bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engineering microbes for 1,3‐propanediol production
Authors: Du Ruotong , Ling Hongzhi , Cheng Keke 
Published: August 2024

Abstract1,3‐Propanediol (1,3‐PDO) has multiple practical applications, for example as an antifreeze and protective agent and as a monomer of partially renewable polyester and polyurethane. The main method for 1,3‐PDO production is currently microbial fermentation. Bio‐based 1,3‐PDO can use renewable materials as substrates, and the process is mild and environmentally friendly.Genetic engineering of microorganisms is crucial to achieve substrate diversity, reduce byproducts to decrease production costs, and facilitate the downstream processing of 1,3‐PDO. This paper reviews the metabolic engineering of 1,3‐PDO in natural and non‐natural producers. In particular, it discusses current progress using non‐natural synthetic pathways to obtain 1,3‐propanediol.Finally, strategies such as integrated production with other high‐value‐added products are proposed for successful commercialization.
Enhancing the Classification of Congenital Heart Defects for Outcome Association Studies in Birth Defects Registries
Authors: Stephens Sara B. , Benjamin Renata H. , Lopez Keila N. , Anderson Brett R. , Lin Angela E. , Shumate Charles J. , Nembhard Wendy N. , Morris Shaine A. , Agopian A. J. 
Published: August 2024

ABSTRACTIntroductionTraditional strategies for grouping congenital heart defects (CHDs) using birth defect registry data do not adequately address differences in expected clinical consequences between different combinations of CHDs. We report a lesion‐specific classification system for birth defect registry–based outcome studies.MethodsFor Core Cardiac Lesion Outcome Classifications (C‐CLOC) groups, common CHDs expected to have reasonable clinical homogeneity were defined. Criteria based on combinations of Centers for Disease and Control‐modified British Pediatric Association (BPA) codes were defined for each C‐CLOC group. To demonstrate proof of concept and retention of reasonable case counts within C‐CLOC groups, Texas Birth Defect Registry data (1999–2017 deliveries) were used to compare case counts and neonatal mortality between traditional vs. C‐CLOC classification approaches.ResultsC‐CLOC defined 59 CHD groups among 62,262 infants with CHDs. Classifying cases into the single, mutually exclusive C‐CLOC group reflecting the highest complexity CHD present reduced case counts among lower complexity lesions (e.g., 86.5% of cases with a common atrium BPA code were reclassified to a higher complexity group for a co‐occurring CHD). As expected, C‐CLOC groups had retained larger sample sizes (i.e., representing presumably better‐powered analytic groups) compared to cases with only one CHD code and no occurring CHDs.DiscussionThis new CHD classification system for investigators using birth defect registry data, C‐CLOC, is expected to balance clinical outcome homogeneity in analytic groups while maintaining sufficiently large case counts within categories, thus improving power for CHD‐specific outcome association comparisons. Future outcome studies utilizing C‐CLOC‐based classifications are planned.
Innovative fixed bed bioreactor platform: Enabling linearly scalable adherent cell biomanufacturing with real‐time biomass prediction from nutrient consumption
Authors: Goral Vasiliy N. , Hong Yulong , Scibek Jeffery J. , Sun Yujian , Romeo Lori E. , Rao Abhijit , Manning Daniel , Zhou Yue , Schultes Joel A. , Tjong Vinalia , Pikula Dragan , Krebs Kathleen A. , Ferrie Ann M. , Kramel Stefan , Weber Jennifer L. , Upton Todd M. , Fang Ye , Melkoumian Zara 
Published: August 2024

AbstractScalable single‐use adherent cell‐based biomanufacturing platforms are essential for unlocking the full potential of cell and gene therapies. The primary objective of this study is to design and develop a novel fixed bed bioreactor platform tailored specifically for scaling up adherent cell culture. The bioreactor comprises a packed bed of vertically stacked woven polyethylene terephthalate mesh discs, sandwiched between two‐fluid guide plates. Leveraging computational fluid dynamics modeling, we optimized bioreactor design to achieve uniform flow with minimal shear stress. Residence time distribution measurements demonstrated excellent flow uniformity with plug flow characteristics. Periodic media sampling coupled with offline analysis revealed minimal gradients of crucial metabolites (glucose, glutamine, lactate, and ammonia) across the bioreactor during cell growth. Furthermore, the bioreactor platform demonstrated high performance in automated cell harvesting, with ≈96% efficiency and ≈98% viability. It also exhibited linear scalability in both operational parameters and performance for cell culture and adeno‐associated virus vector production. We developed mathematical models based on oxygen uptake rates to accurately predict cell growth curves and estimate biomass in real‐time. This study demonstrates the effectiveness of the developed fixed‐bed bioreactor platform in enabling scalable adherent cell‐based biomanufacturing with high productivity and process control.
Parallel metabolic pathway engineering for aerobic 1,2‐propanediol production in Escherichia coli
Authors: Nonaka Daisuke , Hirata Yuuki , Kishida Mayumi , Mori Ayana , Fujiwara Ryosuke , Kondo Akihiko , Mori Yutaro , Noda Shuhei , Tanaka Tsutomu 
Published: August 2024

AbstractThe demand for the essential commodity chemical 1,2‐propanediol (1,2‐PDO) is on the rise, as its microbial production has emerged as a promising method for a sustainable chemical supply. However, the reliance of 1,2‐PDO production in Escherichia coli on anaerobic conditions, as enhancing cell growth to augment precursor availability remains a substantial challenge. This study presents glucose‐based aerobic production of 1,2‐PDO, with xylose utilization facilitating cell growth. An engineered strain was constructed capable of exclusively producing 1,2‐PDO from glucose while utilizing xylose to support cell growth. This was accomplished by deleting the gloA, eno, eda, sdaA, sdaB, and tdcG genes for 1,2‐PDO production from glucose and introducing the Weimberg pathway for cell growth using xylose. Enhanced 1,2‐PDO production was achieved via yagF overexpression and disruption of the ghrA gene involved in the 1,2‐PDO‐competing pathway. The resultant strain, PD72, produced 2.48 ± 0.15 g L−1 1,2‐PDO with a 0.27 ± 0.02 g g−1‐glucose yield after 72 h cultivation. Overall, this study demonstrates aerobic 1,2‐PDO synthesis through the isolation of the 1,2‐PDO synthetic pathway from the tricarboxylic acid cycle.
Aggregated Pattern Classification Method for improving neural disorder stage detection
Authors: Anjum Mohd , Shahab Sana , Ahmad Shabir , Dhahbi Sami , Whangbo Taegkeun 
Published: August 2024

AbstractBackgroundNeurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmental stage, severity, and nervous system effects has limitations. Leveraging artificial intelligence (AI) and machine learning (ML) for pattern recognition provides a potent solution to address these challenges. Therefore, this study focuses on proposing an innovative approach—the Aggregated Pattern Classification Method (APCM)—for precise identification of neural disorder stages.MethodThe APCM was introduced to address prevalent issues in neural disorder detection, such as overfitting, robustness, and interoperability. This method utilizes aggregative patterns and classification learning functions to mitigate these challenges and enhance overall recognition accuracy, even in imbalanced data. The analysis involves neural images using observations from healthy individuals as a reference. Action response patterns from diverse inputs are mapped to identify similar features, establishing the disorder ratio. The stages are correlated based on available responses and associated neural data, with a preference for classification learning. This classification necessitates image and labeled data to prevent additional flaws in pattern recognition. Recognition and classification occur through multiple iterations, incorporating similar and diverse neural features. The learning process is finely tuned for minute classifications using labeled and unlabeled input data.ResultsThe proposed APCM demonstrates notable achievements, with high pattern recognition (15.03%) and controlled classification errors (CEs) (10.61% less). The method effectively addresses overfitting, robustness, and interoperability issues, showcasing its potential as a powerful tool for detecting neural disorders at different stages. The ability to handle imbalanced data contributes to the overall success of the algorithm.ConclusionThe APCM emerges as a promising and effective approach for identifying precise neural disorder stages. By leveraging AI and ML, the method successfully resolves key challenges in pattern recognition. The high pattern recognition and reduced CEs underscore the method's potential for clinical applications. However, it is essential to acknowledge the reliance on high‐quality neural image data, which may limit the generalizability of the approach. The proposed method allows future research to refine further and enhance its interpretability, providing valuable insights into neural disorder progression and underlying biological mechanisms.
Exploring the Effect of Active Components in Oil Tree Peony Seed Meal on Swine Disease Resistance and its Potential Mechanisms Based on Network Pharmacology and Molecular Docking
Authors: Yang Xu , Xue Xian , He Yinglong , Song Peng , Guo Lili , Hou Xiaogai 
Published: August 2024

AbstractThis study aims to explore the feasibility of using network pharmacology and molecular docking technology to predict the effects of active components from oil tree peony seed meal (PSM) on swine diseases. Ten active components of PSM were screened Screening through literature search and network pharmacology standards, including Betulinic acid, Quercetin, Kaempferol, Luteolin, Isorhamnetin, Hydroxygenkwanin, Hederagenin, Benzoyl Paeoniflorin, Albiflorin, Paeoniflorin. Ten types of swine diseases were selected, including African Swine Fever, Aftosa, Swine Vesicular Disease, Transmissible Gastroenteritis, Swine Streptococcal Infection, Blue Aural Disease, Swine Infectious Atrophic Rhinitis, Swine Influenza, Swine Erysipelas, Swine Epidemic Encephalitis. The results showed that the average number of cross genes between the potential target genes of PSM active components and each swine disease target gene accounted for 7.64 % of the total number of swine disease target genes. The GO enrichment analyses showed that putative targets exist in endosomes, lysosomes, cell membranes, nerves, growth factor activity, receptor tyrosine kinase binding, enzyme binding, growth factor binding, transcription coactivator binding, oxidoreductase activity, prostaglandin E receptor activity and insulin receptor substrate binding. The KEGG enrichment analysis results showed that these putative genes were involved in various cancer progression pathways, signaling pathways, and hormone regulatory pathways. A total of 8 core targets were obtained through protein‐protein interaction networks analysis, including Protein Kinase CAMP‐Activated Catalytic Subunit Alpha (PRKACA), Non‐Receptor Tyrosine Kinase (SRC), Mitogen‐Activated Protein Kinase 1 (MAPK1), E1A Binding Protein P300 (EP300), Hypoxia Inducible Factor 1 Subunit Alpha (HIF1A), Phosphatidylinositol‐4,5‐Bisphosphate 3‐Kinase Catalytic Subunit Beta (PIK3CB), C‐X‐C chemokine receptor type 4 (CXCR4) and Estrogen Receptor 2 (ESR2). The HIF‐1 signaling pathway was found to be associated with all 10 selected swine diseases. The PD‐L1 expression, and PD‐1 checkpoint pathway in cancer, and thyroid hormone signaling pathway were not only enriches the core target with a quantity of 7, but also associated with 9 Swine diseases. In addition, the molecular docking results indicate that the core ingredients have strong affinity with hub genes. The research suggests that the active components of PSM may intervene in swine diseases through multiple components, targets, and pathways.
Novel Aminocoumarin‐Based Schiff Bases: High Antifungal Activity in Agriculture
Authors: Zhang Xin , Gao Ming , Dong Yajie , Pan Le , Zhai Manjun , Jin Lu 
Published: August 2024

AbstractStructural modification is an effective way to improve the antifungal activity of natural products and has been widely used in the development of novel fungicides. In this work, a series of aminocoumarin‐based Schiff bases were synthesized and characterized by 1H‐NMR, 13C NMR and HR‐MS spectra. The in vitro inhibition activity of all compounds was tested against four phytopathogenic fungi (Alternaria solani, Fusarium oxysporum, Botrytis cinerea, and Alternaria alternata) using the mycelial growth rate method. The results showed that most of the target compounds exhibited significant antifungal activities. In particular, compounds 5b, 5c, 5d, 5h, 5n, 7c, 7n, and 7p exhibited more effective antifungal activity than commercially available fungicides, chlorothalonil and azoxystrobin. The structure‐activity relationship revealed that the electron‐withdrawing groups with more electronegativity introduced at the C‐3 position were effective in improving the inhibitory activity and that halogenated benzaldehydes would be necessary in the preparation of Schiff bases. The compound 5n against Fusarium oxysporum (EC50=8.73 μg/mL) and the compound 7p against Alternaria alternata (EC50=26.25 μg/mL) were much better than the positive controls (chlorothalonil and azoxystrobin). Therefore, compounds 5n and 7p could serve as promising lead compounds for the development of novel broad‐spectrum fungicides, which could be useful for applications in the agriculture.
Two New Phenylpropanoids and a Polyphenol with Anti‐Cervical Cancer Activity from Smilax china L.
Authors: Hu Li‐Juan , Ye Xian‐Sheng , Lin Kuan , Gao Jie , Liu Wei , Yang You‐Hua , Shu Xi‐Ji , Yang De‐Sen , Gan Guo‐Ping 
Published: August 2024

AbstractTwo novel phenylpropanoids (compounds 1 and 2) and 11 known compounds were isolated from Smilax china L. Their structures were determined by NMR (1D and 2D) and high‐resolution electrospray ionization mass spectrometry. Further, the cytotoxic activity of all the isolated compounds against HeLa, 4T1, and U251 tumor cells was evaluated using the cell counting kit‐8 assay, revealing that compound 13 showed significant cytotoxicity toward HeLa cells. Further investigations explored the impact of compound 13 on the mitochondrial membrane potential, concentration of reactive oxygen species, wound‐healing distance, and cell cycle of HeLa cells. Notably, compound 13 significantly decreased mitochondrial membrane potential, suppressed cell migration, and increased intracellular reactive oxygen species levels in HeLa cells. Furthermore, compound 13 inhibited HeLa cell‐cycle progression in the S phase. These findings indicate that compound 13 is a potential drug lead for the treatment of cervical cancer.
No time to wait in cardiogenic shock!
Authors: Rab Tanveer 
Published: August 2024

Key points
AMI (acute myocardial infarction) cardiogenic shock patients should be transferred immediately to an mechanical circulatory support (MCS) center.
Transfer delays for MCS placement is associated with worse outcomes.
“Hub and spoke model” for transfer of AMI cardiogenic shock (AMICS) patients to dedicated Shock care centers with advanced MCS should be implemented.
The Promotion of Ce‐Based Solid Solution‐Anchored PdRh Bimetallic Alloy by Co for Three‐Way Catalysis
Authors: Jia Lingxi , Zhang Lingling , Wang Huilin , Wang Xiao , Song Shuyan , Zhang Hongjie 
Published: August 2024

AbstractThree‐way catalysts (TWC) have been extensively studied and practically applied as a promising approach to mitigate vehicular exhaust emissions. However, the current TWC still suffer from issues such as the poor low‐temperature activity and stability. In this paper, the PdRh‐CeZrCo7 catalyst was synthesized by modifying CeZr solid solution with cobalt (Co) doping and PdRh bimetallic alloy loading. This catalyst exhibits superior TWC performance with T50 (temperature required to achieve a 50 % conversion rate) for CO, NO, and C3H6 at 172 °C, 175 °C, and 169 °C, respectively, and maintains excellent catalytic performance after 600 minutes of continuous TWC reaction at elevated temperatures. Experimental and mechanistic studies indicate that the doping of Co adjusts the electronic state of the support, exposes more oxygen vacancies, promotes the transition of the precious metal to the lower state, and then improves catalytic activity and stability for the TWC reaction. This work offers a viable strategy for the synergistic modulation of noble metals and composite oxide supports within the realm of TWC reactions, thereby significantly reducing environmental pollution associated with energy utilization.
Gender Differences in Teamwork and Leadership within Virtual Engineering Laboratories
Authors: Schade Marcel , Terkowsky Claudius , Boettcher Konrad , Inerle Stefan , Kaufhold Nils , Herbrandt Swetlana , Sritharan Rajeenthan 
Published: August 2024

AbstractTo adapt to changes in digital transformation and related Learning and Working 4.0, laboratories in engineering education must leap forward and employ well‐thought‐out pedagogical designs. This includes digital laboratories that in return change social dynamics and interaction patterns of students. This contribution takes the first step of examining gender‐specific teamwork and leadership of groups conducting a digital laboratory in fluid mechanics. Self and external evaluation of perceived teamwork of team members (TMs) and leaders (TLs) was analyzed. Furthermore, possibilities for improvements were evaluated. A mixed‐methods analysis was performed with respect to gender and role to assess whether differences occur. Conclusions show considerable homogeneity between genders and roles and identify communication as most important point of improvement.
Nonlinear dynamic process monitoring based on latent mapping embedding deep neural networks
Authors: Yu Zhenhua , Wang Wenjing , Wang Xueting , Jiang Qingchao , Wang Guan 
Published: August 2024

AbstractIn industrial processes, complex nonlinearity and dynamics generally exist, making it challenging to achieve good results using conventional process monitoring methods. In this paper, a latent mapping embedding neural network method (LMNN) is proposed for efficient monitoring of nonlinear dynamic processes. First, a deep neural network (DNN) is employed to acquire features of state variables from nonlinear process data and expand them along with the input to a new feature subspace. Second, a latent mapping (LM) method is used to map the high‐dimensional feature subspace to a low‐dimensional subspace that includes the most beneficial time series information. Then the entire neural network and regression parameters are obtained through an end‐to‐end learning manner, through which the nonlinearity and process dynamics are well characterized. Subsequently, prediction error‐based residual is generated and the monitoring model is established. The performance of the proposed method is verified through a simulation of penicillin production process and an actual fermentation process of penicillin. Comparisons with state‐of‐the‐art methods are carried out, and results validate the effectiveness and superiority of the proposed method.
Ultrathin PdAu Nanowires with High Alloying Degree for the Direct Oxidation of Methane to C1 Oxygenates
Authors: Tan Linhui , Shi Yi , Xu Yueshan , Zhang Xue , Wu Daoxiong , Wang Zhitong , Xiao Juanxiu , Wen Huan , Li Jing , Tian Xinlong , Deng Peilin 
Published: August 2024

Comprehensive SummaryThe direct oxidation of methane (CH4) into high‐valued C1 oxygenates production has garnered increased attention in effectively using vast CH4 and alleviating the global energy crisis. However, due to the high cleavage energy of C—H bond and low polarity of CH4 molecule, it is difficult to activate the first C—H bond. Furthermore, C1 oxygenates are readily inclined to be oxidized to CO2, because their weaker C—H bond comparing with CH4 molecule, resulting in poor selectivity. Herein, we designed ultrathin PdxAuy alloy NWs supported on ZSM‐5 (Z‐5) to investigate the direct oxidation of CH4 to high value‐added oxygenate under mild conditions. By precisely adjusting the molar ratio of Pd/Au and alloying degree, Pd9Au1NWs/Z‐5 showed an excellent yield of 11.57 mmol·g–l·h–1 and the outstanding selectivity of 95.1% for C1 oxygenates (CH3OH, CH3OOH and HCOOH). The in‐situ spectroscopic and mechanism analysis proved that the enhanced catalytic performance of Pd9Au1NWs/Z‐5 was ascribed to the stable one‐dimensional nanostructure and the strong synergy effect with high alloying PdAu, which could increase the adsorption capacity of CH4 molecules on Pd atoms to promote the CH4 conversion. This work offers valuable insights into the design concept of high‐efficient catalysts and the structure‐activity relationship for the direct oxidation of CH4.
Harmonic Scale Factors of Fundamental Transitions for Dispersion‐corrected Quantum Chemical Methods
Authors: Tikhonov Denis S. , Gordiy Igor , Iakovlev Danila A. , Gorislav Alisa A. , Kalinin Mikhail A. , Nikolenko Sergei A. , Malaskeevich Ksenia M. , Yureva Karina , Matsokin Nikita A. , Schnell Melanie 
Published: August 2024

AbstractThis work provides a procedure and database for obtaining the vibrational frequency scale factors that align quantum chemically computed harmonic frequencies with experimental vibrational spectroscopic data. The database comprises 441 molecules of various sizes, from diatomics to the buckminsterfullerene C60. We provide scale factors for 27 dispersion‐corrected methods, 24 of which are DF‐Dn/B with DF=BLYP, PBE, B3LYP, PBE0, Dn=D3(BJ), D4, and B=6‐31G, def2‐SVP, def2‐TZVP, and three of them are the 3c‐family composite methods (HF‐3c, PBEh‐3c, and r2SCAN‐3c). The two scale factors are derived for each method: the absolute scaling, minimizing the absolute deviation of the scaled harmonic frequency from the experimental value, and the relative scaling, which minimizes an analogous relative deviation. The absolute type of scaling is recommended for frequencies above 2000 cm−1, while the relative scaling is optimal for frequencies below 2000 cm−1.
Flakes and Nanoparticles from Waste Ru‐Plated Fashion Items through Food Waste by‐Products
Authors: Cecchi Teresa , Gao Zhaojing , Santato Clara 
Published: August 2024

AbstractRuthenium is relevant for a broad range of applications, including catalysis and electronics. Like other metals of the platinum group, ruthenium stands out as one of the rarest elements in the Earth's crust. The demand for Ru from the industry is putting pressure on its availability. Hence, its recovery from secondary sources is imperative. Fashion solid residues of the plating industry are an important waste stream for Ru. Within this context, we propose a novel approach to Ru recovery for its safe, sustainable, and economically affordable upcycling. The approach is based on peeling from waste metal wires by a green oxidizing agent, H2O2, in an environment acidic by lactic acid, a by‐product of the food industry. Peeled flakes were characterized by scanning electron microscopy, energy dispersive spectroscopy, X‐ray photoelectron spectroscopy, and atomic force microscopy for their structure and (surface) chemical composition and bonding. Inductively Coupled Plasma Optical Emission Spectroscopy shows the ultra‐low concentration of noble metals in the leachate, thereby suggesting their quantitative recovery in their metallic state. Further, we observed the colloidal nature of the washing water of the peeled flakes. Therefore, we hypothesized the presence of nanoparticles in the washing water and went for their characterization.