bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the impact of colleges’ English education on regional economic development: A case study of Shanghai and Jiangsu province
Authors: Agarwal Nidhi , Chen Wenjing , Li Wei , Mohan Chandra
Published: July 2024

In the era of globalization of the knowledge economy and significant global population mobility, language serves not only as a tool for acquiring and exchanging information but also as a bridge and conduit for the dissemination and promotion of technology, culture, and knowledge on a global scale. Language can serve as both a tool to acquire other knowledge and skills, forming human capital, and can also be directly used to serve society, bringing about relative economic benefits to both the nation and individuals. The world language, English, with its unique advantages of spanning regions and borders, widely disseminates various technological, cultural, and economic information. With the increasing integration of the global economy and the development of regional economies in China, there is a growing and strong interactive relationship and interdependence between college English education and regional economic development. This paper selects relevant data from Shanghai and Jiangsu Province over the past decade and, through correlation analysis and regression analysis, establishes a significant correlation between colleges English teaching and regional economic development. It proves that college English teaching has become an important factor in promoting sustainable regional economic development. Based on this conclusion, it proposes the concept that colleges of English teaching and regional economic development should support and promote each other, achieving harmonious development and mutual progress.
Magnetite geochemistry of giant alkalic-type epithermal gold deposits: insights into the magmatic evolution of mineralized alkaline systems
Authors: Schirra Michael , Zajacz Zoltan , Müller Daniel
Published: July 2024

Magnetite, a common mineral in alkaline magmatic complexes hosting giant epithermal Au deposits, is examined to obtain insights into the magmatic evolution and ore fertility of alkaline systems. Textural and compositional analyses of magmatic magnetite from Cripple Creek, USA, and Lihir Island, Papua New Guinea, reveal distinct magma sources and evolution paths. High high-field-strength element concentrations and high La/Yb ratios in magnetite from Cripple Creek suggest relatively low-degree partial melting of lithospheric and asthenospheric mantle sources, whereas magnetite from Lihir Island indicates higher-degree partial melting from subduction-modified mantle. Chromium concentrations track magma evolution, while V systematics record decreasing oxygen fugacity with magma differentiation. Sulfide saturation is observed at Cripple Creek, potentially affecting ore fertility. Magnetite itself bears the capability to scavenge Au from melts as indicated by Au concentrations of up to 40 ng/g. This might point towards elevated Au concentrations in the parental magmas, although experimental data on Au partitioning are lacking. Magnetite compositions overlap across different mineralization styles, challenging its reliability as an exploration tool, but analysis of noble metals in magnetite and its inclusion cargo could offer promising alternative approaches. Overall, magnetite serves as a valuable tool for investigating ore deposit petrogenesis and holds potential for exploration.
OffloaD: Detection Failure-based Scheduler for Offloading Object Detection
Authors: Gomez Clara , Patkhullaev Davron , Hernandez Alejandra C.
Published: July 2024

The current times ask for resource-constrained devices such as drones, light mobile robots, XR glasses, or mobile phones to perform object detection efficiently and in real time. However, when executed on the device, object detection fails to achieve the accuracy requirements. In addition, depending on a powerful edge to offload computation is time-consuming as it requires the transmission of a large amount of data and limits the usage in degraded network conditions. In this article, we propose OffloaD, a novel offloading scheduler based on the detection of failures for object detection. The method addresses the problem of offloading between a resource-constrained device and an edge by leveraging the accuracy of the object detection model at the device and the network conditions. Accuracy is considered through a detection failure metric that consists of introspective, golden, and latency scores. Our main contribution is the offloading scheduler based on the detection of failures of the object detector, which reduces unnecessary data transmission without accuracy degradation. Our method demonstrates that offloading to expensive detectors will not always increase performance and enables detection results and failure estimations even if the network is degraded or unavailable. We implement OffloaD in a physical testbed and perform extensive comparisons against several baselines. The experiments suggest that our approach improves the overall precision-latency performance by reducing the end-to-end latency between 18% and 37% in ideal network conditions and a low latency increase in degraded network conditions while obtaining an accuracy with minimum degradation compared to the baselines. In addition, comparisons to related work methods demonstrate the state-of-the-art performance of OffloaD.
Reusing d-DNNFs for Efficient Feature-Model Counting
Authors: Sundermann Chico , Raab Heiko , Heß Tobias , Thüm Thomas , Schaefer Ina
Published: July 2024

Feature models are commonly used to specify valid configurations of a product line. In industry, feature models are often complex due to numerous features and constraints. Thus, a multitude of automated analyses have been proposed. Many of those rely on computing the number of valid configurations, which typically depends on solving a
#
SAT problem, a computationally expensive operation. Even worse, most counting-based analyses require evaluation for multiple features or partial configurations resulting in numerous
#
SAT computations on the same feature model. Instead of repetitive computations on highly similar formulas, we aim to improve the performance by reusing knowledge between these computations. In this work, we are the first to propose reusing d-DNNFs for performing repetitive counting queries on features and partial configurations. In our experiments, reusing d-DNNFs saved up-to

\(\sim\)

99.98% compared to repetitive invocations of
#
SAT solvers even when including compilation times. Overall, our tool
ddnnife
combined with the d-DNNF compiler
d4
appears to be the most promising option when dealing with many repetitive feature-model counting queries.
MULTICR: Predicting Merged and Abandoned Code Changes in Modern Code Review Using Multi-Objective Search
Authors: Chouchen Moataz , Ouni Ali , Mkaouer Mohamed Wiem
Published: July 2024

Modern Code Review (MCR) is an essential process in software development to ensure high-quality code. However, developers often spend considerable time reviewing code changes before being merged into the main code base. Previous studies attempted to predict whether a code change was going to be merged or abandoned soon after it was submitted to improve the code review process. However, these approaches require complex cost-sensitive learning, which makes their adoption challenging since it is difficult for developers to understand the main factors behind the models’ predictions. To address this issue, we introduce in this article,
MULTICR
, a multi-objective search-based approach that uses Multi-Objective Genetic Programming (MOGP) to learn early code review prediction models as IF-THEN rules.
MULTICR
evolves predictive models while maximizing the accuracy of both merged and abandoned classes, eliminating the need for misclassification cost estimation. To evaluate MULTICR, we conducted an empirical study on 146,612 code reviews from Eclipse, LibreOffice, and Gerrithub. The obtained results show that
MULTICR
outperforms existing baselines in terms of Matthew Correlation Coefficient (MCC) and F1 scores while learning less complex models compared to decision trees. Our experiments also showed how
MULTICR
allows identifying the main factors related to abandoned code reviews as well as their associated thresholds, making it a promising approach for early code review prediction with notable performance and inter-operability. Additionally, we qualitatively evaluate
MULTICR
by conducting a user study through semi-structured interviews involving 10 practitioners from different organizations. The obtained results indicate that 90% of the participants find that
MULTICR
is useful and can help them to improve the code review process. Additionally, the learned IF-THEN rules of
MULTICR
are transparent.
Polynomial Integrality Gap of Flow LP for Directed Steiner Tree
Authors: Li Shi , Laekhanukit Bundit
Published: July 2024

In the Directed Steiner Tree (DST) problem, we are given a directed graph

\(G=(V,E)\)

on

\(n\)

vertices with edge-costs

\(c\in{\mathbb{R}}_{\geq 0}^{E}\)

, a root vertex

\(r\in V\)

, and a set

\(K\subseteq V\setminus\{r\}\)

of

\(k\)

terminals. The goal is to find a minimum-cost subgraph of

\(G\)

that contains a path from

\(r\)

to every terminal

\(t\in K\)

. DST has been a notorious problem for decades as there is a large gap between the best-known polynomial-time approximation ratio of

\(O(k^{\epsilon})\)

for any constant

\(\epsilon \gt 0\)

, and the best quasi-polynomial-time approximation ratio of

\(O\left(\frac{\log^{2}k}{\log\log k}\right)\)

. Toward understanding this gap, we study the integrality gap of the standard flow linear programming relaxation for the problem. We show that the linear program (LP) has an integrality gap of

\(\Omega(n^{0.0418})\)

. Previously, the integrality gap of the LP is only known to be

\(\Omega\left(\frac{\log^{2}n}{\log\log n}\right)\)

[Halperin et al., SODA’03 & SIAM J. Comput.] and

\(\Omega(\sqrt{k})\)

[Zosin-Khuller, SODA’02] in some instance with

\(\sqrt{k}=O\left(\frac{\log n}{\log\log n}\right)\)

. Our result gives the first known lower bound on the integrality gap of this standard LP that is polynomial in

\(n\)

, the number of vertices. Consequently, we rule out the possibility of developing a poly-logarithmic approximation algorithm for the problem based on the flow LP relaxation.
Digital Food Sensing and Ingredient Analysis Techniques to Facilitate Human-Food Interface Designs
Authors: Amarasinghe Chamath , Ranasinghe Nimesha
Published: July 2024

Interactive technologies that shape the traditional human-food experiences are being explored under the emerging field of Human-Food Interaction (HFI). A key challenge in developing HFI technologies is the digital sensing of food, beverages, and their ingredients, commonly known as digital food sensing. Digital food sensing involves recognizing different food and beverages and their internal attributes, such as volume and ingredients (e.g., salt and sugar content). Contemporary research on interactive food applications, such as dietary assessment, primarily employs Computer Vision (CV) techniques to identify food; however, they are ineffective when (1) identifying food’s internal attributes, (2) discriminating visually similar food and beverages, and (3) seamlessly integrating with people’s natural interactions while consuming food. Thus, this article reviews potential food and beverage sensing technologies that can facilitate novel Human-Food Interfaces, primarily focusing on non-disruptive sensing techniques to analyze food and beverages during consumption. First, we review ten different digital food sensing techniques and their applications in four categories. Then, we discuss three main aspects to consider when adopting these food-sensing techniques for human-food interface designs. Finally, we suggest the future research requirements in digital food sensing methodologies, followed by potential applications of digital food sensing in future developments of Human-Food Interfaces.
Selection Neglect and Political Beliefs
Authors: Brundage Matt , Little Andrew T. , You Soosun
Published: July 2024

Individuals, including researchers, often have to form beliefs about the political world from nonrepresentative samples—e.g., their friends, what they see on TV, or content on social media. Substantial evidence indicates that many struggle to account for this selection problem and generally form beliefs as if what they observe is representative. In this review, we provide a formal typology of how this phenomenon of selection neglect affects political beliefs. We identify three types of selection neglect: homophily leads individuals to believe others’ traits and beliefs are closer to their own; the squeaky wheel effect biases beliefs toward more visible or vocal groups; and the man bites dog effect leads to excessive belief in extreme or unusual events. Selection neglect is a unifying way to understand disparate literatures on perceptions of the economy and demographics, beliefs about others’ beliefs, partisan media, and social media. Much empirical research is consistent with biased beliefs driven by selection neglect but rarely directly tests this mechanism outside of lab settings. We discuss how future research can provide more direct evidence.
Case 327: Exogenous Lipoid Pneumonia
Authors: Decavèle Maxens , Pichon Jérémie , Fajac Anne , Milon Audrey , Antoine Martine , Gibelin Aude , Parrot Antoine , Fartoukh Muriel
Published: July 2024

History

A 58-year-old male patient with an active smoking status was admitted twice to the intensive care unit (ICU) of a tertiary referral thoracic center for severe hypercapnic acute respiratory failure and persistent bilateral chest radiograph opacities that were unchanged over the course of the two ICU admissions within a 3-month period. The patient had obesity (body mass index, 36), stage 3 vascular chronic renal insufficiency, and hebephrenic schizophrenia treated with haloperidol, carbamazepine, and cyamemazine. He reported chronic dyspnea on exertion, which worsened for 6 months. At the second ICU admission, the patient was afebrile, with a blood pressure of 160/72 mm Hg and pulse oximetry of 93% on 6 L/min oxygen therapy through a nonrebreathing mask. Physical examination showed signs of respiratory failure with wheezing and active abdominal expiration, and bilateral pulmonary crackles without chest pain, hemoptysis, clubbing, or signs of cardiac failure. The patient had no peripheral lymphadenopathy and no enlarged spleen. Blood gases (on 6 L/min oxygen) showed respiratory acidosis (pH, 7.15 [normal range, 7.38–7.42]; PaO2 level, 67 mm Hg [normal range, 80–100 mm Hg]; PaCO2 level, 102 mm Hg [normal range, 38–42 mm Hg]; bicarbonate [HCO3−], 29 mmol/L [normal range, 22–27 mmol/L]). Noninvasive ventilation was initiated. Imaging performed during the second ICU hospitalization included CT and MRI of the chest without contrast enhancement, and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT.
Case 331
Authors: Umer Muhammad , Sagheer Usman , Furtado Wilfred , Shotwell Matthew , Joshi Jonathan , Shetty Mrinali , Kalra Dinesh K.
Published: July 2024

History

A 43-year-old male patient with no known past medical history presented to the emergency department with new-onset bitemporal headache, dizziness, and bilateral lower extremity weakness for 1 day. The patient denied chest pain, shortness of breath, cough, or recent exposure to sick individuals. He was not on any medications and denied alcohol or illicit drug use. Vital signs were unremarkable. Physical examination was notable for a left-sided pronator drift and bilateral dysmetria that was more pronounced on the left. Results of routine laboratory workup, including complete blood count, metabolic panel, and high-sensitivity troponin level, were normal. An electrocardiogram revealed sinus tachycardia with a heart rate of 102 beats per minute, T-wave inversions in the inferior leads, left axis deviation, incomplete right bundle branch block, and frequent premature ventricular contractions. A radiograph of the chest was unremarkable. CT of the head without contrast enhancement demonstrated no acute intracranial abnormities. MRI of the brain without contrast enhancement revealed multiple acute infarcts involving left posterior inferior cerebellar artery distribution, right cerebellar hemisphere, right mesial temporal lobe, and right posterior limb of the internal capsule. CT angiography of the head and neck showed an occlusion of the right posterior cerebral artery near its origin, with a trace of distal flow. Given that these findings were concerning for a cardioembolic etiology of acute ischemic stroke, transesophageal echocardiography was performed. This showed mild left ventricular systolic dysfunction with an ejection fraction of 40%, mild global hypokinesis, and an additional finding also seen at subsequent cardiac CT and MRI that will be disclosed in part 2 of the case. The patient was started on systemic anticoagulation and guideline-directed medical therapy for heart failure with reduced ejection fraction. CT of the chest showed no evidence of lymphadenopathy or abnormalities in the lung parenchyma or interstitium. Coronary CT angiography was performed ( Fig 1 ), followed by cardiac MRI ( Fig 2 ).
Submillisievert Abdominal Photon-Counting CT versus Energy-integrating Detector CT for Urinary Calculi Detection: Impact on Diagnostic Confidence
Authors: Huflage Henner , Kunz Andreas Steven , Patzer Theresa Sophie , Pichlmeier Svenja , Westhofen Thilo , Gruschwitz Philipp , Heidenreich Julius Frederik , Lennartz Simon , Bley Thorsten Alexander , Grunz Jan-Peter
Published: July 2024

Abdominal photon-counting CT with tin prefiltration enabled submillisievert urolithiasis imaging with high image quality, and radiation exposure was reduced by 44% compared with dose-optimized energy-integrating detector CT.
Dotatate PET/CT and 225Ac-Dotatate Therapy for Somatostatin Receptor–expressing Metastatic Breast Cancer
Authors: Ulaner Gary A. , VanderMolen Louis A. , Li Gary , Ferreira Denis
Published: July 2024

Molecular imaging with somatostatin receptor type 2 (SSTR2)–targeted Dotatate PET/CT and radioligand therapy with SSTR2-targeted actinium 225 Dotatate may enable a new therapeutic option for patients with metastatic breast cancer.
Assessing Digital Breast Tomosynthesis Impact on Early Cancer Detection: Insights from Consecutive Screening
Authors: Jögi Annika , Johnson Kristin , Wittgren Sofia , Sundgren Victor , Tomic Hanna , Olinder Jakob , Åkesson Anna , Andersson Ingvar , Zackrisson Sophia , Bakic Predrag R.
Published: July 2024

Analysis of the Malmö Breast Tomosynthesis Screening Trial revealed lower cancer detection rates and invasive cancers after tomosynthesis, suggesting enhanced early detection potential, particularly for luminal A–like cancers.
Isovalent Co-Substitution of Iron and Titanium into Single-Crystal NMC622
Authors: Macintosh Macgregor F. , Shakouri Mohsen , Obrovac M. N.
Published: July 2024

Substitutional Li[Ni0.6Mn0.2Co0.2]O2 oxides (known as NMC622) were made by all-dry synthesis with Fe and Ti substituting Co and Mn, respectively. The substitutions were performed in three series, Fe substitution for Co, Ti substitution for Mn, and Fe and Ti co-substitution for Co and Mn, according to the formula Li(Ni0.6Mn0.2−y
Co0.2−x
Fe
x
Ti
y
)O2. The resulting oxides were evaluated as cathode materials for Li-ion batteries. Fe-substitution for Co resulted in increased intersite mixing, resulting in increased polarization and capacity fade. Ti-substitution for Mn also resulted in increased intersite mixing, but the mixing was due to Ti3+ in the Li-layer. As a result, Ti-substituted NMCs had improved capacity retention and reduced polarization. These effects were independent of each other, so that Ti could partially offset the negative aspects of Fe-substitution. Additionally, layered Mn-free Li(Ni0.6Ti0.2Co0.2)O2 (NTC622) was produced as an endmember of this series for the first time with low intersite mixing and superior electrochemical performance in comparison to previous reports. These results demonstrate benefits of all-dry Ti-substitution in NMC and the all-dry synthesis method as an avenue towards new cathode composition discovery.
Electrolyte Design for NMC811||SiOx-Gr Lithium-Ion Batteries with Excellent Low-Temperature and High-Rate Performance
Authors: He Wei , Yeddala Munaiah , Rynearson Leah , Lucht Brett
Published: July 2024

The use of high-nickel NMC811 cathode and SiOx-Gr anode can greatly improve the overall energy densities of lithium-ion batteries. However, the unfavorable solid electrolyte interphase (SEI) layer generated from the decomposition of EC-based electrolytes lead to the poor cycling stability of NMC811||SiOx-Gr cells. Here we report an electrolyte design of 1.5 M LiPF6 dissolved in FEC/MA/BN 2:2:6 by volume, which can form thin, robust, and homogeneous SEI layer to greatly improve the charge transfer at the electrode-electrolyte interface. Importantly, the designed electrolyte shows an outstanding low temperature performance that it can deliver a capacity of 123.3 mAh g–1 after 50 cycles at −20 °C with a current density of 0.5 C, overwhelming the standard EC-based electrolyte (1.2 M LiPF6 EC/EMC 3:7 by volume) with a capacity of 35.7 mAh g–1. The electrolyte also has a superior rate performance that it achieves a capacity of 122.5 mAh g−1 at a high current density of 10 C. Moreover, the LTE electrolyte holds the great potential of extreme fast-charging ability because of the large part of CC contribution in the CCCV charging model at high charging current densities.
State of Health Estimation of Lithium-Ion Battery for Electric Vehicle Based on VMD-DBO-SVR Model
Authors: Tong Liang , Gong Minghui , Chen Yong , Kuang Rao , Xu Yonghong , Zhang Hongguang , Peng Baoying , Yang Fubin , Zhang Jian , Li Yiyang
Published: July 2024

State-of-health (SOH) of lithium-ion batteries is an important indicator for measuring performance and remaining life. We propose an innovative prediction model that integrates variational mode decomposition (VMD), Dung Beetle optimizer (DBO), and support vector regression (SVR) algorithms. We extracted relevant features from the discharge characteristic curve and incremental capacity curve. We used Pearson and Spearman correlation coefficient methods for correlation analysis on the extracted health factors (HFs), selecting those that significantly impact SOH as input features. A DBO-SVR model was constructed to establish a nonlinear correlation between HFs and SOH, and the DBO algorithm was used to globally search and optimize the hyperparameters of the SVR model to improve its prediction accuracy. To reduce the impact of noise in battery signals on model performance, VMD technology was introduced to decompose battery signals into multiple intrinsic mode components, to extract useful features and remove noise to further improve prediction accuracy. The proposed method was validated using the NASA battery dataset and compared with other algorithm models. Results showed that the prediction model was significantly better than other models, with a maximum RMSE value of 0.84%, a maximum MAE value of 0.71%, and a stable prediction error value within 1%.
Effect of PVdF Distribution on Properties and Performance of Dry Spray-Coated Graphite Electrodes for Lithium-Ion Batteries for Electric Vehicle Applications
Authors: Barreras-Uruchurtu J. Alberto , Besnard Nicolas , Paul Clément , Marchal Lauréline , Devisme Samuel , Lestriez Bernard
Published: July 2024

We used electrostatic dry spray-coating to fabricate graphite/PVdF anodes. We compared the morphological, mechanical, electrical, and electrochemical properties of electrodes fabricated with three different mixing times of dry electrode components. Quantitative and novel relationships between the PVdF distribution and the electrode properties were obtained. Our investigations suggest that our fabrication methods are viable alternatives for producing electrodes with comparable properties to those fabricated using traditional wet solvent-based methods. Overall, our work provides insights into new and promising methods for fabricating high-quality dry-sprayed electrodes (DSEs) with high mass loadings for use in a variety of electrochemical applications such as electric vehicles.
Substituting Na for Excess Li in Li1+x(Ni0.6Mn0.4)1−xO2 Materials
Authors: Rathore Divya , Perez Harold Smith , Monchesky Ian , Vain Fanny , Xiao Penghao , Yang Chongyin , Dahn J. R.
Published: July 2024

NMC640, a series of Li1+x(Ni0.6Mn0.4)1−xO2 materials, are important Co-free mid-Ni cathode materials for Li-ion batteries, offering high energy density and better cost-efficiency than Ni-rich counterparts. These materials require excess Li compared to stoichiometric composition to improve the electrochemical performance in terms of rate capability and cycling stability. Although lithium-to-transition metal ratios up to 1.15 can be used to optimize the performance, less than 80% of this lithium is electrochemically active during cycling up to a 4.4 V upper cut off. This study explores whether some percentage of the inactive Li can be replaced by sodium to make these materials more cost-effective and bring potential improvements in electrochemical performance. Various amounts of excess Li were substituted by sodium in the structure. The results show that sodium can be integrated into the layered oxide structure without forming any impurity phases and effectively decreases the cation mixing observed in these layered structures. However, this does compromise cycling stability and rate capability. Na tends to occupy Li sites rather than transition metal sites, resulting in electrochemical instability and capacity loss. Even though excess Li is not electrochemically active, it cannot be effectively replaced by sodium without compromising battery performance of Li1+x(Ni0.6Mn0.4)1−xO2 materials.
Capacity and Resistance Diagnosis of Batteries with Voltage-Controlled Models
Authors: Bessler Wolfgang G.
Published: July 2024

Capacity and internal resistance are key properties of batteries determining energy content and power capability. We present a novel algorithm for estimating the absolute values of capacity and internal resistance from voltage and current data. The algorithm is based on voltage-controlled models. Experimentally-measured voltage is used as an input variable to an equivalent circuit model. The simulation gives current as output, which is compared to the experimentally-measured current. We show that capacity loss and resistance increase lead to characteristic fingerprints in the current output of the simulation. In order to exploit these fingerprints, a theory is developed for calculating capacity and resistance from the difference between simulated and measured current. The findings are cast into an algorithm for operando diagnosis of batteries operated with arbitrary load profiles. The algorithm is demonstrated using cycling data from lithium-ion pouch cells operated on full cycles, shallow cycles, and dynamic cycles typical for electric vehicles. Capacity and internal resistance of a “fresh” cell was estimated with high accuracy (mean absolute errors of 0.9% and 1.8%, respectively). For an “aged” cell, the algorithm required adaptation of the model’s open-circuit voltage curve to obtain high accuracies.
The Possible Role of Thermite Reactions in Thermal Runaway of Li-ion Cells with Layered Cathodes
Authors: LaFollette Rodney , Eskra Michael D.
Published: July 2024

It is often observed that some runaway Li-ion cells with layered cathode materials become much hotter internally than existing thermal runaway models predict. Further, metals originally in the positive active material (such as Co, Ni, and Mn) are often found in cells whose temperatures became very high. It has been postulated that the formation of metals can be attributed to reduction of rock salt species (MO, where M is the metal), or the reaction of lithiated active material (LiMO2) with CO2. We propose an alternate process for formation of metals that also results in very high cell temperatures, namely thermite reactions between the Al positive electrode current collector and the positive active material. These reactions are highly exothermic, in contrast with the reactions of MO and LiMO2 mentioned. In this paper the thermodynamics of thermite reactions are presented. Incorporating thermite reactions in runaway models will likely improve temperature prediction of Li-ion cells in thermal runaway.
cUMP elicits interendothelial gap formation during Pseudomonas aeruginosa infection
Authors: deWeever Althea , Paudel Sunita S. , Zhou Chun , Francis C. Michael , Tambe Dhananjay T. , Frank Dara W. , Balczon Ron , Stevens Troy
Published: July 2024

During pneumonia, bacteria utilize a virulence arsenal to communicate with host cells. The Pseudomonas aeruginosa T3SS directly introduces virulence molecules into the host cell cytoplasm. These molecules are enzymes that trigger interkingdom communication. One of the exoenzymes is a nucleotidyl cyclase that produces noncanonical cyclic nucleotides like cUMP. Little is known about how cUMP acts in the cell. Here we found that cUMP instigates pulmonary edema during Pseudomonas aeruginosa infection of the lung.
Development of an Optimal Control Method for the Concentration of Degradable Substances
Authors: Matsuo Tomohito , Shimadera Hikari , Kondo Akira
Published: July 2024

Indoor environments affect occupant hygiene, comfort, and productivity. Special treatments, such as spraying essential oils, disinfectant gases, and water vapor or droplets, have been proposed to improve indoor comfort in recent years. Therefore, a method to control the concentrations of these beneficial substances is required. To control the indoor concentration distribution of various degradable substances emitted indoors, this article proposes a novel method that uses the linear relationship between the source and concentration distributions. The method was evaluated through numerical experiments using CFD. Furthermore, the effects of the deposition (Dep) and decomposition (Dec) of the substances on the performance were assessed. The method successfully determined the optimal emission intensities for each emission source to make the concentration field close to the objective—the uniform distribution—in the experiment. When substances decomposed in the air or were deposited on the walls, the performance of the optimal control decreased compared to the case without Dec or Dep. This indicated that the occurrence of Dec or Dep lowered the optimization performance by enhancing the unevenness of the concentration field in the area near the emission source and far from the source. The Dep case showed relatively lower performance than the Dec case because the Dep occurred more spatially unevenly than the Dec. In addition, the more emission sources employed, the smaller the gap between the objective and the optimized concentration field. This method will help control indoor air quality more efficiently.
Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran
Authors: Shaibani Mohammad Javad , Fazaeli Ali Akbar
Published: July 2024

The expected healthcare (HC) inflation rate (IR) (HCIR) is an important variable for all economic agents within HC systems. In recent years, during the COVID‐19 pandemic, Iran has experienced a high HCIR in its health system. In this context, a robust approximation of HCIR will be a helpful tool for health authorities and other decision makers. Using monthly time series data of HCIR in Iran, we developed various forecasting techniques based on classical smoothing methods, decomposition ETS (error, trend, and seasonality) approaches, autoregressive (AR) integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and a multilayer nonlinear AR artificial neural network (NARANN) with several training algorithms including Bayesian regularization (BR), Levenberg–Marquardt (LM), scaled conjugate gradient (SCG), Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi‐Newton, conjugate gradient with Powell–Beale restarts (CGB), conjugate gradient with Fletcher–Reeves updates (CGF), and resilient propagation (RPROP) algorithms. Initially, based upon various criteria and possible combinations, we selected the superior model for each method separately. After that, the best model in each category is involved in 6‐ and 12‐multi‐step‐ahead prediction. In this stage, several error criteria are calculated. According to our findings, in a six‐step forecasting window, the Holt–Winters with a multiplicative seasonal pattern and SARIMA showed less bias, though compared to other alternatives like NARANN‐lm/br, the difference was relatively small. In the next process, by doubling the forecasting window, it is observed that artificial neural network (ANN) (i.e., Bayesian NARANN) strictly outperformed other models. As a result, in shorter steps, the Holt–Winters method can provide a better prediction, while in longer windows, Bayesian NARANN can be implemented vigorously for the prediction. Finally, we used 10 models to predict the future trend of HCIR in Iran till the end of July 2024.
TGFβ1, SNAIL2, and PAPP‐A Expression in Placenta of Gestational Diabetes Mellitus Patients
Authors: He Yujing , Yang Xiyao , Wu Na
Published: July 2024

Background: Gestational diabetes mellitus (GDM) is a pregnancy‐related diabetic condition that may cause serious complications. However, its pathogenesis remains unclear. Placental damage due to GDM may lead to several health issues that cannot be ignored. Thus, we aimed to identify the mechanisms underlying GDM by screening differentially expressed genes (DEGs) related to vascular endothelial cells in the GDM databases and verify the expression of these DEGs in the placentas of women afflicted by GDM.

Methods: We used GDM microarray datasets integrated from the Gene Expression Omnibus (GEO) database. Functional annotation and protein–protein interaction (PPI) analyses were used to screen DEGs. Placental tissues from 20 pregnant women with GDM and 20 healthy pregnant women were collected, and differential gene expression in the placental tissues was verified via qRT‐PCR, western blotting, and immunofluorescence.

Results: Bioinformatics analysis revealed three significant DEGs: SNAIL2, PAPP-A, and TGFβ1. These genes were all predicted to be underexpressed in patients with GDM. The results of qRT‐PCR, western blot, and immunofluorescence analyses indicated that SNAIL2 and PAPP‐A in the placenta tissue of patients with GDM were significantly underexpressed. However, TGFβ1 in the placenta tissues of GDM was significantly overexpressed.

Conclusion: SNAIL2, TGFβ1, and PAPP‐A may affect the placentas of pregnant women with GDM, warranting further investigation.
IFN‐γ‐Licensed Mesenchymal Stem Cells Are More Susceptible to Death when Exposed to Quorum‐Sensing Signal Molecule OdDHL and Less Effective in Inhibiting the Growth of Pseudomonas aeruginosa
Authors: Sousa Marielly Reis Resende , Silva-Carvalho Amandda Évelin , Sousa Maurício Gonçalves da Costa , Martins Danilo César Mota , Garcez Emãnuella Melgaço , Filiú Braga Luma Dayane de Carvalho , Carvalho Juliana Lott de , Dalmolin Tanise Vendruscolo , Rezende Taia Maria Berto , Saldanha-Araujo Felipe
Published: July 2024

Currently, a series of licensing strategies has been investigated to enhance the functional properties of mesenchymal stem cells (MSCs). Licensing with IFN‐γ is one of the most investigated strategies for enhancing the immunosuppressive potential of such cells. However, it is not yet known whether this licensing strategy could interfere with the ability of MSCs to control bacterial growth, which may be relevant considering their clinical potential. In this study, we compared the antimicrobial potential of IFN‐γ‐licensed and unlicensed MSCs by exposing them to Pseudomonas aeruginosa and its quorum‐sensing inducer molecule OdDHL. Our data show that—when challenged with OdDHL—IFN‐γ‐licensed and unlicensed MSCs present increased levels of the antimicrobial HAMP transcript, but that only IFN‐γ‐licensed MSCs undergo modulation of CASP1 and BCL2, entering apoptosis. Furthermore, we demonstrate that only IFN‐γ‐licensed MSCs show modulation in genes involved in apoptosis and tend to undergo cell death when cultured with P. aeruginosa. As a consequence, IFN‐γ‐licensed MSCs showed lower capacity to control bacterial growth, compared to unlicensed MSCs. Taken together, our observations reveal an increased susceptibility to apoptosis of IFN‐γ‐licensed MSCs, which compromises their potential to control the bacterial growth in vitro. These findings are relevant to the field of cell therapy, considering the potential applicability of MSCs.
Taz/Tead1 Promotes Alternative Macrophage Activation and Kidney Fibrosis via Transcriptional Upregulation of Smad3
Authors: Ren Yizhi , Zhou Lu , Li Xinyuan , Zhu Xingwen , Zhang Zhiheng , Sun Xiaoli , Xue Xian , Dai Chunsun
Published: July 2024

Macrophage alternative activation is involved in kidney fibrosis. Previous researches have documented that the transcriptional regulators Yes‐associated protein (Yap)/transcriptional coactivator with PDZ‐binding motif (Taz) are linked to organ fibrosis. However, limited knowledge exists regarding the function and mechanisms of their downstream molecules in regulating macrophage activation and kidney fibrosis. In this paper, we observed that the Hippo pathway was suppressed in macrophages derived from fibrotic kidneys in mice. Knockout of Taz or Tead1 in macrophages inhibited the alternative activation of macrophages and reduced kidney fibrosis. Additionally, by using bone marrow–derived macrophages (BMDMs), we investigated that knockout of Taz or Tead1 in macrophages impeded both cell proliferation and migration. Moreover, deletion of Tead1 reduces p‐Smad3 and Smad3 abundance in macrophages. And chromatin immunoprecipitation (ChIP) assays showed that Tead1 could directly bind to the promoter region of Smad3. Collectively, these results indicate that Tead1 knockout in macrophages could reduce TGFβ1‐induced phosphorylation Smad3 via transcriptional downregulation of Smad3, thus suppressing macrophage alternative activation and IRI‐induced kidney fibrosis.
Macleaya Extract versus Pregabalin Therapeutic Effectiveness for Neuropathic Pain in Dogs
Authors: Petchnamthong Saowanee , Krambunlue Titiyaporn , Suwanna Nirut
Published: July 2024

Dogs suffer from neuropathic pain due to several neurological disorders, particularly intervertebral disc disease. We aimed to identify alternative therapeutics for neuropathic pain relief in dogs by comparing the treatment efficacy of pregabalin and Macleaya extract against neuropathic pain from cervical spinal hyperesthesia caused by intervertebral disc disease in dogs. We evaluated 10 dogs suffering from cervical intervertebral disc disease for neuropathic pain using the filament von Frey aesthesiometer (VFA). The dogs were randomly divided into two groups, G1 (n = 5) was treated with 4 mg/kg of pregabalin/12 hours orally for 14 days, and G2 (n = 5) was treated with 15 mg/kg Macleaya extract once daily orally for 14 days. To detect neuropathic pain, the VFA was used to measure the sensory threshold (ST) on days 0, 7, and 14. The results revealed decreases in all ST outcomes with no significant differences between the groups on day 14 posttreatment, as well as a decrease in the severity of neurological disease in both groups on day 7 posttreatment. No significant differences were detected in hematological and biochemical profiles (alanine aminotransferase (ALT), alkaline phosphatase (ALP), serum creatinine (SCR), urea nitrogen (BUN), and total protein (TP)) in both groups between pre‐ and posttreatment were not significantly different. The Macleaya extract can reduce neuropathic pain in a similar pattern to pregabalin. Macleaya extract may be effective for the treatment of neuropathic pain in dogs with spinal hyperesthesia.
Cervical Cancer Evades the Host Immune System through the Inhibition of Type I Interferon and CXCL9 by LIF
Authors: Bonfill-Teixidor Ester , Neva-Alejo Almudena , Arias Alexandra , Cuartas Isabel , Iurlaro Raffaella , Planas-Rigol Ester , Solé Laura , Pecharromán Irene , Cabrera Silvia , García Ángel , Garcia-Illescas David , Espinosa Lluís , Gil-Moreno Antonio , Oaknin Ana , Seoane Joan
Published: July 2024

Purpose:

Cervical cancer is a viral-associated tumor caused by the infection with the human papilloma virus. Cervical cancer is an immunogenic cancer that expresses viral antigens. Despite being immunogenic, cervical cancer does not fully respond to immune checkpoint inhibitors (ICI). LIF is a crucial cytokine in embryo implantation, involved in maternal tolerance that acts as an immunomodulatory factor in cancer. LIF is expressed in cervical cancer and high levels of LIF is associated with poor prognosis in cervical cancer.

Experimental Design:

We evaluated the impact of LIF on the immune response to ICI using primary plasmocytoid dendritic cells (pDC) and macrophage cultures, syngeneic animals and patient-derived models that recapitulate the human tumor microenvironment.

Results:

We found that the viral proteins E6 and E7 induce the expression of LIF via the NFκB pathway. The secreted LIF can then repress type I interferon expressed in pDCs and CXCL9 expressed in tumor-associated macrophages. Blockade of LIF promotes the induction of type I interferon and CXCL9 inducing the tumor infiltration of CD8 T cells. This results in the sensitization of the tumor to ICI. Importantly, we observed that patients with cervical cancer expressing high levels of LIF tend to be resistant to ICI.

Conclusions:

Our data show that the HPV virus induces the expression of LIF to provide a selective advantage to the tumor cell by generating local immunosuppression via the repression of type I interferon and CXCL9. Combinatory treatment with blocking antibodies against LIF and ICI could be effective against cervical cancer expressing high levels of LIF.
Pharmacogenomic Score Effectively Personalizes Treatment of Acute Myeloid Leukemia
Authors: Marrero Richard J. , Wu Huiyun , Cao Xueyuan , Parcha Phani Krishna , Elsayed Abdelrahman H. , Inaba Hiroto , Kuo Dennis John , Degar Barbara A. , Heym Kenneth , Taub Jeffrey W. , Lacayo Norman , Pui Ching-Hon , Ribeiro Raul C. , Rubnitz Jeffrey E. , Pounds Stanley B. , Lamba Jatinder K.
Published: July 2024

Purpose:

Cytarabine (also known as ara-C) has been the backbone of acute myeloid leukemia (AML) chemotherapy for more than five decades. Recent pharmacogenomics-based 10-SNP ara-C (ACS10) scores showed low ACS10 (≤0) to be associated with poor outcomes in patients with AML treated with standard chemotherapy. Here, we evaluated the ACS10 score in the context of three different induction I regimens in patients with pediatric AML.

Experimental Design:

ACS10 score groups (low, ≤0, or high, >0) were evaluated for association with event-free survival (EFS) and overall survival (OS) by three randomized treatment arms in patients treated on the AML02 (NCT00136084) and AML08 (NCT00703820) clinical trials: AML02 low-dose ara-C (LDAC arm, n = 91), AML02 + AML08 high-dose ara-C (HDAC arm, n = 194), and AML08 clofarabine + ara-C (Clo/ara-C arm, n = 105) induction I regimens.

Results:

Within the low-ACS10 score (≤0) group, significantly improved EFS and OS were observed among patients treated with Clo/ara-C as compared with LDAC (EFS, HR = 0.45; 95% CI, 0.23–0.88; P = 0.020; OS, HR = 0.44; 95% CI, 0.19–0.99; P = 0.048). In contrast, within the high-ACS10 score group (score >0), augmentation with Clo/ara-C was not favorable as compared with LDAC (Clo/ara-C vs. LDAC, EFS, HR = 1.95; 95% CI, 1.05–3.63; P = 0.035; OS, HR = 2.10; 95% CI, 0.96–4.59; P = 0.063). Personalization models predicted 9% improvement in the outcome in ACS10 score–based tailored induction (Clo/ara-C for low and LDAC for high-ACS10 score groups) as compared with nonpersonalized approaches (P < 0.002).

Conclusions:

Our findings suggest that tailoring induction regimens using ACS10 scores can significantly improve outcomes in patients with AML. Given the SNPs are germline, preemptive genotyping can accelerate matching the most effective remission induction regimen.
Harnessing Artificial Intelligence for the Detection and Management of Colorectal Cancer Treatment
Authors: Jacob Michael , Reddy Ruhananhad P. , Garcia Ricardo I. , Reddy Aananya P. , Khemka Sachi , Roghani Aryan Kia , Pattoor Vasanthkumar , Sehar Ujala , Reddy P. Hemachandra
Published: July 2024

Currently, eight million people in the United States suffer from cancer and it is a major global health concern. Early detection and interventions are urgently needed for all cancers, including colorectal cancer. Colorectal cancer is the third most common type of cancer worldwide. Based on the diagnostic efforts to general awareness and lifestyle choices, it is understandable why colorectal cancer is so prevalent today. There is a notable lack of awareness concerning the impact of this cancer and its connection to lifestyle elements, as well as people sometimes mistaking symptoms for a different gastrointestinal condition. Artificial intelligence (AI) may assist in the early detection of all cancers, including colorectal cancer. The usage of AI has exponentially grown in healthcare through extensive research, and since clinical implementation, it has succeeded in improving patient lifestyles, modernizing diagnostic processes, and innovating current treatment strategies. Numerous challenges arise for patients with colorectal cancer and oncologists alike during treatment. For initial screening phases, conventional methods often result in misdiagnosis. Moreover, after detection, determining the course of which colorectal cancer can sometimes contribute to treatment delays. This article touches on recent advancements in AI and its clinical application while shedding light on why this disease is so common today.