American Journal of Plant Sciences 2022年第1期13卷 1-22页

作者： Néstor Walter Soria Ana Cristina Figueroa María Soledad Díaz Valeria Roxana Alasino Pablo Yang Dante Miguel beltramo Cátedra de Biotecnología Facultad de Ciencias Químicas Unidad Asociada al CONICET: área de Cs. Agrarias Ingeniería Cs. Biológicas Universidad Católica de Córdoba Córdoba Argentina Centro de Excelencia en Productos y Procesos de Córdoba—CEPROCOR Santa María de Punilla Córdoba Argentina CONICET Santa María de Punilla Córdoba Argentina

Peanuts can be affected by the presence of pathogenic microorganisms. The fungus Thecaphora frezii (T. frezii), which belongs to the taxonomic class Ustilaginomycetes, is the causal agent of the disease known as “peanut smut”. The life cycle of this fungus includes three stages, namely teliospores, basidiospores and hyphae. In the hyphae stage, infection occurs in the peanut plant, which requires the involvement of some enzymes secreted by the fungus. These include the Plant Cell Wall-Degrading Enzymes (PCWDEs), which degrade various polysaccharides. This study aimed to identify the presence of transcript for enzymes belonging to the PCWDEs from three stages of T. frezii. For this, total RNA was extracted from the three ontogenetic stages of T. frezii. These samples were analyzed using an RNA-Seq approach and some transcripts were quantified using Real Time PCR. The analysis of the data provided by the RNA-Seq of the three T. frezii stages, it was possible to identify some transcripts that could encode enzymes compatible with polysaccharides degradation that are part of the plant cell wall. In T. frezii transcriptome, 40 deduced proteins would be enzymes with functions of PCWDEs were identified. They were divided into 27 glycoside hydrolases;two polysaccharide lyases;three carbohydrate esterases and eight enzymes with auxiliary activities. In addition, the fungal SNF1 gene was identified whose activity could be affected by high glucose level, and indirectly influence the levels of some PCWDEs. The analysis of the PCWDEs could help to understand part of the fungal infection process and possibly find substances that can control its development.

关键词： Carbohydrate-Degrading Enzymes Phytopathogenic Fungi Smut Fungi Transcriptome Thecaphora frezii

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免疫疗法联合立体定向放疗治疗非小细胞肺癌脑转移:一项AIRO多中心回顾性研究

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中国肺癌杂志 2022年第4期25卷 I0007-I0022页

作者： Silvia SCOCCIANTI Emanuela OLMETTO Valentina PINZI Mattia Falchetto OSTI Rossella Di FRANCO Saverio CAINI Paola ANSELMO Paolo MATTEUCCI Davide FRANCESCHINI Cristina MANTOVANI Giancarlo beltramo Francesco PASQUALETTI Alessio BRUNI Paolo TINI Emilia GIUDICE Patrizia CIAMMELLA Anna MERLOTTI Sara PEDRETTI Marianna TRIGNANI Marco KRENGLI NiccolòGIAJ-LEVRA Isacco DESIDERI Guido PECCHIOLI Paolo MUTO Ernesto MARANZANO Laura FARISELLI Pierina NAVARRIA Umberto RICARDI Vieri SCOTTI Lorenzo LIVI 王绿化(翻译/校对) Radiation Oncology Unit Ospedale Santa Maria AnnunziataDepartment of OncologyBagno a RipoliFlorenceItaly Radiation Oncology Unit Azienda Ospedaliero Universitaria CareggiDepartment of Experimental and Clinical Biomedical Sciences"Mario Serio"FlorenceItaly U.O Radioterapia Fondazione IRCCS Istituto Neurologico Carlo BestaDepartment of NeurosurgeryMilanItaly U.O.C Radioterapia A.O.U Sant'Andrea Facolta Medicina e Psicologia Universita SapienzaDepartment of MedicineSurgery and Translational MedicineRomeItaly Istituto Nazionale Tumori IRCCS Fondazione G.PascaleDepartment of RadiotherapyNaplesItaly Institute for Cancer Research Prevention and Clinical Network(ISPRO)Cancer Risk Factors and Life-Style Epidemiology UnitFlorenceItaly Radiotherapy Oncology Center S.Maria HospitalDepartment of OncologyTerniItaly Humanitas Research Hospital Radiotherapy and Radiosurgery DepartmentRozzanoItaly Radiotherapy Unit Department of OncologyTurinItaly Cyberknife Centro Diagnostico Italiano Department of RadiologyMilanItaly Radiation Oncology Azienda Ospedaliero Universitaria PisanaDepartment of Translational MedicinePisaItaly Radiotherapy Unit University Hospital of ModenaDepartment of Oncology and HematologyModenaItaly Radiotherapy Unit University of SienaDepartment of Radiotherapy and OncologySienaItaly UOC di Radioterapia Policlinico Universitario Tor VergataDepartment of Onco-HaematologyRomeItaly Radioterapia Oncologica"G.Prodi "AO-IRCCS Arcispedale S.Maria NuovaDepartment of Oncology and Advanced TechnologyReggio EmiliaItaly Radiation Oncology A.S.O.S.Croce e Carle Department of Radiation OncologyCuneoItaly U.O.Radioterapia Oncologica Department of Radiation OncologyASST Spedali Civili di Brescia e Universita degli studi di BresciaBresciaItaly U.O.C.Radioterapia Oncologica Ospedale Clinicizzato SS Annunziata-Universita Chieti G.D'AnnunzioDepartment of Radiation OncologyChietiItaly Radiation Oncology University Hospital Maggiore della CaritdDepartment of Translational Medicine

背景与目的通过意大利放射治疗和临床肿瘤学学会(Italian Association of Radiotherapy and Clinical Oncology, AIRO)的一项多中心回顾性研究,明确免疫疗法(immunotherapy, IT)和立体定向放疗(stereotactic radiotherapy,SRT)包括放射外科治疗(radiosurgery, RS)或大分割立体定向放疗(hypofractionated stereotactic radiotherapy, HFSRT)治疗非小细胞肺癌(non-small cell lung cancer, NSCLC)脑转移的疗效和毒性。方法对来自19个意大利中心接受SRT+IT的NSCLC伴脑转移患者进行分析,并与单独接受SRT的对照组患者进行比较。结果共纳入SRT+IT组100例和单独SRT组50例。接受SRT+IT的患者有更长的颅内局部无进展生存期(intracranial local progression-free survival, i LPFS)(经倾向性评分调整后,P=0.007)。在诊断为脑转移时接受IT合并有颅外进展的患者中(n=24),接受SRT后再进行IT与较好的总生存期(overall survival, OS)相关(P=0.037)。多因素分析显示组织学类型为非腺癌、卡氏体能状态(Karnofsky performance status,KPS)评分=70分以及接受HFSRT与显著减少的生存期相关(P值分别为0.019、0.017和0.007)。与SRT和IT治疗间隔>7天(n=10)相比,治疗间隔≤7天(n=90)与更长的OS相关(经倾向性评分调整后,P=0.008)。联合治疗耐受性良好。在放射性坏死方面,接受SRT+IT的患者与单独SRT的患者无显著差异。SRT和IT的治疗间隔对毒性发生率无影响。结论 SRT+IT是一种安全的联合治疗方法,与单独SRT相比,具有更长的i LPFS。

关键词：立体定向放疗回顾性研究脑转移倾向性评分临床肿瘤学免疫疗法放射治疗

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