bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model
Authors: Cao Yinping , Fang Fengying , Wang Guowei , Zhu Wenyu , Hu Yijie
Published: October 2024

Coiled tubing has been widely used in oilfield development because it can significantly improve oil well productivity and recovery efficiency. However, with the increase in fracturing, drilling, and sand-washing operations, the erosion of coiled tubing walls caused by solid particles has become one of the main failure modes. To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. The results show that the main influencing factors for coiled tubing erosion rate are impact velocity, impact angle, and sand concentration. In addition, the SSA-BPNN model shows a high goodness of fit (R) and a good fit with the experimental data. The SSA-BPNN model underwent standard statistical validation tests, effectively predicting the erosion rate of coiled tubing with a high coefficient of determination and low errors, demonstrating a robust consistency between predicted and actual values. This study is of great significance to oilfield engineers, pipeline designers, and oilfield developers, and provides effective support for optimizing oilfield development and pipeline maintenance. The main users include oil companies, engineering consulting institutions and related industry personnel, and may also attract the interest of scientific research institutions and academia, providing a useful reference for the technological progress of the oil industry.
Improving a WRF-Based High-Impact Weather Forecast System for a Northern California Power Utility
Authors: Carpenter Richard L. , Gowan Taylor A. , Lillo Samuel P. , Strenfel Scott J. , Eiserloh Arthur. J. , Duffey Evan J. , Qu Xin , Capps Scott B. , Liu Rui , Zhuang Wei
Published: October 2024

We describe enhancements to an operational forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to forecast conditions in Northern and Central California for critical decision-making such as proactively de-energizing selected circuits within the power grid. WRF forecasts are routinely produced on a 2 km grid, and the results are used as input to wildfire fuel moisture, fire probability, wildfire spread, and outage probability models. This forecast system produces skillful real-time forecasts while achieving an optimal blend of model resolution and ensemble size appropriate for today’s computational resources afforded to utilities. Numerous experiments were performed with different model settings, grid spacing, and ensemble configuration to develop an operational forecast system optimized for skill and cost. Dry biases were reduced by leveraging a new irrigation scheme, while wind skill was improved through a novel approach involving the selection of Global Ensemble Forecast System (GEFS) members used to drive WRF. We hope that findings in this study can help other utilities (especially those with similar weather impacts) improve their own forecast system.
Verdiff-Net: A Conditional Diffusion Framework for Spinal Medical Image Segmentation
Authors: Zhang Zhiqing , Liu Tianyong , Fan Guojia , Pu Yao , Li Bin , Chen Xingyu , Feng Qianjin , Zhou Shoujun
Published: October 2024

Spinal medical image segmentation is critical for diagnosing and treating spinal disorders. However, ambiguity in anatomical boundaries and interfering factors in medical images often cause segmentation errors. Current deep learning models cannot fully capture the intrinsic data properties, leading to unstable feature spaces. To tackle the above problems, we propose Verdiff-Net, a novel diffusion-based segmentation framework designed to improve segmentation accuracy and stability by learning the underlying data distribution. Verdiff-Net integrates a multi-scale fusion module (MSFM) for fine feature extraction and a noise semantic adapter (NSA) to refine segmentation masks. Validated across four multi-modality spinal datasets, Verdiff-Net achieves a high Dice coefficient of 93%, demonstrating its potential for clinical applications in precision spinal surgery.
A Local Heating Profile to Manage Lower Back Pain in an Automotive Seat: A Pilot Study
Authors: Mallette Matt M. , Gur-Arie Nathaniel , Gerrett Nicola
Published: October 2024

Lower back pain (LBP) is one of the most prevalent health losses in adults worldwide. Historically, heat has been successfully used for treating pain and relieving tight muscles. Given the effective contact with the occupant’s back and proximity to the heat source, coupled with increasing commute times, automotive seats offer an opportunity to intervene. Fifteen adults (nine female) who experienced acute, subacute, and chronic lower back pain were recruited to examine the effectiveness of heat delivered to the lower back in providing temporary pain relief. Participants sat in a car seat for 38 min on two days, which included a 5-min baseline followed by a 33-min intervention; control, or localized. For the control condition, participants sat for 33 min without any thermal devices on, while the localized condition heated and maintained the seat surface temperature of the lower seat back area to ~45 °C. Over the 33-min control condition, the back skin temperature increased by ~1–2 °C and did not impact the subjective LBP. Heating the lower back for 33 min to ~39 °C reduced the subjective LBP by 10%. We demonstrated that lower back pain can be alleviated from an automotive seat providing heat to the lower back within normal commute times in those with lower back pain.
Metabolic and Proteomic Profiling of Coronary Microvascular Dysfunction: Insights from Rat Models
Authors: Lu Yan , Wang Yuying , Xin Qiqi , Yuan Rong , Chen Keji , Chu Jianfeng , Cong Weihong
Published: October 2024

Coronary microvascular dysfunction (CMD) represents a principal etiological factor in ischemic heart disease. Nonetheless, a considerable subset of CMD patients experiences diagnostic delays attributable to the inadequacy of current diagnostic methodologies; which in turn results in deferred therapeutic interventions and elevated mortality rates. This study seeks to elucidate the distinct metabolic profile associated with CMD in rat models and to identify specific diagnostic markers that could enhance the diagnostic accuracy for CMD. In this study, 18 Wistar rats were randomly allocated into two groups: the sham group and the CMD group. The CMD group received injections of embolic microspheres into the left ventricle to establish a CMD model. Subsequently, non-targeted metabolomics and acetylated proteomics analyses were conducted. Machine-learning techniques were employed to identify the co-diagnostic markers of the disease. This study identified 53 key proteins through differential expression proteins (DEPs) and modular proteins analysis. Subsequently, four core proteins (Emc1; Ank1; Fbln2; and Hp) were determined as diagnostic markers for CMD using lasso regression, support vector machine, and random forest methodologies. Receiver operating characteristic curve analysis further demonstrated robust diagnostic performance. Gene ontology and kyoto encyclopedia of genes and genome enrichment analyses indicated that the DEPs were predominantly associated with metabolic pathways. Ultimately, the integrative analysis of proteomics and metabolomics suggested that the central metabolic mechanism underlying CMD pathogenesis may be linked to the tricarboxylic acid cycle. This study revealed specific changes in the proteomic and metabolic profiles of CMD rats and identified four diagnostic markers, which are proteins and metabolites that could be potential diagnostic biomarkers for CMD.
How Do ROS Induce NETosis? Oxidative DNA Damage, DNA Repair, and Chromatin Decondensation
Authors: Azzouz Dhia , Palaniyar Nades
Published: October 2024

Neutrophil extracellular traps (NETs) are intricate, DNA-based, web-like structures adorned with cytotoxic proteins. They play a crucial role in antimicrobial defense but are also implicated in autoimmune diseases and tissue injury. The process of NET formation, known as NETosis, is a regulated cell death mechanism that involves the release of these structures and is unique to neutrophils. NETosis is heavily dependent on the production of reactive oxygen species (ROS), which can be generated either through NADPH oxidase (NOX) or mitochondrial pathways, leading to NOX-dependent or NOX-independent NETosis, respectively. Recent research has revealed an intricate interplay between ROS production, DNA repair, and NET formation in different contexts. UV radiation can trigger a combined process of NETosis and apoptosis, known as apoNETosis, driven by mitochondrial ROS and DNA repair. Similarly, in calcium ionophore-induced NETosis, both ROS and DNA repair are key components, but only play a partial role. In the case of bacterial infections, the early stages of DNA repair are pivotal. Interestingly, in serum-free conditions, spontaneous NETosis occurs through NOX-derived ROS, with early-stage DNA repair inhibition halting the process, while late-stage inhibition increases it. The intricate balance between DNA repair processes and ROS production appears to be a critical factor in regulating NET formation, with different pathways being activated depending on the nature of the stimulus. These findings not only deepen our understanding of the mechanisms behind NETosis but also suggest potential therapeutic targets for conditions where NETs contribute to disease pathology.
The Role of Keeving in Modulating Fermentation and the Flavour Profiles of Apple Brandy
Authors: Januszek Magdalena , Satora Paweł , Pater Aneta , Wajda Łukasz
Published: October 2024

Keeving is the removal of nutrients from apple musts due to their binding to pectin, resulting in a slower fermentation and spontaneous arrest. The aim of this study was to determine the effect of keeving on the chemical composition of fermented apple must and on the volatile profile and sensory analysis of apple brandies. We compared the application of keeving during spontaneous fermentation with fermentation carried out by Saccharomyces cerevisiae (SafSpirit HG-1). We evaluated the impact of adding different doses of calcium chloride on various parameters of fermented musts and distillates. Calcium chloride had a greater effect on the ethanol concentration, total extract, and fermentation efficiency than on the type of fermentation used. However, a different phenomenon was observed with respect to the volatiles. The concentration of most of the higher alcohols, acetaldehyde, dodecanal, and geranylaceton, decreased after spontaneous fermentation and increased during the fermentation carried out with Saccharomyces cerevisiae SafSpirit HG-1. In general, the application of keeving contributed to a decrease in the concentration of ethyl and methyl esters, but caused an increase in the concentration of all acetate esters and terpenoids. When the amount of nutrients in the environment is limited and starvation occurs, microorganisms use the available nutrients for basic metabolic processes that allow them to survive and limit the formation of side metabolites such as volatiles. However, most of the samples fermented after the faecal depletion achieved high scores for the floral, fruity, and “overall note” parameters in the sensory analysis. This means that this method, carried out with a properly selected yeast strain, could be feasible for the distilling industry.
Real-World Experience in the Clinical Use of Pirfenidone in Patients with Idiopathic Pulmonary Fibrosis in Taiwan: A Post-Marketing Surveillance Study
Authors: Kuo Ping-Hung , Tu Chih-Yen , Chen Chia-Hung , Kao Kuo-Chin , Hsu Jeng-Yuan , Lin Meng-Chih , Chong Inn-Wen , Sheu Chau-Chyun
Published: October 2024

Background: Idiopathic pulmonary fibrosis (IPF) is a serious, progressive lung disease for which treatments are scarce. Pirfenidone has been approved for the treatment of IPF in Taiwan since 2016. This study aimed to gain a better insight into pirfenidone’s real-world safety and effectiveness in adult IPF patients in Taiwan. Methods: We conducted a prospective, multicenter, post-marketing surveillance study, and analyzed data from a small sample of 50 IPF patients treated with pirfenidone. Results: Most patients were men, with a mean age of 72.8 years (±10.3). They were in physiology stage I or II with a baseline mean forced vital capacity (FVC) of 2.236 L (73.8% of predicted value). After treatment with pirfenidone, the mean FVC decreased by 0.088 L at week 24 and 0.127 L at week 52. The mean 6 min walk test was 325.5 m at baseline, increased by 8.1 m at week 24, but then decreased by 23.0 m at week 52. These changes from baseline did not reach statistical significance. Pirfenidone prevented worsening of cough but did not stabilize dyspnea. During 52 weeks of treatment, the incidence of total adverse drug reactions was 62.0%, with decreased appetite (32.0%) and pruritis (10.0%) being the most common. The adverse events leading to treatment discontinuation were decreased appetite (8.0%), nausea (4.0%), and respiratory failure (4.0%). No safety concern was raised by the study. Treatment with pirfenidone stabilized both FVC and the subjective symptom of cough in most patients. Conclusions: This post-marketing surveillance study demonstrated that pirfenidone is an effective, safe, and well-tolerated treatment in patients with IPF in Taiwan.
Causal Relationship Between Sjögren’s Syndrome and Gut Microbiota: A Two-Sample Mendelian Randomization Study
Authors: Wang Xinrun , Liu Minghui , Xia Weiping
Published: October 2024

Background: Gut microbiota have been previously reported to be related to a variety of immune diseases. However, the causal connection between Sjögren’s syndrome (SS) and gut microbiota has yet to be clarified. Methods: We employed a two-sample Mendelian randomization (MR) analysis to evaluate the causal connection between gut microbiota and SS, utilizing summary statistics from genome-wide association studies (GWASs) obtained from the MiBioGen and FinnGen consortia. The inverse variance weighted (IVW) approach represents the primary method of Mendelian randomization (MR) analysis. Sensitivity analysis was used to eliminate instrumental variables heterogeneity and horizontal pleiotropy. In addition, we performed an analysis using independent GWAS summary statistics for SS from the European Bioinformatics Institute (EBI) dataset for further verify our results. Results: IVW results demonstrated that the phylum Lentisphaerae (OR = 0.79, 95% CI: 0.63–0.99, p = 0.037), class Deltaproteobacteria (OR = 0.67, 95% CI: 0.47–0.96, p = 0.030), family Porphyromonadaceae (OR = 0.60, 95% CI: 0.38–0.94, p = 0.026), genus Eubacterium coprostanoligenes group (OR = 0.61, 95% CI: 0.4–0.93, p = 0.021), genus Blautia (OR = 0.62, 95% CI: 0.43–0.90, p = 0.012), genus Butyricicoccus (OR = 0.61, 95% CI: 0.42–0.90, p = 0.012), genus Escherichia.Shigella (OR = 0.7, 95% CI: 0.49–0.99, p = 0.045) and genus Subdoligranulum (OR = 0.61, 95% CI: 0.44–0.86, p = 0.005) exhibited protective effects on SS. Relevant heterogeneity of horizontal pleiotropy or instrumental variables was not detected. Furthermore, repeating our results with an independent cohort provided by the EBI dataset, only the genus Eubacterium coprostanoligenes group remained significantly associated with the protective effect on SS (OR = 0.41, 95% CI: 0.18–0.91, p = 0.029). Two-step MR analysis further revealed that genus Eubacterium coprostanoligenes group exerts its protective effect by reducing CXCL6 levels in SS (OR, 0.87; 95% CI = 0.76–0.99, p = 0.033). Conclusions: Our study using two-sample MR analysis identified a causal association between multiple genera and SS. A two-step MR result calculated that genus Eubacterium coprostanoligenes group mediated its protective effect by reducing CXCL6 levels in SS. However, the datasets available from the MiBioGen and FinnGen consortia do not provide sufficient information or comprehensive demographic data for subgroup analyses. Additional validation using various omics technologies is necessary to comprehend the development of SS in the intricate interplay between genes and the environment over a period of time.
Prediction of Thrombus Formation within an Oxygenator via Bioimpedance Analysis
Authors: Korte Jan , Lauwigi Tobias , Herzog Lisa , Theißen Alexander , Suchorski Kai , Strudthoff Lasse J. , Focke Jannis , Jansen Sebastian V. , Gries Thomas , Rossaint Rolf , Bleilevens Christian , Winnersbach Patrick
Published: October 2024

Blood clot formation inside the membrane oxygenator (MO) remains a risk in extracorporeal membrane oxygenation (ECMO). It is associated with thromboembolic complications and normally detectable only at an advanced stage. Established clinical monitoring techniques lack predictive capabilities, emphasizing the need for refinement in MO monitoring towards an early warning system. In this study, an MO was modified by integrating four sensor fibers in the middle of the hollow fiber mat bundle, allowing for bioimpedance measurement within the MO. The modified MO was perfused with human blood in an in vitro test circuit until fulminant clot formation. The optical analysis of clot residues on the extracted hollow fibers showed a clot deposition area of 51.88% ± 14.25%. This was detectable via an increased bioimpedance signal with a significant increase 5 min in advance to fulminant clot formation inside the MO, which was monitored by the clinical gold standard (pressure difference across the MO (dp-MO)). This study demonstrates the feasibility of detecting clot growth early and effectively by measuring bioimpedance within an MO using integrated sensor fibers. Thus, bioimpedance may even outperform the clinical gold standard of dp-MO as a monitoring method by providing earlier clot detection.
Strategic Integration: A Cross-Disciplinary Review of the fNIRS-EEG Dual-Modality Imaging System for Delivering Multimodal Neuroimaging to Applications
Authors: Chen Jiafa , Yu Kaiwei , Bi Yifei , Ji Xing , Zhang Dawei
Published: October 2024

Background: Recent years have seen a surge of interest in dual-modality imaging systems that integrate functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to probe brain function. This review aims to explore the advancements and clinical applications of this technology, emphasizing the synergistic integration of fNIRS and EEG. Methods: The review begins with a detailed examination of the fundamental principles and distinctive features of fNIRS and EEG techniques. It includes critical technical specifications, data-processing methodologies, and analysis techniques, alongside an exhaustive evaluation of 30 seminal studies that highlight the strengths and weaknesses of the fNIRS-EEG bimodal system. Results: The paper presents multiple case studies across various clinical domains—such as attention-deficit hyperactivity disorder, infantile spasms, depth of anesthesia, intelligence quotient estimation, and epilepsy—demonstrating the fNIRS-EEG system’s potential in uncovering disease mechanisms, evaluating treatment efficacy, and providing precise diagnostic options. Noteworthy research findings and pivotal breakthroughs further reinforce the developmental trajectory of this interdisciplinary field. Conclusions: The review addresses challenges and anticipates future directions for the fNIRS-EEG dual-modal imaging system, including improvements in hardware and software, enhanced system performance, cost reduction, real-time monitoring capabilities, and broader clinical applications. It offers researchers a comprehensive understanding of the field, highlighting the potential applications of fNIRS-EEG systems in neuroscience and clinical medicine.
Field Investigation on the Thermal Environment and Comfort of People Exercising in a Fitness Center
Authors: Wang Haiying , Hao Yongwang , Lin Huxiang , Hou Rongfu , Gong Kefei
Published: October 2024

A favorable thermal environment in fitness centers is important to attract more members and is beneficial to the health of exercising people. The purpose of this study was to research the actual thermal environment of a typical fitness center in different seasons and the thermal requirement of exercising people. A field investigation covering winter, spring, and summer was conducted. The environmental parameters were measured. Subjective questionnaires involving individual information, clothing insulation, thermal sensation, etc., were collected. Participants’ heart rates were tested to estimate their metabolic rate (MR). A total of 740 valid questionnaires were collected. The results showed that a scissors gap existed between the predictive mean vote (PMV) and the thermal sensation vote (TSV) for the exercising people. For the higher MR group, there was a separation between the TSV and thermal preference vote, e.g., most participants would not prefer to cooler or warmer thermal environment when they felt hot or cold. The CO2 concentration changed greatly among seasons and the distribution in the fitness center was not uniform. With mechanical ventilation, the CO2 concentration in summer was the lowest. In other seasons it became much higher due to limited natural ventilation. However, subjective response to indoor air quality showed no significant difference among seasons. The participants felt more satisfied to the overall thermal environment in the transition season. The results can be referenced in the thermal environment management in fitness centers during seasonal changes.
Functional Assessments of Gynecologic Cancer Models Highlight Differences Between Single-Node Inhibitors of the PI3K/AKT/mTOR Pathway and a Pan-PI3K/mTOR Inhibitor, Gedatolisib
Authors: Broege Aaron , Rossetti Stefano , Sen Adrish , Menon Arul S. , MacNeil Ian , Molden Jhomary , Laing Lance
Published: October 2024

Background/Objectives: The PI3K/AKT/mTOR (PAM) pathway is frequently activated in gynecological cancers. Many PAM inhibitors selectively target single PAM pathway nodes, which can lead to reduced efficacy and increased drug resistance. To address these limitations, multiple PAM pathway nodes may need to be inhibited. Gedatolisib, a well-tolerated panPI3K/mTOR inhibitor targeting all Class I PI3K isoforms, mTORC1 and mTORC2, could represent an effective treatment option for patients with gynecologic cancers. Methods: Gedatolisib and other PAM inhibitors (e.g., alpelisib, capivasertib, and everolimus) were tested in endometrial, ovarian, and cervical cancer cell lines by using cell viability, cell proliferation, and flow cytometry assays. Xenograft studies evaluated gedatolisib in combination with a CDK4/6 inhibitor (palbociclib) or an anti-estrogen (fulvestrant). A pseudo-temporal transcriptomic trajectory of endometrial cancer clinical progression was computationally modeled employing data from 554 patients to correlate non-clinical studies with a potential patient group. Results: Gedatolisib induced a substantial decrease in PAM pathway activity in association with the inhibition of cell cycle progression and the decreased cell viability in vitro. Compared to single-node PAM inhibitors, gedatolisib exhibited greater growth-inhibitory effects in almost all cell lines, regardless of the PAM pathway mutations. Gedatolisib combined with either fulvestrant or palbociclib inhibited tumor growth in endometrial and ovarian cancer xenograft models. Conclusions: Gedatolisib in combination with other therapies has shown an acceptable safety profile and promising preliminary efficacy in clinical studies with various solid tumor types. The non-clinical data presented here support the development of gedatolisib combined with CDK4/6 inhibitors and/or hormonal therapy for gynecologic cancer treatment.
Fusing Artificial Intelligence and Machine Learning for Anti-Cancer Drug Discovery
Authors: Adamopoulos Christos , Papavassiliou Kostas A. , Papavassiliou Athanasios G.
Published: October 2024

The integration of artificial intelligence (AI) and machine learning (ML) in modern oncology is rapidly transforming cancer drug discovery and development [...]
A Highly Efficient Catalytic Co-Combustion of Aromatic and Oxygenated Volatile Organic Compounds (VOCs) via H2-Driven Onsite Heating
Authors: Munsif Sehrish , Ullah Lutf , Cao Long , Murthy Palle Ramana , Zhang Jing-Cai , Li Wei-Zhen
Published: October 2024

Catalytic combustion, a highly efficient technique for reducing volatile organic compounds (VOCs), is the focus of this study. We investigate the improved catalytic efficiency of the physical mixing of nanosized Pt and atomically dispersed Co, supported on Al2O3 catalysts (Pt-Co)/Al2O3 (PM) for the catalytic combustion of VOCs. The catalyst efficiency is evaluated for the hydrogen-assisted catalytic oxidation of various VOCs, including aromatic and oxygenated VOCs such as benzene, toluene, methanol, and formic acid. Our study aims to understand the impact of hydrogen incorporation on the combustion process of various VOCs. The findings of this work underscore the potential of hydrogen-assisted catalytic ignition, which can achieve ignition at ambient temperature, a significant departure from conventional electric heating that typically requires additional energy to raise the temperature. Various characterization techniques, such as BET, STEM, and XRD, are employed to assess the structure–activity relationship of the catalyst. The optimal hydrogen concentration for complete VOC conversion is 3%. Notably, even at a lower hydrogen concentration of 2%, benzene and methanol reach an ideal ignition temperature of over 500 °C when introduced into the physically mixed catalyst. This study highlights the significant potential of hydrogen-assisted catalytic combustion, inspiring further research and offering a promising method to reduce VOCs effectively.
Sex Differences in Astrocyte Activity
Authors: Gozlan Elisa , Lewit-Cohen Yarden , Frenkel Dan
Published: October 2024

Astrocytes are essential for maintaining brain homeostasis. Alterations in their activity have been associated with various brain pathologies. Sex differences were reported to affect astrocyte development and activity, and even susceptibility to different neurodegenerative diseases. This review aims to summarize the current knowledge on the effects of sex on astrocyte activity in health and disease.
Adsorption and Sensing Properties of Ni-Modified InSe Monolayer Towards Toxic Gases: A DFT Study
Authors: Dong Jianhong , Qiu Xiaoqian , Huang Shuying , Lin Shaomin , Liu Lisha , Xiong Huihui
Published: October 2024

The emission of toxic gases from industrial production has intensified issues related to atmospheric pollution and human health. Consequently, the effective real-time monitoring and removal of these harmful gases have emerged as significant challenges. In this work, the density functional theory (DFT) method was utilized to examine the adsorption behaviors and electronic properties of the Ni-decorated InSe (Ni-InSe) monolayer when interacting with twelve gases (CO, NO, NO2, NH3, SO2, H2S, H2O, CO2, CH4, H2, O2, and N2). A comparative assessment of adsorption strength and sensing properties was performed through analyses of the electronic structure, work function, and recovery time. The results show that Ni doping enhances the electrical conductivity of the InSe monolayer and improves the adsorption capabilities for six toxic gases (CO, NO, NO2, NH3, SO2, and H2S). Furthermore, the adsorption of these gases on the Ni-InSe surface is characterized as chemisorption, as indicated by the analysis of the adsorption energy, density of states, and charge density difference. Additionally, the adsorption of CO, NO, NO2, and SO2 results in significant alterations to the bandgap of Ni-InSe, with changes of 18.65%, 11.37%, 10.62%, and −31.77%, respectively, underscoring its exceptional sensitivity. Moreover, the Ni-InSe monolayer exhibits a moderate recovery time of 3.24 s at 298 K for the SO2. Consequently, the Ni-InSe is regarded as a promising gas sensor for detecting SO2 at room temperature. This research establishes a foundation for the development of an Ni-InSe-based gas sensor for detecting and mitigating harmful gas emissions.
Evaluation of a Model of Transitional Care After Preterm Birth on Parents’ Mental Health and Self-Efficacy: A Randomized Controlled Pilot Trial
Authors: Schuetz Haemmerli Natascha , Stoffel Liliane , Schmitt Kai-Uwe , Humpl Tilman , Nelle Mathias , Stalder Odile , Cignacco Eva
Published: October 2024

Background/Objectives: Parents of premature infants experience depression, anxiety, post-traumatic stress disorder, and increased stress, which can negatively impact parent–infant relationships and infant development. To reduce negative consequences and optimally support families, we developed the Transition to Home model (TtH). In this randomized controlled pilot trial (RCT), the feasibility of performing an experimental study to analyse the effects of TtH on parental mental health over time was evaluated. Methods: The following domains were assessed: recruitment, follow-up and study burden, outcome measures used and parental mental health outcomes. We included n = 22 parent couples with their preterm infants in the control group and n = 23 in the intervention group. Depression, anxiety and post-traumatic stress disorders, parenting stress, and parental self-efficacy were assessed at five timepoints. The study burden was evaluated once at the end of the study. Results: The control and intervention groups had similar socio-demographic characteristics. The groups showed no differences in the mental health outcomes except for depression in mothers at T2 (p = 0.042) and T5 (p = 0.027) and state anxiety in fathers at T2 (p = 0.016). Conclusions: This pilot RCT established a framework for the evaluation of the TtH model of care and demonstrated the viability of the evaluation scheme. The results confirm the suitability of the RCT’s structure and the feasibility of the methods and instruments used. Minor adjustments are recommended to include a more diverse sample in future studies.
The Effects of Warm Acupuncture on the Expression of AMPK in High-Fat Diet-Induced MAFLD Rats
Authors: Lee Yumi , Choi Donghee , Park Junghye , Kim Jae Gwan , Choi Taejin , Youn Daehwan
Published: October 2024

This study investigated the effects of acupuncture and warm acupuncture on the expression and mechanism of the AMP-activated protein kinase (AMPK) signalling pathway associated with lipid accumulation in the liver tissue of rats with metabolic dysfunction-associated fatty liver disease (MAFLD) induced by a high-fat diet. Sprague–Dawley rats were categorised into four groups: control (CON), untreated MAFLD (MAFLD), and two MAFLD groups treated with acupuncture (ACU) and warm acupuncture (WA). The treatment groups underwent 16 application sessions over 8 weeks at the SP9 and BL18 acupoints. We measured the expression levels of AMPK, sterol regulatory element-binding protein1 (SREBP1), acetyl-coenzyme A carboxylase (ACC), peroxisome proliferator-activated receptorα (PPARα), carnitine palmitoyltransferase1 (CPT1), and CPT2. AMPK was activated in both ACU and WA groups. WA downregulated both SREBP1 and ACC expression at the protein level, whereas the acupuncture treatment downregulated SREBP1 expression. Additionally, WA selectively induced the activation of signalling pathways related to AMPK, PPARα, CPT1, and CPT2 at the mRNA level. Histological observations confirmed that fat accumulation was reduced in both the ACU and the WA groups compared to the MAFLD group. The WA treatment-promoted amelioration of HFD-induced MAFLD may be related to the activation of the AMPK/SREBP1/ACC pathway in the liver.
Correction: Chen et al. Preparation of Pie-Shaped CoMoO4 with High Capacitive and Photocatalytic Properties by a Solvothermal Method. Coatings 2022, 12, 1771
Authors: Chen Shuoyan , Wu Juan , Wang Gang , Wang Jing , Fan Licai , Hao Jian , Wang Shen , Liu Yang , Wu Hongyu , Li Yang , Gao Jing , Yang Mingli
Published: October 2024

Following publication, concerns were raised regarding the peer-review process related to the publication of this article [...]
Cardiac Troponin Levels in Patients with Chronic Kidney Disease: “Markers of High Risk or Just Noise’’?
Authors: Geladari Eleni V. , Vallianou Natalia G. , Evangelopoulos Angelos , Koufopoulos Petros , Panagopoulos Fotis , Margellou Evangelia , Dalamaga Maria , Sevastianos Vassilios , Geladari Charalampia V.
Published: October 2024

Kidney disease is linked to the development of cardiovascular disorders, further increasing morbidity and mortality in this high-risk population. Thus, early detection of myocardial damage is imperative in order to prevent devastating cardiovascular complications within this patient group. Over the years, cardiac biomarkers have been identified and are now widely used in everyday clinical practice. More specifically, available data suggest that cardiac troponin and its regulatory subunits (TnT, TnI, and TnC) reflect the injury and necrosis of myocardial tissue. While cTnC is identical in cardiac and skeletal muscle, TnT and TnI constitute cardiac-specific forms of troponin, and, as such, they have been established by international societies as biomarkers of cardiac damage and diagnostic indicators for acute myocardial infarction. Elevations in the levels of both cardiac troponins (cTnT and cTnI) have been also reported in asymptomatic patients suffering from chronic kidney disease. Therefore, if abnormal, they often generate confusion among clinicians regarding the interpretation and clinical significance of their numerical values in emergency settings. The aim of this review is to explore the reasons behind elevated troponin levels in patients with chronic kidney disease and identify when these elevated levels of biomarkers indicate the need for urgent intervention, considering the high cardiovascular risk in this patient group.
[89Zr]Zr-PSMA-617 PET/CT in a Patient with Biochemical Recurrence of Prostate Cancer and Prior Indetermined Findings on [18F]PSMA-1007 Imaging
Authors: Bastian Moritz B. , Burgard Caroline , Blickle Arne , Speicher Tilman , Ezziddin Samer , Rosar Florian
Published: October 2024

We report a case of a 79-year-old male patient with a history of radical prostatectomy for prostate cancer. The patient presented with biochemical reoccurrence; however, previous conventional PSMA PET/CT using [18F]PSMA-1007 showed two indetermined findings with low uptake in the right iliac lymph nodes. Further MRI evaluation provided no additional information. A recently introduced PSMA tracer, [89Zr]Zr-PSMA-617 (half-life: 3.3 days), was administered in an attempt to confirm the diagnosis and aid in potential radiation planning. [89Zr]Zr-PSMA-617 PET/CT clearly revealed the previously indetermined right iliac lymph nodes as definitely metastatic and also identified additional lymph node metastases that were undetected in prior scans. This case highlights the potential superior sensitivity of [89Zr]Zr-PSMA-617 PET/CT in detecting recurrent disease, especially in unclear settings of [18F]PSMA-1007 PET/CT and demonstrates its potential for guiding targeted radiation therapy with curative intent.
Machine Learning Diagnostic Model for Early Stage NSTEMI: Using hs-cTnI 1/2h Changes and Multiple Cardiovascular Biomarkers
Authors: Wu Junyi , Ge Yilin , Chen Ke , Chen Siyu , Yang Jiashu , Yuan Hui
Published: October 2024

Background: This study demonstrates differences in the distribution of multiple cardiovascular biomarkers between non-ST-segment elevation myocardial infarction (NSTEMI) and unstable angina (UA) patients. Diagnostic machine learning predictive models measured at the time of admission and 1/2 h post-admission, achieving competitive diagnostic predictive results. Objective: This study aims to explore the diagnostic value of changes in high-sensitivity cardiac troponin I (hs-cTnI) levels in patients with suspected NSTEMI. Methods: A total of 267 patients presented with chest pain, requiring confirmation of acute coronary syndrome (ACS) subtypes (NSTEMI vs. UA). Hs-cTnI and other cardiac markers, such as creatine kinase-MB (CK-MB) and Myoglobin (Myo), were analyzed. Machine learning techniques were employed to assess the application of hs-cTnI level changes in the clinical diagnosis of NSTEMI. Results: Levels of CK-MB, Myo, hs-cTnI measured at admission, hs-cTnI measured 1–2 h after admission, and NT-proBNP in NSTEMI patients were significantly higher than those in UA patients (p < 0.001). There was a positive correlation between hs-cTnI and CK-MB, as well as Myo (R = 0.72, R = 0.51, R = 0.60). The optimal diagnostic model, Hybiome_1/2h, demonstrated an F1-Score of 0.74, an AUROC of 0.96, and an AP of 0.89. Conclusions: This study confirms the significant value of hs-cTnI as a sensitive marker of myocardial injury in the diagnosis of NSTEMI. Continuous monitoring of hs-cTnI levels enhances the accuracy of distinguishing NSTEMI from UA. The models indicate that the Hybiome hs-cTnI assays perform comparably well to the Beckman assays in predicting NSTEMI. Moreover, incorporating hs-cTnI measurements taken 1–2 h post-admission significantly enhances the model’s effectiveness.
A Platform of Federated Learning Management for Enhanced Mobile Collaboration
Authors: Yusubov Farkhod , Lee KangYoon
Published: October 2024

Federated learning (FL) has emerged as a crucial technology in today’s data-centric environment, enabling decentralized machine learning while safeguarding user privacy. This study introduces “Federated Learning ML Operations (FedOps) Mobile”, a novel FL framework optimized for the dynamic and heterogeneous ecosystem of mobile devices. FedOps Mobile addresses the inherent challenges of FL—such as system scalability, device heterogeneity, and operational efficiency—through advanced on-device training using TensorFlow Lite and CoreML. The framework’s innovative approach includes sophisticated client selection mechanisms that assess device readiness and capabilities, ensuring equitable and efficient participation across the network. Additionally, FedOps Mobile leverages remote device control for seamless task management and continuous learning, all without compromising the user experience. The main contribution of this study is the demonstration that federated learning across heterogeneous devices, especially those using different operating systems, can be both practical and efficient using the FedOps Mobile framework. This was validated through experiments that evaluated three key areas: operational efficiency, model personalization, and resource optimization in multi-device settings. The results showed that the proposed method excels in client selection, energy consumption, and model optimization, establishing a new benchmark for federated learning in diverse and complex environments.
Innovations for Holistic and Sustainable Transitions
Authors: Koundouri Phoebe , Alamanos Angelos , Devves Stathis , Landis Conrad , Dellis Kostantinos
Published: October 2024

Energy system planning has evolved from a narrow focus on engineering and supply works towards addressing more complex, multifactorial challenges. Increasingly challenged by climate change, extreme events, economic shocks, and altered supply demand patterns, the analysis of energy systems requires holistic approaches based on data-driven models, taking into account key socio-economic factors. We draw insights from reviewing the literature, indicating the need to cover the following major gaps: the shift to transdisciplinary approaches, incorporating environmental system analysis; resilient and sustainable energy designs based on flexible portfolios of renewable mixes; the integration of socio-economic aspects, economic analyses and behavioural models to ensure energy systems are not only technically sound but socially acceptable and viable; the need for stakeholder engagement considering the human angle in energy security and behavioural shifts. Responding to these pressing challenges and emerging needs, the Global Climate Hub (GCH) initiative, operating under the UN Sustainable Development Solutions Network, offers a conceptual framework, leveraging transdisciplinary approaches. In this Concept Paper, we present for the first time the idea of the GCH as a framework that we believe has the potential to address the modern holistic needs for energy system analysis and policymaking. By setting the conceptual/theoretical ground of our suggested approach, we aim to provide guidance for innovative combinations of cutting-edge models, socio-economic narratives, and inclusive interaction with relevant stakeholders for the development and the long-term implementation of sustainable pathways.
Collaborative Governance of Stakeholders in the Payment for Forest Ecosystem Services: An SA-SNA-EGA Approach
Authors: Wei Xue , Li Hua , Chen Wenhui
Published: October 2024

Forests provide goods and services while maintaining ecological security. However, the market does not adequately reflect their economic benefits, posing a significant challenge to the Payments for Forest Ecosystem Services (PFES). The involvement of multiple stakeholders with varying responsibilities and interests complicates collaboration and hinders effective governance. This study proposes an integrated approach using stakeholder analysis, social network analysis, and evolutionary game analysis to explore the collaborative governance of stakeholders in PFES. Through field surveys, the study empirically investigates PFES in China, demonstrating the effectiveness of this integrated approach. The results indicate the following: (i) Stakeholders are classified into three categories; the key stakeholders include the central and local governments, forest managers, and paying users. (ii) Stakeholders still need to strengthen collaboration. Local governments, forest managers, their employees, and communities exert widespread influence; paying users and research institutions have high efficiency in resource sharing. (iii) Five evolutionarily stable strategies are observed at different stages. Government intervention is crucial for changing the stagnant state. Benefits and government incentives have a positive impact on stakeholder collaborative governance. The research findings offer theoretical insights to enhance stakeholder collaboration and promote the development of the PFES. Key strategies include addressing key stakeholders’ needs, diversifying incentives, and establishing an accessible information platform.
Transcriptomic and Proteomic Integration Reveals Key Tapping-Responsive Factors for Natural Rubber Biosynthesis in the Rubber Tree Hevea brasiliensis
Authors: He Lixia , Yang Yang , Ma Junjun , Yuan Boxuan , Fang Fengyan , Wang Juanying , Wang Mei , Li Aifang , Chen Jinxian , Hui Shugang , Wang Xuchu
Published: October 2024

Natural rubber is a crucial industrial material, and it is primarily harvested from the latex of the rubber tree Hevea brasiliensis by tapping the tree trunk. During the regular tapping process, mechanical damage seriously affects latex reproduction and rubber yield, but the molecular mechanisms on tapping stimulation remain unclear. In this study, we firstly determined the changed physiological markers on latex regeneration, overall latex yield, and latex flow time during the tapping process. Then, we combined proteomics and transcriptomics analyses of latex during tapping and identified 3940 differentially expressed genes (DEGs) and 193 differentially expressed proteins (DEPs). Among them, 773 DEGs and 120 DEPs displayed a persistent upregulation trend upon tapping. It is interesting that, in the detected transcription factors, basic helix-loop-helix (bHLH) family members occupied the highest proportion among all DEGs, and this trend was similarly observed in DEPs. Notably, 48 genes and 34 proteins related to natural rubber biosynthesis were identified, and most members of small rubber particle protein (SRPP) and rubber elongation factor (REF) showed a positive response to tapping stimulation. Among them, SRPP6 and REF5 showed significant and sustained upregulation at the gene and protein levels following tapping, indicating their pivotal roles for post-tapping rubber biosynthesis. Our results deepen the comprehension of the regulation mechanism underlying tapping and provide candidate genes and proteins for improving latex production in the Hevea rubber tree in future.
Boosting Health Benefits in Vegetables: A Novel Ultraviolet B (UVB) Device for Rapid At-Home Enhancement of Phytochemicals and Bioactivity
Authors: Gastélum-Estrada Alejandro , Reza-Zaldivar Edwin E. , Jacobo-Velázquez Daniel A.
Published: October 2024

The consumption of vegetables is essential for reducing the risk of noncommunicable diseases, yet global intake falls short of recommended levels. Enhancing the nutraceutical content of vegetables through postharvest abiotic stress, such as ultraviolet B (UVB) radiation, offers a promising solution to increase health benefits. This study developed a user-friendly, at-home UVB device designed to increase the phytochemical content in common vegetables like carrots, lettuce, and broccoli. The device applies UVB radiation (305–315 nm) to fresh-cut vegetables, optimizing exposure time and intensity to maximize nutraceutical enrichment. The results demonstrated that UVB exposure increased the phenolic content by 44% in carrots, 58% in broccoli, and 10% in lettuce, with chlorogenic acid levels rising by 367% in lettuce, 547% in broccoli, and 43% in carrots after 48 h of storage. UVB treatment also enhanced antioxidant activity by up to 41% in broccoli and anti-inflammatory potential by 22% in carrots. In terms of gene expression, UVB treatment upregulated UCP-1 expression by 555% in carrots, enhanced thermogenesis, and increased SIRT-1 and ATGL expression by over 200%, promoting lipid metabolism. This process provides a convenient and efficient method for consumers to boost the health benefits of their vegetables. The study concludes that UVB-induced abiotic stress is an effective strategy to improve vegetable nutritional quality, offering a novel approach to increasing bioactive compound intake and aiding in the prevention of diet-related diseases.
Evaluation of Advanced Biofuels in Internal Combustion Engines: Diesel/Fusel Oil/Vegetable Oil Triple Blends
Authors: Estevez Rafael , López-Tenllado Francisco J. , Aguado-Deblas Laura , Bautista Felipa M. , Romero Antonio A. , Luna Diego
Published: October 2024

In this research work, the feasibility of using fusel oil, a by-product of the sugar–alcohol industry, as an LVLC solvent in blends with straight vegetable oils (SVOs) and diesel was investigated. Concretely, diesel/fusel oil/sunflower oil (D/FO/SO) and diesel/fusel oil/castor oil (D/FO/CO) triple blends were prepared and characterized by measuring the most important physicochemical properties, i.e., viscosity, density, cold flow properties, flash point and cetane number. An appreciable improvement in cold flow values has been achieved with triple blends, without compromising properties such as calorific value and cetane number. Likewise, the triple blends meet the viscosity and density requirements specified by the European quality standard EN 14214 and the American standard ASTM D6751. After characterization, the triple blends were used on a diesel engine, evaluating different parameters such as power output, opacity, exhaust emissions (CO and NOx) and consumption at different engine loads. The results indicate that as the biofuel content in the blend increases, engine power decreases while fuel consumption rises. Nevertheless, the values obtained with D/FO/CO are better than those for D/FO/SO and are also very similar to those of fossil diesel. Regarding opacity values and NOx emissions obtained with the utilization of the triple blends, they are lower than those produced by diesel. However, in the case of CO emissions, it depends on the type of oil used, with the samples prepared with castor oil exhibiting the best results.