bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of a novel microbial abundance prognostic risk (MAPR) model for predicting prognosis in CRC - based on bioinformatics
Authors: Chen Li , Lin Jie , Zhuang Wan-Li , Peng Shi-Rui , Li Xin-Biao , Li Dong-Liang , Xie Long-ke 
Published: June 2023

Abstract
Background Previous studies have demonstrated the significant role of the microbiome in the prognosis of colorectal cancer (CRC) patients. However, few studies have utilized bioinformatics to analyze the prognostic value of the microbiome in CRC. In this study, we constructed a CRC microbial abundance prognostic risk (MAPR) model and evaluated its prognostic value.
Methods The TCGA CRC microbiome data (TCGA-CRC-microbiome) was downloaded from the cBioPortal website. Univariate, LASSO, and multivariate Cox regression analyses were performed to investigate the relationship between CRC microbial abundance and survival. The MAPR model was constructed based on the above analyses. The predictive ability of the MAPR model was evaluated using Kaplan-Meier (KM) survival curves, receiver operating characteristic (ROC) curves, independent prognostic analysis, and nomogram models.
Results Using 11 microbial genera which exhibited adverse overall survival (OS) in CRC patients from overall 1406 microbes in the TCGA-CRC microbiome dataset to construct a MAPR model.
This model was constructed and assessed for prognostic value using different survival endpoints. The results indicated that the high-risk group had shorter OS, progression-free interval (PFI), disease-specific survival (DSS), and disease-free interval (DFI). High-risk status served as an independent adverse prognostic factor, with greater prognostic value than other clinical indicators. Compared to the MAPR-unincorporated CRC nomogram, the four nomograms incorporating MAPR significantly improved the predictive ability.
Conclusion The successful establishment of CRC's MAPR and its unique prognostic value provide a novel perspective for further investigations into the prognostic mechanisms of CRC patients.
The transcriptome profiling of the Sistani cattle and its crossbred with Montbeliarde breed
Authors: Esfeden Batol Asghari , Dashab Gholam Reza , Banabazi Mohammad Hossein , Rokouei Mohammad 
Published: June 2023

Abstract
Transcriptome study of the desired crossbreed and comparing it with the pure parental population is a method for evaluating and selecting cross with appropriate products, yet disease resistance, high tolerance to environmental stresses, and compatibility with the climate of the breeding tract. RNA-Sequencing (RNA-seq) technology was employed to investigate the effect of crossbreeding by the Montbeliarde cattle on the “Sistani cattle” transcriptome. Blood samples were collected from 60 cows (30 pure and 30 crossbreeds). The samples were shared together and two samples were taken from each group for sequencing (4 samples). Total RNA was extracted in the Media Teb Gene Laboratory of Iran. The mRNA selection, library preparation, and sequencing were performed at BGI Shenzhen, China on an Illumina HiSeq 2500 sequencer. After assembling the transcripts with the bovine reference genome, Cuffdiff was used to detect differential gene expression in purebred and its crossbred. In total, 45 significantly differentially expressed genes were identified (false discovery rate q < 0.05) between purebred Sistani and “Sistani×Montbeliarde” crossbreed. These genes are reported to have a role in immune response, calving, fertility, and resistance to mastitis. Besides, they may have a role in different levels of heat tolerance and disease resistance. Therefore, Sistani×Montbeliarde crossbred might be suitable for the climatic conditions of the Sistan region in Iran.
Trade-offs in the substrate mix optimization of biogas plants considering biomethane market conditions
Authors: Güsewell Joshua , Rousta Milad , Eltrop Ludger 
Published: June 2023

Abstract
Background:
New regulations and market conditions affect the profitability of biomethane upgrading as a repowering option for existing biogas plants following on-site CHP utilization. These conditions present challenges like higher sustainability requirements and opportunities in new markets and higher revenues. Finding the optimal substrate mix and profitable solutions across multiple market conditions, plant-specific process constraints, and substrate properties requires optimization methods like linear programming (LP).
Methods:
We developed a substrate mix optimization model within an assessment framework for repowering existing biogas plants (BGPs). By modeling different variations of the German biomethane markets and conducting a sensitivity analysis for various BGPs, we assessed changes in the substrate mix, GHG emissions, contribution margins, and constraint parameters to derive conclusions for operators and future framework design.
Results:
Integrating market revenues and constraints into the substrate mix optimization can increase contribution margins by 12–55%. The gains increase by considering multiple markets simultaneously but are limited to a few BGPs. The plant-specific LP solution space and setting of the benchmark are decisive. The former limits the potential of high substrate-specific contribution margins, which has a significantly higher impact than the relation between plant-specific characteristics and process constraints. The advanced fuel market is the lead market for biomethane, incentivizing low yield and GHG emission substrates, decreasing gas production and GHG emissions but increasing LCOE and partially CO2 abatement costs.
Conclusions:
The key to improving profitability is a large LP solution space to supply an increasing biomethane demand while fulfilling new requirements. Increasing market options, substrate availability, and digestion system capacity achieve this. Another way is by reducing normative requirements such as a maize cap or double counting of advanced fuels and favoring high but uniform GHG requirements and low GHG emission substrates. Operators can prepare robustly for the future substrate mix by adding digester volume and pre-treatment tech, ensuring long-term and diverse substrate availability, and sales contracts with flexible components. Although current market conditions improve GHG emissions, they do not necessarily increase manure usage when other options, such as straw, are viable. Other regulatory support systems will be required to do so.
A dual indexed approach to small RNA sequencing library preparation for PRO-seq
Authors: Layden Hillary M. , Jones Angela L. , Ellis Jacob D. , Hiebert Scott W. 
Published: June 2023

Abstract
Advances in next generation sequencing (NGS) technologies have vastly increased the number of samples that can be sequenced together and reduced the cost per sample. To fully utilize the increased capacity of standard sequencers, samples must be multiplexed. Sample multiplexing allows libraries to be pooled and sequenced together on a single sequencing run. Multiplexing requires libraries that have been prepared with a unique 6-12 bp sequence (index). The most efficient and cost-effective sequencing platforms rely on paired end sequencing methodologies to improve multiplexing efficiency. While libraries with a single index can be sequenced on paired end sequencers they reduce the efficiency of demultiplexing and increase the sequencing cost due to index mis-assignment. However, some specialized library preparation protocols, like the TruSeq Small RNA protocol, that rely on custom sequencing adapters have not been updated by Illumnia to include a second index. Commercially available kits for creating small RNA paired end libraries are expensive and do not provide the level of transparency required to adapt the kits to custom protocols. Here, we provide a dual-indexed approach to small RNA library preparatio that reduces the cost per library by nearly half (compared to the NEXTFLEX v3 kit) and includes all sequences for the oligonucleotides required. While this workflow was developed for PRO-seq libraries, deviations from the original TruSeq Small RNA library preparation protocol are denoted and alternate reagents are provided to facilitate adaptation of existing protocols.
Establishment of an efficient expression and regulation system in Streptomyces for economical and high-level production of the natural blue pigment indigoidine
Authors: Zhao Ming , Zhang Xiu-Shan , Xiong Liang-Bin , Liu Kun , Li Xiang-Fei , Liu Yan , Wang Feng-Qing 
Published: June 2023

Abstract
Background Indigoidine, as a kind of natural blue pigment, is widely used in textiles, food, and pharmaceutical and mainly synthesized from L-glutamine via a condensation reaction by indigoidine synthetases, most of which originated from Streptomyces species. Although Streptomyces possesses strong secondary metabolism, the switches of which from the primary metabolism are complex and thus a challenge to holistically optimize their productivities. Therefore, most of the researchers choose to over-express indigoidine synthetases in the heterologous host to achieve high-level production of indigoidine.
Results Considering the advantages of low-cost culture medium and simple culture conditions during the large-scale culture of Streptomyces, here, an updated regulation system derived from Streptomyces self-sustaining system, constructed in our previous study, was established for the highly efficient production of indigoidine in Streptomyces lividans TK24. The updated system was constructed via promoter mining and σhrdB expression optimization, and this system was applied to precisely and continuously regulate the expression of indigoidine synthetase IndC derived from Streptomyces albus J1704. Finally, the engineered strain was cultured in the cheap industrial medium, and 14.3 g/L and 46.27 g/L indigoidine could be achieved in flask and 4 L fermentor, respectively, reaching the highest level of microbial synthesis of indigoidine.
Conclusions This study will lay a foundation for the industrial application of Streptomyces cell factories to produce indigoidine.
Studying Data Loss, Nonlinearity, and Modulation Effects in Drone Swarms with Artificial Intelligence
Authors: Kharchenko Volodymyr , Grekhov Andrii , Kondratiuk Vasyl 
Published: June 2023

Abstract
Artificial Intelligence (AI) of drone swarms depends on reliable communications. The parallelism and distributed characteristics of swarm intelligence provide self-adapting and reliable capabilities. This article is devoted to the calculation of packet losses and the impact of traffic parameters on the data exchange in swarms. Original swarm models were created with the help of MATLAB and NetCracker packages. Dependences of data packet losses on the transaction size are calculated for different drone number in a swarm using NetCracker software. Data traffic with different parameters and statistical distribution laws was considered. The effect of different distances to drones on the base station workload has been simulated. Data transmission in a swarm was studied using MATLAB software depending on the signal-to-noise ratio, nonlinearity levels of base station amplifier, signal modulation types, base station antenna diameters, and signal phase offsets. The data obtained allows foresee the operation of drone communication channels in swarms.
A novel Chemokine-related LncRNA signature predicts the prognosis and immunotherapy response in lung adenocarcinoma patients
Authors: Zhu Kang , Xiong Linmin , Xiong Jianwen , Zhu Ying , Liang Yonggang , Yu Dongliang 
Published: June 2023

AbstractBackground Chemokines and their receptors are widely reported to be closely associated with cancer progression, especially in the immune microenvironment. However, studies on chemokine-related lncRNAs (CRLs) in lung adenocarcinoma (LUAD) have not been reported. This study aimed to construct a prognostic model based on CRL signature to explore their relationship with prognosis and immune infiltration in LUAD. Samples and methods: We first obtained RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) database, then identified prognostic CRLs by co-expression analysis and univariate Cox analysis, and constructed a prognostic model based on CRLs to predict the prognosis of LUAD patients using multifactorial Cox analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Kaplan-Meier (K-M) survival curve analysis and receiver operating characteristic (ROC) curve analysis were used to assess the prognostic ability of the model. Finally, we also explored the relationship of the risk model with immune checkpoint gene expression, tumor mutation burden, immunotherapy scores, and drug sensitivity. Results We constructed a risk model based on seven CRLs (AL391261.1, AC034223.2, SH3BP5-AS1, LY86-AS1, AC104971.3, LINC01843, AL157388.1) that were significantly associated with prognosis. Patients with LUAD were divided into high-risk and low-risk groups, using the median value of the risk score as the cutoff. K-M survival analysis showed that the higher the risk score, the worse the prognosis. the area under the ROC curve (AUC) was 0.796, and multi-factor Cox analysis showed that the risk score was an independent risk factor affecting the prognosis of LUAD. In addition, our risk model played a key role in predicting immune checkpoint gene expression, tumor mutation burden, immunotherapy score, and drug sensitivity in LUAD patients. Conclusion We have identified a new CRL signature that has clinical value in predicting the prognosis of LUAD patients and provides a theoretical basis for the development of immunotherapy regimens for LUAD.
Differentiating Intracranial Solitary Fibrous Tumors from Atypical Meningiomas Using Conventional MRI: A Comparison of Radiomics Models Versus Assessment from Radiologists, and Exploration of Correlation with Collagen Volume Fraction.
Authors: Zhang Hua , Li Xiaoling , Xing Zhen , Kang Jie , Song Yang , Li JianYe , Cao Dairong , Wang XingFu 
Published: June 2023

Abstract
Purpose:
To investigate the performance of qualitative, quantitative assessment and radiomics models between solitary fibrous tumors (SFTs) and atypical meningiomas (ATMs), and the relationship between imaging parameters and collagen volume fraction (CVF).
Methods:
This study included 132 patients with ATMs and 50 patients with SFTs who underwent MRI. Qualitative assessment was performed using a five-point-scale visual scoring on T1WI and T2WI. Quantitative assessment was conducted by dividing the signal values of tumors by those of centrum semioval or thalamus. Radiomics models were established on T1WI, T2WI, and T1&T2WI. Spearman correlation was used to determine the correlation between CVF and imaging features.
Results
The AUCs and cutoff values of qualitative parameters were 0.913, > 3 on T1WI, and 0.763, ≤ 4 on T2WI in testing set. The AUCs were 0.854, 0.877, 0.942 for T1WI, T2WI and T1&T2WI models in testing set. There were significant differences between radiomics models and qualitative and quantitative assessment in training set (P < 0.05), while there were no significant differences in testing set. Among SFTs, negative correlation was obtained between CVF and qualitative and quantitative parameters on T1WI and T2WI.
Conclusion
The hyperintensity on T1WI and hypointensity on T2WI were valuable for discriminating SFTs and ATMs. The performance of radiomics models was superior to qualitative and quantitative parameters. The imaging parameters on T1WI and T2WI were negatively correlated with CVF among SFTs.
Phase I Trial Evaluating Locoregionally-delivered IL13Rα2-targeting CAR T Cells in High-Grade Glioma
Authors: Brown Christine , Hibbard Jonathan , Alizadeh Darya , Blanchard M. , Natri Heini , Wang Dongrui , Ostberg Julie , Aguilar Brenda , Wagner Jamie , Paul Jinny , Starr Renate , Filippov Aleksandr , Chaudhry Ammar , Ressler Julie , Kilpatrick Julie , Myers-McNamara Paige , Chen Mike , Wang Leo , Rockne Russell , Georges Joseph , Portnow Jana , Barish Michael , D'Apuzzo Massimo , Banovich Nicholas , Forman Stephen , Badie Behnam 
Published: June 2023

Abstract
Chimeric antigen receptor (CAR) T cell therapy is at early stages of clinical testing for solid tumors. We report here a completed phase I trial (NCT02208362) evaluating locoregional delivery of IL13Rα2-targeted CAR T cells in 65 patients with recurrent high-grade glioma, the majority being recurrent glioblastoma (rGBM; 2 + recurrences). Primary endpoints were safety and feasibility, with secondary endpoints measuring therapy-related bioactivity. Weekly intratumoral (ICT) and/or intraventricular (ICV) administration of IL13Rα2-CAR T cells was well-tolerated with clinically manageable adverse events. Stable disease or better was achieved in 50% of patients, with two partial responses, one complete response (CR), and a second CR after additional CAR T cycles off-protocol therapy. Patients with rGBM treated with dual ICT/ICV delivery and an optimized manufacturing process exhibited superior overall median survival of 10.2 months, compared to 6.1 months for other treatment arms. Central nervous system (CNS) increases in inflammatory cytokines, including IFNγ, CXCL9, and CXCL10, were associated with CAR T cell administration and bioactivity. Further, pre-treatment intratumoral CD3 T cell levels were positively associated with survival, indicating an interplay between host immunity and CAR T cells as a determinant of outcomes. These findings advance our understanding of CAR T cell immunotherapy for malignant brain tumors.
Lenvatinib plus PD-1 inhibitors combined with chemotherapy versus lenvatinib plus PD-1 inhibitors for unresectable or recurrent biliary tract cancer
Authors: Zheng Xiang , Jiang Zedong , Shao Zhiwei , Gao Zhenzhen , Zhou Bo , Li Guogang , Zhang Qiyi , Zhang Yuanbiao , Yan Sheng 
Published: June 2023

Abstract
Background
Lenvatinib and programmed cell death-1 (PD-1) inhibitors have emerged as a novel treatment for patients with BTC. This study aimed to compare the efficacy and safety of triple therapy with lenvatinib, PD-1 inhibitors plus chemotherapy (LenP + C) and dual therapy with lenvatinib plus PD-1 inhibitors (LenP) in patients with unresectable or recurrent BTC.
Methods
BTC patients receiving LenP + C or LenP treatment between June 2020 and March 2022 were retrospectively analyzed. The primary outcome was progression-free survival (PFS). The secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS) and safety.
Results
Ninety-eight patients were included in the present study, and they were divided into the LenP + C group (n = 40) and LenP group (n = 58). The median PFS was 8.3 months in the LenP + C group, significantly longer than 4.5 months in the LenP group (HR = 0.471; 95% CI, 0.271–0.817; P = 0.007). Although no difference was found in ORR between the two groups (LenP + C, 42.5% vs. LenP, 27.6%, P = 0.125), the DCR was higher in the LenP + C group than in the LenP group (95.0% vs. 75.9%, P = 0.012). The median OS was comparable between the two groups (13.7 vs. 12.4 months, P = 0.749). Treatment-related adverse events were more frequently observed in the LenP + C group. The incidence of neutropenia (grade ⩾3) was higher in patients receiving triple therapy (15% vs. 2%, P = 0.035).
Conclusions
This study showed that treatment with lenvatinib and PD-1 inhibitors is safe and effective for advanced BTC. The combination of chemotherapy with lenvatinib and PD-1 inhibitors showed improved anti-tumor efficacy compared with lenvatinib and anti-PD-1 therapy, yet with more toxic effects.
Soil water availability affects the vertical distribution of fine roots in poplar short rotation coppice
Authors: Berhongaray Gonzalo , Tripathi Abhishek , Fischer Milan , Orság Matěj , Trnka Mirek , King John 
Published: June 2023

AbstractFine roots (< 2 mm), which play a critical role in water and nutrient uptake, are an important component of the ecosystem carbon cycle and often have higher productivity than above-ground parts. The objective of this study is to investigate the effect of soil water availability on the distribution of fine roots annual production and turnover rate. The study was conducted in a throughfall reduction experiment established in a coppiced plantation at the Czech Republic. The vertical distribution of fine root biomass and fine root production were correlated with soil moisture early in the season. Low soil moisture levels (i.e. 20%) corresponded to a greater proportion of roots at depth. Understanding these responses may be beneficial to enhance carbon input in deeper layers and thus potentially carbon sequestration by manipulating the soil moisture in the topsoil through introducing early phenology understory species into bioenergy or agroforestry setups.
Instantaneous CO2 emission modeling for the Euro 6 start-stop vehicle based on portable emission measurement system and artificial intelligence methods
Authors: Mądziel Maksymilian 
Published: June 2023

Abstract
One of the increasingly common methods to counteract the increased fuel consumption of vehicles is start-stop technology. This paper introduces a methodology which presents the process of measuring and creating a computational model of CO2 emissions using artificial intelligence techniques for a vehicle equipped with start-stop technology. The method requires only measurement data of velocity, acceleration of vehicle and gradient of road to predict the emission of CO2. In this paper, 3 methods of machine learning techniques were analyzed, while the best prediction results are shown by the gradient boosting method. For the developed models, the results were validated using the coefficient of determination, the mean squared error, and based on visual evaluation of residual and instantaneous emission plots and CO2 emission maps. The developed models present a novel methodology and can be used for microscale environmental analysis.
La comunicación de la colección Join Life en tiendas físicas de Zara Barcelona (2022), etiquetas y ficha de producto web
Authors: Regadera González Elisa 
Published: June 2023

La comunicación que las marcas de moda realizan sobre la sostenibilidad está hoy más cuestionada que nunca. La nueva propuesta de directiva de la Comisión Europea -Green Claims Directive-, marcará un antes y un después para muchas compañías, pues pretende alertar sobre diversas prácticas comunicativas que confunden al consumidor, incluyendo las etiquetas: “mostrar una etiqueta sostenible que no esté basada en una certificación o no esté establecida por autoridades públicas, constituye una práctica de competencia desleal en todas las circunstancias”. En este artículo analizaremos la comunicación de la sostenibilidad realizada por Inditex -en concreto, sobre su colección Join Life distinguida como la más sostenible-, tanto en su Política de Sostenibilidad y Hoja de Ruta, como en las nueve tiendas físicas de ZARA Barcelona (2022), precisamente un año antes de que Inditex haya eliminado la etiqueta del mercado. Hemos utilizado el método del Case Study, integrando: análisis de textos (Política de Sostenibilidad y Hoja de Ruta); estudio descriptivo de las tiendas físicas, incluyendo breve entrevista a los empleados; análisis del contenido de las etiquetas de las prendas en tienda; y finalmente,análisis del contenido de la ficha de producto de esas prendas en la web.Aunque se trata de una certificación recién suprimida por Inditex (marzo 2023), pensamos que las conclusiones obtenidas en este estudio pueden contribuir a una mejora en la gestión de la comunicación de la sostenibilidad por parte de las marcas de moda.