bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glucose metabolism‐based signature predicts prognosis and immunotherapy strategies for colon adenocarcinoma
Authors: Bai Zilong , Yan Chunyu , Nie Yuanhua , Zeng Qingnuo , Xu Longwen , Wang Shilong , Chang Dongmin 
Published: November 2023

AbstractBackgroundThe global prevalence and metastasis rates of colon adenocarcinoma (COAD) are high, and therapeutic success is limited. Although previous research has primarily explored changes in gene phenotypes, the incidence rate of COAD remains unchanged. Metabolic reprogramming is a crucial aspect of cancer research and therapy. The present study aims to develop cluster and polygenic risk prediction models for COAD based on glucose metabolism pathways to assess the survival status of patients and potentially identify novel immunotherapy strategies and related therapeutic targets.MethodsCOAD‐specific data (including clinicopathological information and gene expression profiles) were sourced from The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus (GEO) datasets (GSE33113 and GSE39582). Gene sets related to glucose metabolism were obtained from the MSigDB database. The Gene Set Variation Analysis (GSVA) method was utilized to calculate pathway scores for glucose metabolism. The hclust function in R, part of the Pheatmap package, was used to establish a clustering system. The mutation characteristics of identified clusters were assessed via MOVICS software, and differentially expressed genes (DEGs) were filtered using limma software. Signature analysis was performed using the least absolute shrinkage and selection operator (LASSO) method. Survival curves, survival receiver operating characteristic (ROC) curves and multivariate Cox regression were analyzed to assess the efficacy and accuracy of the signature for prognostic prediction. The pRRophetic program was employed to predict drug sensitivity, with data sourced from the Genomics of Drug Sensitivity in Cancer (GDSC) database.ResultsFour COAD subgroups (i.e., C1, C2, C3 and C4) were identified based on glucose metabolism, with the C4 group having higher survival rates. These four clusters were bifurcated into a new Clust2 system (C1 + C2 + C3 and C4). In total, 2175 DEGs were obtained (C1 + C2 + C3 vs. C4), from which 139 prognosis‐related genes were identified. ROC curves predicting 1‐, 3‐ and 5‐year survival based on a signature containing nine genes showed an area under the curve greater than 0.7. Meanwhile, the study also found this feature to be an important predictor of prognosis in COAD and accordingly assessed the risk score, with higher risk scores being associated with a worse prognosis. The high‐risk and low‐risk groups responded differently to immunotherapy and chemotherapeutic agents, and there were differences in functional enrichment pathways.ConclusionsThis unique signature based on glucose metabolism may potentially provide a basis for predicting patient prognosis, biological characteristics and more effective immunotherapy strategies for COAD.
Prediction of 5‐year survival in soft tissue leiomyosarcoma using a machine learning model algorithm
Authors: Kamalapathy Pramod N. , Gonzalez Marcos R. , de Groot Tom M. , Ramkumar Dipak , Raskin Kevin A. , Ashkani‐Esfahani Soheil , Lozano‐Calderón Santiago A. 
Published: November 2023

AbstractBackground and ObjectivesLeiomyosarcoma (LMS) is associated with one of the poorest overall survivals among soft tissue sarcomas. We sought to develop and externally validate a model for 5‐year survival prediction in patients with appendicular or truncal LMS using machine learning algorithms.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was used for development and internal validation of the models; external validation was assessed using our institutional database. Five machine learning algorithms were developed and then tested on our institutional database. Area under the receiver operating characteristic curve (AUC) and Brier score were used to assess model performance.ResultsA total of 2209 patients from the SEER database and 81 patients from our tertiary institution were included. All models had excellent calibration with AUC 0.84−0.85 and Brier score 0.15−0.16. After assessing the performance indicators according to the TRIPOD model, we found that the Elastic‐Net Penalized Logistic Regression outperformed other models. The AUCs of the institutional data were 0.83 (imputed) and 0.85 (complete‐case analysis) with a Brier score of 0.16.ConclusionOur study successfully developed five machine learning algorithms to assess 5‐year survival in patients with LMS. The Elastic‐Net Penalized Logistic Regression retained performance upon external validation with an AUC of 0.85 and Brier score of 0.15.
Statistical investigations into automated spray‐applied stripe coats to complex geometries of floating offshore wind foundations
Authors: Kelm Daniel , Marquardt Tom , Momber Andreas , Sellmeyer Steffen , Irmer Michael 
Published: November 2023

AbstractThe automation of coating processes allows consistent, economical, and ecological applications. In this study, the effects of various surface geometries—steel plates, plates with weld seams, plates with bolts, and plates with welded fillets—on the uniformity of dry film thickness (DFT) after robotic stripe coating applications with an electrostatic spray device are investigated and analyzed with statistical methods. Robot traverse rate, pump pressure, and voltage. Based on analysis of variance studies, the robot traverse rate was identified to be the most influential factor. For plates with weld seams, an optimization study was conducted, resulting in a multiresponse prediction model. The model achieved a DFT within the target range across all measuring points within a 95% confidence interval. At an optimized factor combination (117 mm/s, 0.3 MPa, 61.4 kV), the DFT values ranged between 100 and 142 µm. The findings of this study provide fundamentals for achieving uniform coating distributions on complex geometries and for optimizing process parameters.
Optimal test planning for heterogeneous Wiener processes
Authors: Cheng Ya‐Shan , Peng Chien‐Yu 
Published: November 2023

AbstractDegradation models based on heterogeneous Wiener processes are commonly used to assess information on the lifetime of highly reliable products. An optimal test plan given limited resources is generally obtained using numerical methods for heterogeneous Wiener processes. However, numerical searches for optimal test plans have the disadvantage of being time‐consuming and may provide unclear explanations for the findings. To overcome these difficulties, we derive an explicit expression for decision variables (such as the termination time, number of measurements, and sample size) of ‐ and ‐optimal test plans with cost constraints. The theoretical results not only ensure that the optimal test plan is found, but also provide clear insights into the decision variables affected by model parameters and experimental costs. Some numerical examples are presented to support the efficiency and applicability of the optimal test plans.
Do sectors (still) matter? Exploring similarities and differences between public, private, and non‐profit organizations from an organizational identity perspective
Authors: Nunes Francisco Guilherme , do Nascimento Generosa , Martins Luís Dias 
Published: November 2023

AbstractThis paper uses an organizational identity perspective to investigate similarities and differences between public, private, and nonprofit organizations. The analysis is focused on three interrelated identity domains: the content used by members to define their organizations; the orientation of the organizational identity (individualistic, relational, and collectivistic); the nature of members' attachment to their organizations (identification, neutral identification, ambivalent identification, disidentification). Using a sample of 256 members of organizations belonging to these three sectors we found that: the content used to describe public, private, and nonprofit organizations, although sharing numerous elements, also contains sector‐specific meanings, especially in nonprofit organizations; concerning the organizational identity orientation, private organizations are seen as more individualistic and more relational than public and nonprofit ones, while public organizations score high in the collectivistic orientation; regarding the nature of members' attachment, although members of the three types of organizations exhibit the same levels of organizational identification and neutral identification, nonprofit organizations generate more disidentification and ambivalent identification among their members than public and private ones. Overall, organizational elements revealing operational practices tend to be similar, while those elements representing organizational identity tend to be different.
A newly identified compound activating UCP1 inhibits obesity and its related metabolic disorders
Authors: Onodera Ken , Hasegawa Yutaka , Yokota Nozomi , Tamura Shukuko , Kinno Hirofumi , Takahashi Iwao , Chiba Hiraku , Kojima Hirotatsu , Katagiri Hideki , Nata Koji , Ishigaki Yasushi 
Published: November 2023

AbstractObjectivePromoting thermogenesis in adipose tissue has been a promising strategy against obesity and related metabolic complications. We aimed to identify compounds that promote thermogenesis in adipocytes and to elucidate their functions and roles in metabolism.MethodsTo identify compounds that directly promote thermogenesis from a structurally diverse set of 4800 compounds, we utilized a cell‐based platform for high‐throughput screening that induces uncoupling protein 1 (Ucp1) expression in adipocytes.ResultsWe identified one candidate compound that activates UCP1. Additional characterization of this compound revealed that it induced cellular thermogenesis in adipocytes with negligible cytotoxicity. In a subsequent diet‐induced obesity model, mice treated with this compound exhibited a slower rate of weight gain, improved insulin sensitivity, and increased energy expenditure. Mechanistic studies have revealed that this compound increases mitochondrial biogenesis by elevating maximal respiration, which is partly mediated by the protein kinase A (PKA)‐p38 mitogen‐activated protein kinase (MAPK) signaling pathway. A further comprehensive genetic analysis of adipocytes treated with these compounds identified two novel UCP1‐dependent thermogenic genes, potassium voltage‐gated channel subfamily C member 2 (Kcnc2) and predicted gene 5627 (Gm5627).ConclusionsThe identified compound can serve as a potential therapeutic drug for the treatment of obesity and its related metabolic disorders. Furthermore, our newly clarified thermogenic genes play an important role in UCP1‐dependent thermogenesis in adipocytes.
Electronegativity effect on the ESIPT process of 4′‐N,N‐dimethylamino‐3‐hydroxyflavone (DMA3HF) and its derivatives
Authors: Liu Zhiqiang , Han Ligang , Wang Xiali , Wang Yi , Hou Yingmin 
Published: November 2023

Abstract4′‐N,N‐dimethylamino‐3‐hydroxyflavone (DMA3HF) has antioxidant activity and excited state proton transfer (ESIPT) property. In this study, the influence of electronegativity on the ESIPT process has been studied by DFT/TD‐DFT methods. Except DMA3HF, the substitutes of S and Se have been designed. The analysis of main bond parameters, infrared vibration spectra, and reduced density gradient function shows that the reduction of atomic electronegativity could promote the ESIPT process. Dihedral angle, frontier molecular orbitals and hole‐electron analysis indicate that the twisted intramolecular charge transfer (TICT) process has been enhanced by the decreasing electronegativity. The results show that the decrease of atomic electronegativity is beneficial to TICT and ESIPT processess.
Nonlinear diffusion‐limited two‐dimensional colliding‐plume simulations with very high‐order numerical approximations
Authors: Straka Jerry M. , Williams Paul D. , Kanak Katharine M. 
Published: November 2023

AbstractAtmospheric numerical models play a crucial role in operational weather forecasting, as well as in improving our understanding of atmospheric dynamics via research studies. Maximising their accuracy is of paramount importance. Use of advective flux schemes greater than O7 in atmospheric models is largely undocumented, with no studies considering O3–O17 fluxes with formal accuracy‐preserving high‐order interpolation, pressure gradient/divergence, and subgrid‐scale (SGS) turbulent fluxes. Higher‐order numerical approximations can reduce truncation, amplitude and phase errors, and potentially improve model accuracy and effective resolution. Here, simulations are presented using very‐high‐order O3–O17 fluxes, with/without high‐order O2–O18 Lagrangian interpolations, pressure gradient/divergence approximations, and SGS turbulent fluxes for a two‐dimensional, highly‐viscous (Re ∼ 100) diffusion‐limited, nonlinear colliding‐plumes problem using 25–200 m spatial resolutions. The highest‐order flux schemes coupled with higher‐order interpolations, pressure gradient/divergence and SGS flux approximations produced the best solutions, with higher‐order fluxes and interpolations being most important. Overall solution convergence of order about O1–O2 with mode‐split (fast sound/slow advective waves) O3 Runge–Kutta temporal schemes was negatively impacted by order at most O1 temporal convergence with SGS fluxes, divergence damping, and especially spatial filters, compared to about order O3 convergence with these inactivated. While very‐high‐order schemes were shown to improve solution accuracy, few cost‐effective higher‐order highly‐viscous test problem solutions (higher order vs finer resolution) were found using theoretical floating‐point operations (FPO) with Courant‐Friedrichs‐Lewy (CFL)‐limited or constant stable Courant number‐based time steps. However, employing central processing unit (CPU) time, rather than FPOs, demonstrated there was reduced computational burden using higher‐order approximations. We conclude that O9–O17 flux schemes with or without high‐order (≥O4) interpolations, pressure gradient/divergence approximations, and SGS fluxes can improve atmospheric model solution accuracy, without prohibitive computation costs, compared to O3–O7 flux with O2 interpolations, pressure gradient/divergence approximations, and SGS fluxes.
Quantifying the probability of invasive carp introduction via freshwater diversions: Arrival Assessment
Authors: Rycroft Taylor , Volk Kaitlin , Franceschini René A. Garcia , Montgomery Cheryl , Katzenmeyer Alan 
Published: November 2023

AbstractThe Mississippi River is host to multiple species of invasive carp, including bighead, silver, and black carp, which have been linked to negative ecological impacts upon introduction to a waterbody. Most of the rivers emptying into the Gulf of Mexico are hydrologically separated from the Mississippi River by seawater and have historically been considered safe from an invasion of carp attempting to traverse coastal waters due to their intolerance of seawater salinity levels. However, there is growing concern that freshwater diversions of the Mississippi River into brackish or saltwater systems could reduce salinity to a level that allows entrained carp to navigate freshwater plumes to uninvaded rivers. To help quantify this risk, we conducted an Arrival Assessment that estimates the number of invasive carp that will enter a receiving waterbody through a single freshwater diversion event. A case study using the Bonnet Carré Spillway is presented here to illustrate how water managers and spillway operators can derive predictions for a specific spillway and how mitigative steps can be taken to target the most influential parameters and help reduce the number of carp that pass. The findings of this case study suggest that, for an average spillway opening event, the number of invasive carp that pass through the Bonnet Carré Spillway is higher than many water managers may be willing to accept. This Arrival Assessment serves as the first of three components within a broader, forthcoming quantitative risk assessment that will also consider the number of carp that survive (Survival Assessment) to reach a suitable, uninvaded river for reproduction and population sustainment (Establishment Assessment) and determine the magnitude and uncertainty of the risk of introduction to uninvaded waters downstream from a freshwater diversion that forms a hydrological connection to a source waterbody inhabited by invasive carp.
Seaweed supplementation to organic dairy cows may reduce climate impact of manure in pasture soils during a laboratory incubation
Authors: Arndt Kyle A. , Reyes Diana C. , Quigley Charlotte T. C. , Brito Andre F. , Price Nichole N. , Contosta Alexandra R. 
Published: November 2023

AbstractIntroductionEnteric methane (CH4) emissions are one of the largest components of the anthropogenic CH4 budget, and with accelerating climatic changes, there are calls to reduce anthropogenic greenhouse gas emissions. Certain seaweeds fed as supplements can reduce enteric CH4 emissions from ruminant animals by as much as 80%; however, these studies have yet to analyze downstream impacts that may arise from the deposit of affected manures on pastures or agricultural fields.Materials and MethodsHere we conducted a 28‐day soil and manure incubation utilizing manures collected from dairy cows in a seaweed feeding trial to analyze the impacts of manure on greenhouse gas fluxes and nutrient cycling. Cows were fed different diets with a control group (no seaweed supplementation), and a 3% and 6% by dry‐weight seaweed (Chondrus crispus) supplementation. Three soil moisture treatments were also tested, with a field moist capacity [67% gravimetric water content (GWC)], a drier group (50% GWC), and a saturated treatment (84% GWC).ResultsWe found that manure from seaweed‐fed cows reduced emissions of carbon dioxide and had similar emissions of methane and nitrous oxide to the control. Higher moisture levels increased CH4 emissions and nitrous oxide emissions with CH4 emissions trending higher in seaweed supplements trending higher in. Inorganic nitrogen turnover varied more based on moisture levels than seaweed supplements, as did the magnitude of methane and nitrous oxide emissions. Total carbon and nitrogen mostly decreased except in the 3% seaweed supplementation, which increased carbon and nitrogen with a drop in C:N in the 50% GWC group.ConclusionSeaweed supplements may partially reduce climate impacts of manures from cows fed seaweed supplements or at least not cause harm or impact manure quality. Given feeds may reduce enteric CH4 emissions, they may be a part of a successful strategy to reduce climate impacts of cattle.
Moving towards sustainable environment development in emerging economies: The role of green finance, green tech‐innovation, natural resource depletion, and forested area in assessing the load capacity factor
Authors: Anas Muhammad , Zhang Wei , Bakhsh Satar , Ali Liaqat , Işık Cem , Han Jie , Liu Xuemeng , Rehman Hamad Ur , Ali Amjad , Huang Min 
Published: November 2023

AbstractEnvironmental sustainability is increasingly being prioritized by governments around the world, particularly in emerging economies. This study examined the role of green finance and green technological innovation in environmental sustainability using the “load capacity factor”, also takes into account natural resource depletion and forest cover. This study used annual data from 2000 to 2018 for emerging economies: Brazil, China, India, Indonesia, Turkey and Mexico. Methods of analysis included the cross‐section augmented autoregressive distributed lags (CS‐ARDL) model, along with validation by the common correlated mean group (CCEMG) and augmented mean group (AMG). The results show that green finance, green technological innovation and forested areas consistently have a positive impact on environmental sustainability, while resource depletion has a negative impact. The findings of CS‐ARDL are consistent with those of CCEMG and AMG. The study also makes recommendations that emerging economies need to prioritize REDD+ (Reducing Emissions from Deforestation and Forest Degradation) initiatives and implement resource decoupling policies, in addition to green finance and green technology policies, to achieve environmental sustainability.
Emergence of Cell Behavior Through Feedback Control of Polymersome Membrane Transport
Authors: Rifaie‐Graham Omar 
Published: November 2023

AbstractArtificial cell and organelle construction has recently gained substantial attention to generate simplified models for understanding of biological phenomena, or micro‐ and nanomachines for biomedical and biotechnological applications. A wide array of building blocks has been employed to build these systems as membraneless structures with the ability to compartmentalize chemical reactions by enhanced partitioning, or as membrane‐defined entities that provide a physical barrier that inhibits the interference of external factors. While these systems present unique properties that enable high fidelity to biological processes, they present limited ability to recreate the high selectivity and specificity of small molecule trafficking observed in biological membranes. Owing to their high chemical versatility, polymers can be leveraged to generate 3D structures that resemble biological membranes while providing transmembrane chemical motifs that enable responsiveness to a wide array of stimuli. This Concept Article discusses the ability to control membrane transport facilitating the emergence of out‐of‐equilibrium feedback mechanisms that ultimately modulate enzymatic rates. This can be employed to engineer future artificial cells and organelles that display homeostasis as a mechanism of self‐adaptation to continuously evolving environments.
Tretinoin (2,4‐difluoro‐phenyl) triazole activates proapoptotic protein expression and targets NRP2 protein to inhibit esophageal carcinoma cell growth
Authors: Alotaibi Saad H. 
Published: November 2023

AbstractThe present study investigated the effect of tretinoin (2,4‐difluoro‐phenyl) triazole (TDFPT) on the growth and proliferation of Kyse‐270 and EC9706 esophageal carcinoma cells and explored the underlying mechanism. The results demonstrated that TDFPT treatment of Kyse‐270 and EC9706 cells led to a dose‐dependent reduction in cell proliferation. Colony formation was significantly (p < .05) reduced in Kyse‐270 and EC9706 cells on treatment with various concentrations of TDFPT. In TDFPT‐treated Kyse‐270 and EC9706 cells, the expression of Bcl‐2 protein showed a remarkable decrease, whereas the level of Bax protein was found to be higher compared with the control cells. Cell invasion showed a prominent decrease in Kyse‐270 and EC9706 cells on treatment with TDFPT. Treatment with TDFPT led to a prominent suppression in the expression of MMP‐9 and NRP2 in Kyse‐270 and EC9706 cells. In silico studies using the AutoDock Vina and discovery studio software revealed that various confirmations of TDFPT bind to NRP2 protein with the affinity ranging from −8.6 to −6.1 kcal/mol. It was found that the TDFPT interacts with NRP2 protein by binding to alanine (ALA A:295), proline (PRO A:306), glutamine (GLN A:307), and isoleucine (ILE A:293) amino acid residues. In summary, TDFPT exposure suppresses esophageal carcinoma cell proliferation, inhibits colony formation ability, and activates apoptotic pathway. Thus, TDFPT acts as an effective antiproliferative agent for esophageal carcinoma cells and needs to be investigated further as chemotherapeutic molecule.