bluuebunny/crossref_metadata_2025 huggingface dataset:
Human Serum, Following Absorption of Fish Cartilage Hydrolysate, Promotes Dermal Fibroblast Healing through Anti-Inflammatory and Immunomodulatory Proteins
Authors: Le Faouder Julie , Guého Aurélie , Lavigne Régis , Wauquier Fabien , Boutin-Wittrant Line , Bouvret Elodie , Com Emmanuelle , Wittrant Yohann , Pineau Charles
Published: September 2024

Background/Objectives: Marine collagen peptides (MCPs) and glycosaminoglycans (GAGs) have been described as potential wound-healing (WH) agents. Fish cartilage hydrolysate (FCH) is a natural active food ingredient obtained from enzymatic hydrolysis which combines MCPs and GAGs. Recently, the clinical benefits of FCH supplementation for the skin, as well as its mode of action, have been demonstrated. Some of the highlighted mechanisms are common to the WH process. The aim of the study is therefore to investigate the influence of FCH supplementation on the skin healing processes and the underlying mechanisms. Methods: To this end, an ex vivo clinical approach, which takes into account the clinical digestive course of nutrients, coupled with primary cell culture on human dermal fibroblasts (HDFs) and ultra-deep proteomic analysis, was performed. The effects of human serum enriched in circulating metabolites resulting from FCH ingestion (FCH-enriched serum) were assessed on HDF WH via an in vitro scratch wound assay and on the HDF proteome via diaPASEF (Data Independent Acquisition—Parallel Accumulation Serial Fragmentation) proteomic analysis. Results: Results showed that FCH-enriched human serum accelerated wound closure. In support, proteins with anti-inflammatory and immunomodulatory properties and proteins prone to promote hydration and ECM stability showed increased expression in HDFs after exposure to FCH-enriched serum. Conclusions: Taken together, these data provide valuable new insights into the mechanisms that may contribute to FCH’s beneficial impact on human skin functionality by supporting WH. Further studies are needed to reinforce these preliminary data and investigate the anti-inflammatory and immunomodulatory properties of FCH.
Chemerin in the Spotlight: Revealing Its Multifaceted Role in Acute Myocardial Infarction
Authors: Mitsis Andreas , Khattab Elina , Myrianthefs Michael , Tzikas Stergios , Kadoglou Nikolaos P. E. , Fragakis Nikolaos , Ziakas Antonios , Kassimis George
Published: September 2024

Chemerin, an adipokine known for its role in adipogenesis and inflammation, has emerged as a significant biomarker in cardiovascular diseases, including acute myocardial infarction (AMI). Recent studies have highlighted chemerin’s involvement in the pathophysiological processes of coronary artery disease (CAD), where it modulates inflammatory responses, endothelial function, and vascular remodelling. Elevated levels of chemerin have been associated with adverse cardiovascular outcomes, including increased myocardial injury, left ventricular dysfunction, and heightened inflammatory states post-AMI. This manuscript aims to provide a comprehensive review of the current understanding of chemerin’s role in AMI, detailing its molecular mechanisms, clinical implications, and potential as a biomarker for diagnosis and prognosis. Additionally, we explore the therapeutic prospects of targeting chemerin pathways to mitigate myocardial damage and improve clinical outcomes in AMI patients. By synthesizing the latest research findings, this review seeks to elucidate the multifaceted role of chemerin in AMI and its promise as a target for innovative therapeutic strategies.
Outcome Disparities in Patients with Early-Stage Laryngeal Cancer Depending on Localization, Tobacco Consumption, and Treatment Modality
Authors: Wald Theresa , Koppe Tim-Jonathan , Pirlich Markus , Zebralla Veit , Kunz Viktor , Dietz Andreas , Stoehr Matthaeus , Wichmann Gunnar
Published: September 2024

Background/Objectives: Laryngeal squamous cell carcinoma (LSCC) is among most frequent malignancies of the head and neck. Recent oncologic research focusses on advanced rather than on early stages. Thus, we aimed to improve the knowledge concerning prognostic factors and survival in early glottic (GC) and supraglottic cancer (SGC). Methods: We retrospectively investigated patients diagnosed in 2007 to 2020 with stage I or II GC (ICD-10-C32.0) or SGC (ICD-10-C32.1, C32.8 or C32.9). For precise discrimination of GC and SGC, pathology reports about biopsy and definitive excision were closely examined and information on clinical characteristics and risk factors were collected before analyzing patterns of risk factors for overall survival (OS) in multivariate Cox regression analyses (mvCox). Results: The cohort included 220 patients with early GC (n = 183) and SGC (n = 37). The GC patients showed significantly improved 5-year OS compared to SGC patients (83.6% vs. 64.9%; p = 0.004), whereas survival according to UICC stage (I vs. II) was not different (p = 0.177). Surgical resection was superior to definitive radiotherapy (RT) for 5-year OS (p < 0.001). Cumulative tobacco consumption of greater than 10 pack years drastically impaired OS (p = 0.024), especially in patients receiving RT (p < 0.001). Supraglottic localization, smoking, and re-resection after initial R1 status consistently were independent prognostic factors in mvCox. Conclusions: Our cohort of early LSCC patients demonstrates significant negative impact of supraglottic localization, older age, tobacco consumption, poor tumor differentiation, and re-resection on OS. Further research is required as there is still lack of evidence on optimal decision-making and therapeutic strategies.
Circulating Tumor Cells: Origin, Role, Current Applications, and Future Perspectives for Personalized Medicine
Authors: Rapanotti Maria Cristina , Cenci Tonia , Scioli Maria Giovanna , Cugini Elisa , Anzillotti Silvia , Savino Luca , Coletta Deborah , Di Raimondo Cosimo , Campione Elena , Roselli Mario , Bernardini Sergio , Bianchi Luca , De Luca Anastasia , Ferlosio Amedeo , Orlandi Augusto
Published: September 2024

Circulating tumor cells (CTCs) currently represent a revolutionary tool offering unique insights for the evaluation of cancer progression, metastasis, and response to therapies. Indeed, CTCs, upon detachment from primary tumors, enter the bloodstream and acquire a great potential for their use for personalized cancer management. In this review, we describe the current understanding of and advances in the clinical employment of CTCs. Although considered rare and fleeting, CTCs are now recognized as key players favoring the development of cancer metastasis and disease recurrence, particularly in malignant melanoma, lung, breast, and colorectal cancer patients. To date, the advancements in technology and the development of several successful approaches, also including immunomagnetic enrichment allow for a reliable and reproducible detection and characterization of CTCs. Those innovative methodologies improved the isolation, quantification, and characterization of CTCs from the blood of cancer patients, providing extremely useful evidence and new insights into the nature of the tumor, its epithelial/mesenchymal profile, and its potential resistance to therapy. In fact, in addition to their prognostic and predictive value, CTCs could serve as a valuable instrument for real-time monitoring of treatment response and disease recurrence, facilitating timely interventions and thus improving patient outcomes. However, despite their potential, several challenges hinder the widespread clinical utility of CTCs: (i) CTCs’ rarity and heterogeneity pose technical limitations in isolation and characterization, as well as significant hurdles in their clinical implementation; (ii) it is mandatory to standardize CTC detection methods, optimize the sample processing techniques, and integrate them with existing diagnostic modalities; and (iii) the need for the development of new techniques, such as single-cell analysis platforms, to enhance the sensitivity and specificity of CTC detection, thereby facilitating their integration into routine clinical practice. In conclusion, CTCs represent a potential extraordinary tool in cancer diagnostics and therapeutics, offering unprecedented opportunities for personalized medicine and precision oncology. Moreover, their ability to provide real-time insights into tumor biology, treatment response, and disease progression underlines a great potential for their clinical application to improve patients’ outcomes and advance our understanding of cancer biology.
Breaking the Cycle of Pain: The Role of Graded Motor Imagery and Mirror Therapy in Complex Regional Pain Syndrome
Authors: Donati Danilo , Boccolari Paolo , Giorgi Federica , Berti Lisa , Platano Daniela , Tedeschi Roberto
Published: September 2024

Background: Complex Regional Pain Syndrome (CRPS) is a chronic condition characterized by severe pain and functional impairment. Graded Motor Imagery (GMI) and Mirror Therapy (MT) have emerged as potential non-invasive treatments; this review evaluates the effectiveness of these therapies in reducing pain, improving function, and managing swelling in CRPS patients. Methods: A systematic review was conducted including randomized controlled trials (RCTs) that investigated GMI and MT in CRPS patients. This review was registered in PROSPERO (CRD42024535972) to ensure transparency and adherence to protocols. This review included searches of PubMed, Cochrane, SCOPUS, and Web of Science databases. Out of 81 studies initially screened, 6 were included in the final review. Studies were assessed for quality using the PEDro and RoB-2 scales. The primary outcomes were pain reduction, functional improvement, and swelling reduction. Results: Graded Motor Imagery (GMI) and Mirror Therapy (MT) reduced pain by an average of 20 points on the Neuropathic Pain Scale (NPS) and resulted in functional improvements as measured by the Task-Specific Numeric Rating Scale (NRS). GMI also contributed to some reduction in swelling. MT, particularly in post-stroke CRPS patients, showed significant pain reduction and functional improvements, with additional benefits in reducing swelling in certain studies. However, the included studies had small sample sizes and mixed designs, which limit the generalizability of the findings. The studies varied in sample size and design, with some risk of bias noted. Conclusions: Graded Motor Imagery (GMI) and Mirror Therapy (MT) have proven to be effective interventions for managing Complex Regional Pain Syndrome (CRPS), with significant improvements in pain reduction and functional recovery. These non-invasive treatments hold potential for integration into standard rehabilitation protocols. However, the small sample sizes and variability in study designs limit the generalizability of these findings. Future research should focus on larger, more homogeneous trials to validate the long-term effectiveness of GMI and MT, ensuring more robust clinical application.
Perfectionism and Emotion Regulation in the Study of Suicidal Ideation in Portuguese Young Adults
Authors: Brás Marta , Antunes João , Reis Ana , Carmo Cláudia
Published: September 2024

Suicide is a serious public health problem worldwide, being the culmination of a process that normally begins with suicidal ideation. Therefore, it is important to assess suicidal ideation and know its risk factors. The association between perfectionism and suicidal ideation has been widely debated in the literature. However, knowledge about the role of emotion regulation in this relationship is scarce. The main objective of this investigation was thus to study the role of emotion regulation in the relationship between perfectionism and suicidal ideation in young adults. A sample of 224 Portuguese young adults was recruited through an online form which assessed suicidal ideation, perfectionism, and emotion regulation. The results showed a positive relationship between suicidal ideation and emotion regulation difficulties. There was also a positive association between emotion regulation difficulties and perfectionism, especially regarding the strategies and dimensions of maladaptive perfectionism. The relationship between perfectionism and suicidal ideation was fully mediated by emotion regulation difficulties. Increases in emotion regulation difficulties from increased perfectionism could contribute decisively to increasing the risk of suicidal ideation. Thus, the assessment of perfectionism and emotion regulation difficulties can promote the prevention and psychological interventions for suicidal behavior.
The Effect of Time Display Format on Cognitive Performance of Integrated Meteorological Radar Information
Authors: Liu Bo , Wang Yunhe , Li Yongxin
Published: September 2024

A proper time display format is essential for pilots to understand integrated meteorological radar information, thereby making informed flying decisions and steering clear of hazardous weather. Previous studies on time display format supported the advantages of digital format, while some studies found that analog clock format is superior to digital format. This study explored the effect of time display format on the cognitive performance of integrated meteorological radar information through two experiments. Experiment 1 first examined the effects of digital and analog clock displays on the timing of individual processing advance or delay changes in a general scenario. Then, Experiment 2 was conducted in a simulated flight scenario to investigate the advantages and disadvantages of digital and analog clock display in delay time processing with and without time pressure. The results showed the following: (1) Analog clock has more advantages than digital display format in processing the varying time difference. (2) Whether with or without time pressure, analog clock is more conducive to individual cognition of integrated meteorological radar information than digital time display. (3) The length of delay time is an important factor affecting individual time cognition, and it can also affect the cognition of radar information. The longer the delay time, the more difficult it is to identify the time and understand the information. These findings provide a certain reference for the design of the integrated meteorological radar information display interface.
Exploring the Impact and Prevention of Epidemics Based on Inter-Animal Transmission from an Environmental Perspective
Authors: Liao Yuxuan , Jia Yonghong , Guo Luyao , Cheng Zhu , Jiang Xingchi , Hu Wenxin , Long Enshen
Published: September 2024

Respiratory infectious diseases are more likely to occur in indoor environments. Therefore, the probability of transmission when sharing the same indoor space with an infected individual for a certain period of time has an impact on the response measures to influenza outbreaks. The experimental methods for studying indoor transmission risks present significant operational challenges. Hence, to accurately predict the process of virus transmission in human living environments, it is crucial to use animal experiments in controlled environments. This study extensively reviews classical documents, taking into account exposure methods as well as environmental factors such as temperature, humidity, viral release intensity, and ventilation frequency. Based on the reference to animal experiments, the analogy law between the animal experiment environment and the human living environment is put forward. For human society, a dynamic respiratory infectious disease model that takes environmental factors into account is developed. The incidence probability of susceptible populations and the law of respiratory virus transmission at a certain time and space are explored. Ultimately, the statistical analysis revealed that temperature and susceptible people, followed by humidity and ventilation frequency, are the most sensitive factors influencing disease outbreak. In conclusion, this research provides a new reference model for predicting the spread of respiratory infectious diseases. It expands the application scope of animal experiments and offers guidance for setting environmental factors in animal virus transmission experiments, assessing the likelihood of infection in human living environments, guiding human behavior, and preparing for future virus outbreaks.
A Study on Improving the Shape Error of the Lower Mold of Free-Form Concrete Panels Using Magnetic Force
Authors: Kim Jihye , Youn Jongyoung , Jo Minje , Jeong Kyeongtae , Lee Jaesung , Lee Donghoon
Published: September 2024

FCPs (free-form concrete panels) can be made using reusable and easily customizable silicone molds tailored to the unique shape of each panel. CNC (Computer Numerical Control)-type rods move vertically to press the silicone plate and shape the lower curved surface. Silicone caps are attached to the ends of the rods to facilitate the formation of smooth curves. However, there is currently no fixing method for the silicone caps and the silicone plate, which makes them vulnerable to the lateral pressure exerted during concrete pouring. Therefore, the current study used magnetic force to improve the lower shape of free-form molds. To this end, a neodymium silicone cap was designed by adding a neodymium magnet to the upper surface of the silicone cap. Moreover, two types of silicone plates were developed for fixing: one type is IS-LSM (Iron Sheet–Silicone Mold), which includes an iron sheet, while the other type is IP-LSM (Iron Powder–Silicone Mold), which is made by mixing iron powder. To verify these two techniques, FCP manufacturing experiments were conducted. The experimental results indicated that IS-LSM had a broader error range than existing techniques, thus rendering it unusable, while IP-LSM yielded significant values. Consequently, a t-test was conducted to validate the data for IP-LSM at 30%, 50%, and 70%, and it was confirmed that the difference in error data was significant at a 95% confidence level. Future research in this area should investigate the addition of iron powder to the silicone plate and a side fixing method for the silicone mold. Such research would help advance the production technology of free-form concrete panels.
Assessment of Reinforcement Steel–Concrete Interface Contact in Pullout and Beam Bending Tests Using Test-Fitted Cohesive Zone Parameters
Authors: Santana Paulo Fernando Matos , Evangelista Junior Francisco , Oliveira Marcos Honorato
Published: September 2024

Modeling the steel-concrete interface is a constant research topic in structural engineering. Several studies have explored advanced modeling methods, including cohesive models. This article fits into this context by investigating the bond strength at the steel-concrete interface based on a cohesive model. The numerical parameters considered in the software ABAQUS 2019 are investigated. The experimental and numerical results of pullout and beam tests were used as references for the parameters fitting process. With the Concrete Damaged Plasticity model (CDP), the physical non-linearity of the concrete was considered. The contact was described as a surface-to-surface interaction. The pullout tests’ cohesive parameters were fitted with experimental tests. Regarding the beam models, an analysis was carried out verifying the use of pullout fitting parameters in the beam models, aiming to compensate for the eventual absence of these data. For the pullout models, the cohesive parameters fitting process yielded better results than those obtained with the recommended values. Improvements were especially significant regarding slippage at the maximum pullout force. The use of pullout test-fitted parameters in the beam models had a smaller influence on the ultimate load predictions. However, the slippage predictions and beam deflection were more affected by the change in cohesive parameters. The bond modeling using a surface-based technique performed well at a low computational cost, considering the materials’ physical nonlinearities and 3D geometries. The results, also in general, did not significantly change the load predictions, which indicates a possibility of use in numerical simulations when the pullout data is available.
Analysis of HER2-Low Breast Cancer in Aotearoa New Zealand: A Nationwide Retrospective Cohort Study
Authors: Lasham Annette , Ramsaroop Reenadevi , Wrigley Abbey , Knowlton Nicholas
Published: September 2024

Objectives: To perform the first national analysis of demographic and clinicopathological features associated with the HER2 positive, HER2-low, and HER2-zero invasive breast cancers in New Zealand. The study will reveal the proportion of women who may benefit from new HER2-targeted antibody drug conjugate (ADC) therapies. Methods: Utilising data from Te Rēhita Mate Ūtaetae (Breast Cancer Foundation NZ National Register), the study analysed data from women diagnosed with invasive breast cancer over a 21-year period. The HER2 status of tumours was classified into three categories—HER2-zero, HER2-low, HER2-positive. Results: From 2009–2021, 94% of women underwent HER2 testing, with 14% diagnosed with HER2-positive breast cancer. For advanced-stage disease, 38% of those formerly classified as HER2-negative were reclassified as HER2-low. Including HER2-positive breast cancers, this indicates that 60% of women with advanced breast cancer may potentially benefit from the new HER2-directed ADCs (approximately 120 women per year). Conclusions: The findings suggest a significant proportion of women with invasive breast cancer in New Zealand could benefit from new HER2-targeted treatments. There is a need to standardise HER2 testing to enhance personalised treatment and improve outcomes.
A Study of Disease Prognosis in Lung Adenocarcinoma Using Single-Cell Decomposition and Immune Signature Analysis
Authors: Lee Cheng-Yang , Wu Yu-Chung , Liao Tze-Chi , Hsiao Shih-Hsin , Hsu Justin Bo-Kai , Chang Tzu-Hao
Published: September 2024

Background: The development of tumors is a highly complex process that entails numerous interactions and intricate relationships between the host immune system and cancer cells. It has been demonstrated in studies that the treatment response of patients can be correlated with the tumor microenvironment (TME). Consequently, the examination of diverse immune profiles within the TME can facilitate the elucidation of tumor development and the development of advantageous models for diagnoses and prognoses. Methods: In this study, we utilized a single-cell decomposition method to analyze the relationships between cell proportions and immune signatures in lung adenocarcinoma (LUAD) patients. Results: Our findings indicate that specific immune cell populations and immune signatures are significantly associated with patient prognosis. By identifying poor prognosis signatures (PPS), we reveal the critical role of immune profiles and cellular composition in disease outcomes, emphasizing their diagnostic potential for predicting patient prognosis. Conclusions: This study highlights the importance of immune signatures and cellular composition, which may serve as valuable biomarkers for disease prognosis in LUAD patients.
New Catalysts and Reactors for the Synthesis or Conversion of Methanol
Authors: Soler Jaime
Published: September 2024

Energy storage is a critical issue in the development of an economy based on the use of renewable energy [...]
Biodiesel Synthesis from Date Seed Oil Using Camel Dung as a Novel Green Catalyst: An Experimental Investigation
Authors: Alsaiari Raiedhah A. , Musa Esraa M. , Rizk Moustafa A.
Published: September 2024

Biodiesel is seen as more environmentally benign than petroleum-based fuels. It is also cheaper and capable of creating cleaner energy, which has a good impact on increasing the bioeconomy. An investigation was conducted on a novel heterogeneous catalyst system utilized in the synthesis of eco-friendly biodiesel from date seed oil, a non-edible feedstock obtained through the calcination of desiccated camel manure at varying temperatures. X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, and scanning electron microscopy (SEM) were utilized to characterize this catalyst. As a result of raising the calcination temperature, the results showed that the pore size of the catalyst decreased. The biodiesel production was optimized to be 86% by using the transesterification method. The optimal reaction parameters included a catalyst with 4% loading, a molar ratio of 1:8 between date seed oil and ethanol, and a temperature of 75 °C for a reaction period of three hours. The confirmation of FAME generation was achieved by gas chromatography–mass spectrometry (GC–MS). The fuel qualities of fatty acid ethyl ester are in accordance with ASTM, suggesting that it is a suitable alternative fuel option. Utilizing biodiesel derived from waste and untamed resources to establish and execute a more sustainable and ecologically conscious energy plan is praiseworthy. The adoption and integration of green energy practices could potentially yield positive environmental outcomes, thereby fostering enhanced societal and economic development for the biodiesel sector on a broader scale.
Successful Sperm Retrieval and Clinical Pregnancies Following Micro-TESE and ICSI Treatments in Patients with Nonobstructive Azoospermia Due to Various Etiologies
Authors: Liu Guangmin , Huang Zenghui , Zhu Wenbing , Zhang Huan , Fan Liqing , Huang Chuan
Published: September 2024

(1) Background: Nonobstructive azoospermia (NOA) etiologies affect the sperm retrieval rate (SRR) by microdissection testicular sperm extraction (micro-TESE) and the clinical outcomes following intracytoplasmic sperm injection (ICSI); (2) Methods: We investigated seven NOA etiologies. The SRR and clinical outcomes of 627 patients were analyzed between November 2017 and July 2022 in the Reproductive and Genetic Hospital of China International Trust and Investment Corporation-Xiangya (CITIC-Xiangya); (3) Results: The overall SRR was 39.4% (247/627). The SRR according to NOA etiologies were: Y chromosome azoospermia factor c microdeletions (26/46, 56.5%), Klinefelter syndrome (KS), 36/85, 42.4%), idiopathic (110/398, 27.6%), cryptorchidism (20/29, 69.0%), chromosome anomalies (7/13, 53.9%), orchitis (45/50, 90.0%), and cancer (3/6, 50.0%). The SRR were different for spermatogonia arrest (26/96, 27.1%), maturation arrest (76/177, 42.9%), and SCOS (30/80, 37.5%) according to histological examinations. The clinical pregnancy rate was similar among the NOA etiologies. The high-quality embryo rate differed between successful (54.7%) and unsuccessful (40.9%) pregnancies. Moreover, the successfully pregnant women (28.99 years) were younger than the unsuccessfully pregnant ones (30.92 years); (4) Conclusions: The SRR from patients with NOA was associated with the etiology and histological categories, while the clinical outcome was associated with the high-quality embryo rate and the female partner’s age.
A Flow Cytometry-Based Examination of the Mouse White Blood Cell Differential in the Context of Age and Sex
Authors: Arlt Elise , Kindermann Andrea , Fritsche Anne-Kristin , Navarrete Santos Alexander , Kielstein Heike , Bazwinsky-Wutschke Ivonne
Published: September 2024

Analysis of the white blood cell differential as part of a flow cytometry-based approach is a common routine diagnostic tool used in clinics and research. For human blood, the methodological approach, suitable markers, and gating strategies are well-established. However, there is a lack of information regarding the mouse blood count. In this article, we deliver a fast and easy protocol for reprocessing mouse blood for the purpose of flow cytometric analysis, as well as suitable markers and gating strategies. We also present two possible applications: for the analysis of the whole blood count, with blood from a cardiac puncture, and for the analysis of a certain leukocyte subset at multiple time points in the framework of a mouse experiment, using blood from the facial vein. Additionally, we provide orientation values by applying the method to 3-month-old and 24-month-old male and female C57BL/6J mice. Our analyses demonstrate differences in the leukocyte fractions depending on age and sex. We discuss the influencing factors and limitations that can affect the results and that, therefore, need to be considered when applying this method. The present study fills the gap in the knowledge related to the rare information on flow cytometric analysis of mouse blood and, thus, lays the foundation for further investigations in this area.
Isolation of Functional Human MCT Transporters in Saccharomyces cerevisiae
Authors: Hotiana Hajira Ahmed , Nordlin Karl Patric , Gotfryd Kamil , Pedersen Per Amstrup , Gourdon Pontus
Published: September 2024

Human monocarboxylate transporters (hMCTs) belong to the solute carrier 16 (SLC16) family of proteins and are responsible for the bi-directional transport of various metabolites, including monocarboxylates, hormones, and aromatic amino acids. Hence, the metabolic role of hMCTs is undisputable, as they are directly involved in providing nutrients for oxidation and gluconeogenesis as well as participate in circulation of iodothyronines. However, due to the difficulty in obtaining suitable amounts of stable hMCT samples, the structural information available for these transporters is limited, hindering the development of effective therapeutics. Here we provide a straightforward, cost-effective strategy for the overproduction of hMCTs using a whole-cell Saccharomyces cerevisiae-based system. Our results indicate that this platform is able to provide three hMCTs, i.e., hMCT1 and hMCT4 (monocarboxylate transporters), and hMCT10 (an aromatic amino acid transporter). hMCT1 and hMCT10 are recovered in the quantity and quality required for downstream structural and functional characterization. Overall, our findings demonstrate the suitability of this platform to deliver physiologically relevant membrane proteins for biophysical studies.
Effects of Continuous Rolling and Reversible Rolling on 2.4% Si Non-Oriented Silicon Steel
Authors: Shao Kaixuan , Niu Yuhao , Pei Yinghao , Qiao Jialong , Pan Hongbo , Wang Haijun
Published: September 2024

The cold-rolled non-oriented silicon steel sheets with a Si content of 2.4 wt.%, produced by continuous and reversible cold rolling, were used as the experimental material. The effects of annealing temperature on the microstructure, texture, and magnetic properties were studied by optical microscopy, an X-ray diffractometer, and a magnetic property measuring instrument. The experimental results showed that the dominant texture components at the surface of both sheets were almost the same, i.e., α and γ fibers. After annealing at 920 °C for 30 s, a complete recrystallization occurred in both sheets. When annealing below 1070 °C, the average grain sizes of continuous cold-rolled sheets were slightly higher than those of reversible cold-rolled ones. Additionally, for all specimens, the recrystallization texture components were γ fiber, as well as weak α fiber, λ fiber, and Goss texture. Additionally, the difference was the texture intensity. The iron losses of the finished products of continuous cold rolling were lower than those of the finished products of reversible cold rolling with the increase in annealing temperature, and the magnetic induction was higher than that of the finished products of reversible cold rolling.
Optimal Training Positive Sample Size Determination for Deep Learning with a Validation on CBCT Image Caries Recognition
Authors: Wang Yanlin , Li Gang , Zhang Xinyue , Wang Yue , Zhang Zhenhao , Li Jupeng , Ma Junqi , Wang Linghang
Published: September 2024

Objectives: During deep learning model training, it is essential to consider the balance among the effects of sample size, actual resources, and time constraints. Single-arm objective performance criteria (OPC) was proposed to determine the optimal positive sample size for training deep learning models in caries recognition. Methods: An expected sensitivity (PT) of 0.6 and a clinically acceptable sensitivity (P0) of 0.5 were applied to the single-arm OPC calculation formula, yielding an optimal training set comprising 263 carious teeth. U-Net, YOLOv5n, and CariesDetectNet were trained and validated using clinically self-collected cone-beam computed tomography (CBCT) images that included varying quantities of carious teeth. To assess performance, an additional dataset was utilized to evaluate the accuracy of caries detection by both the models and two dental radiologists. Results: When the number of carious teeth reached approximately 250, the models reached the optimal performance levels. U-Net demonstrated superior performance, achieving accuracy, sensitivity, specificity, F1-Score, and Dice similarity coefficients of 0.9929, 0.9307, 0.9989, 0.9590, and 0.9435, respectively. The three models exhibited greater accuracy in caries recognition compared to dental radiologists. Conclusions: This study demonstrated that the positive sample size of CBCT images containing caries was predictable and could be calculated using single-arm OPC.
An Additively Optimal Interpreter for Approximating Kolmogorov Prefix Complexity
Authors: Leyva-Acosta Zoe , Acuña Yeomans Eduardo , Hernandez-Quiroz Francisco
Published: September 2024

We study practical approximations of Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the optimality of the interpreter for this language as the reference machine for the Coding Theorem Method (CTM). This method is designed to address applications of algorithmic complexity that differ from the popular traditional lossless compression approach based on the principles of algorithmic probability. The chosen model of computation is proven to be suitable for this task, and a comparison to other models and methods is conducted. Our findings show that CTM approximations using our model do not always correlate with the results from lower-level models of computation. This suggests that some models may require a larger program space to converge to Levin’s universal distribution. Furthermore, we compare the CTM with an upper bound on Kolmogorov complexity and find a strong correlation, supporting the CTM’s validity as an approximation method with finer-grade resolution of K.
Finding Talent: An Overview of Research about Best Practices in Identification
Authors: Johnsen Susan K.
Published: September 2024

Instead of the traditional identification approaches that focus on selecting students for specific programs, talent identification models are tailored to individual student talents across a variety of domains and identify emerging talents needing to be developed. This flexibility is incorporated within The Talent Identification Cycle that includes (a) pre-identification development opportunities; (b) a variety of assessments to develop individual student profiles; (c) services that are customized to each student’s interests, strengths, and needs; (d) ongoing assessments of student performance that consider program revisions and changes in placements; (e) an overall assessment of the identification process to ensure that all students receive appropriate services. Research evidence is summarized for each component of the cycle, along with considerations and concrete examples for practitioners. The conclusion incorporates possible challenges for schools that are engaged in moving away from more traditional to more flexible identification approaches.
A Systematic Literature Review of Integrated STEM Education: Uncovering Consensus and Diversity in Principles and Characteristics
Authors: Portillo-Blanco Ane , Deprez Hanne , De Cock Mieke , Guisasola Jenaro , Zuza Kristina
Published: September 2024

Integrated STEM education is increasingly present in classrooms and in educational research, as it is proposed as a possible strategy to improve the problems of students’ lack of interest in scientific–technological disciplines. However, this increased interest in STEM education has been paralleled by a loss of cohesion in the interpretations of its theoretical basis and by an ongoing discussion on integrated STEM education’s foundations, making its understanding, translation into real projects, and evaluation difficult to undertake. Published articles defining a STEM theoretical framework have different descriptions, so the aim of this systematic literature review is to analyse these explanations and compare them with each other. Following the PRISMA 2020 guidelines, 27 articles of interest about STEM and STEAM education were obtained and analysed with a focus on the principles and characteristics described in the texts. After organising the information and analysing the similarities and differences in the principles and characteristics, we concluded that there is great consensus on the principles of “integration”, “real-world problems”, “inquiry”, “design”, and “teamwork”. Nonetheless, this review identifies areas of discussion regarding both the principles and their characteristics that invite further analysis to refine our understanding of what integrated STEM education should entail.
Dynamic Partitioning of Graphs Based on Multivariate Blood Glucose Data—A Graph Neural Network Model for Diabetes Prediction
Authors: Li Jianjun , Jiang Xiaozhe , Wang Kaiyue
Published: September 2024

Postprandial Hyperglycemia (PPHG) persistently threatens patients’ health. Therefore, accurate diabetes prediction is crucial for effective blood glucose management. Most current methods primarily focus on analyzing univariate blood glucose data using traditional neural networks, neglecting the importance of spatiotemporal modeling of multivariate data at the node and subgraph levels. This study aimed to evaluate the accuracy of using deep learning (DL) techniques to predict diabetes based on multivariable blood glucose data, aiming to improve resource allocation and decision-making in healthcare. We introduce a Nonlinear Aggregated Graph Neural Network (NLAGNN) that utilizes continuous multivariate historical blood glucose data from multiple patients to predict blood glucose levels over time, addressing the challenge of accurately extracting strong and weak correlation features. We preliminarily propose a Nonlinear Fourier Graph Neural Operator (NFGO) for nonlinear node representation, which effectively reduces meaningless noise. Additionally, a dynamic partitioning of graphs is introduced, which divides the a hypergraph into distinct subgraphs, enabling the further processing of strongly correlated features at the node and subgraph levels, ultimately obtaining the final prediction through layer aggregation. Extensive experiments on three datasets show that our proposed method achieves competitive results compared to existing advanced methods.
Flexible Integrated Scheduling Considering Periodic Maintenance
Authors: Ding Xueying , Xie Zhiqiang , Zhou Wei , Tan Zhenjiang , Sun Ming
Published: September 2024

Aiming at the problem of current flexible integrated scheduling, most of the current research shortens the total processing time of products and ignores the loss of the equipment in the processing, which affects the scheduling ability of the equipment; in this context, a flexible integrated scheduling algorithm considering periodic maintenance (FIS-PM) is proposed. The algorithm flexibly mobilizes the processing sequence of the selected processing equipment, and uniformly maintains all equipment at a certain time. First, the ISA-PM algorithm adopts the strategy combination of the layer priority, the short-time, and the equipment priority strategy to schedule the operations. Then, based on the forest firefighting model, the maintenance start point and duration of the equipment are determined by the relationship between the number of the processed operations and the number of the unprocessed operations and the loss of equipment during the maintenance. Finally, the dynamic adjustment strategy is adopted, which not only realizes the maintenance of the equipment, but also reduces the makespan of the products. The experimental results show that the proposed ISA-PM algorithm realizes the optimization effect of reducing the makespan of complex products, completing the maintenance, and improving the overall utilization rate of equipment systems.
A Deep Learning-Based Low-Overhead Beam Tracking Scheme for Reconfigurable Intelligent Surface-Aided Multiple-Input and Single-Output Systems with Estimated Channels
Authors: Guo Rongbin , Yuan Jiantao , Wang Guan , Xu Congyuan , Yin Rui
Published: September 2024

The next generation network requires not only an ultra-high data rate, global coverage, and connectivity, but also a reduction in network deployment costs and energy consumption. The emergence of reconfigurable intelligent surface (RIS) technology provides an effective way to improve efficiency and reduce cost, while the passive elements bring new challenges of channel estimation (CE) and beam tracking. For an RIS-aided multiple-input and single-output (MISO) system, in this paper, to obtain the channel state information (CSI), we propose a principle component analysis (PCA)-based staged channel estimation method. Based on the estimated channel, we propose a deep learning (DL)-based beam tracking scheme to realize low-complexity RIS reflection coefficient design, which effectively improves the signal-to-noise ratio (SNR) on the user side. The simulation results verified our proposed channel estimation scheme based on PCA, and the beam tracking scheme based on a deep neural network (DNN) for semi-active RIS-aided MISO systems can obtain approximate performances to traditional hand-crafted convex optimization-based algorithms like semi-definite relaxation (SDR) with much lower computational complexity.
Attention-Guided and Topology-Enhanced Shift Graph Convolutional Network for Skeleton-Based Action Recognition
Authors: Lu Chenghong , Chen Hongbo , Li Menglei , Jing Lei
Published: September 2024

Graph Convolutional Networks (GCNs) have emerged as a game-changer in skeleton-based action recognition. However, most previous works are resource-heavy, with large FLoating-number OPerations (FLOPs) limiting the model’s potential. A recent work involving shift operators to GCN (Shift-GCN) has successfully introduced a lightweight GCN, but there is still a performance gap compared to previous results. Inspired by Shift-GCN, we propose an innovative and novel model named attention-guided and topology-enhanced shift graph convolutional network (AT-Shift-GCN), which continues the lightweight benchmark and provides a more powerful performance. We employ a topological transfer operation to aggregate the information flow of different channels and extract spatial information. In addition, to extract temporal information across scales, we apply attention to interacting with shift convolution kernels of different lengths. Furthermore, we integrate an ultralight spatiotemporal attention module to fuse spatiotemporal details and provide robust neighborhood representation. In summary, AT-Shift-GCN is a breakthrough in skeleton-based action recognition that provides a lightweight model with enhanced performance on three datasets.
An Analysis of Research Trends for Using Artificial Intelligence in Cultural Heritage
Authors: Gîrbacia Florin
Published: September 2024

Artificial intelligence (AI) techniques have been increasingly applied in assisting various cultural heritage (CH)-related tasks. The aim of this study is to examine the research trends and current applications of AI in this vast domain. After obtaining a dataset from the Web of Science and Scopus databases, a scientometric analysis of research publications from 2019 to 2023 related to the use of AI in CH was conducted. The trending topics based on the author’s keywords were identified by using the ScientoPy v2.1.3 software. Through this approach, five main topics were identified: classification, computer vision, 3D reconstruction, recommender systems, and intangible cultural heritage. The analysis highlights the upward trend in publications in this field since 2019, indicating a growing interest in the application of AI techniques in CH. By analyzing the latest research in the field, it is observed that AI techniques are mostly applied to assist CH in the discovery, description, classification, and preservation tasks. The report gives insights into the main research areas and developing trends in the field of artificial intelligence and machine learning. The study offers important information about the key research areas and emerging trends related to using AI techniques in the CH field. This helps to recognize the potential, development, and increasing influence of these technologies within the CH domain. The findings of this study contribute to the future development of AI applications in CH, enabling professionals to use the advantages of these technologies.
Exploring and Visualizing Multilingual Cultural Heritage Data Using Multi-Layer Semantic Graphs and Transformers
Authors: Gagliardi Isabella , Artese Maria Teresa
Published: September 2024

The effectiveness of archives, particularly those related to cultural heritage, depends on their accessibility and navigability. An intuitive interface is essential for improving accessibility and inclusivity, enabling users with diverse backgrounds and expertise to interact with archival content effortlessly. This paper introduces a new method for visualizing and navigating dataset information through the creation of semantic graphs. By leveraging pre-trained large language models, this approach groups data and generates semantic graphs. The development of multi-layer maps facilitates deep exploration of datasets, and the capability to handle multilingual datasets makes it ideal for archives containing documents in various languages. These features combine to create a user-friendly tool adaptable to various contexts, offering even non-expert users a new way to interact with and navigate the data. This enhances their overall experience, promoting a greater understanding and appreciation of the content. The paper presents experiments conducted on diverse datasets across different languages and topics employing various algorithms and methods. It provides a thorough discussion of the results obtained from these experiments.
Blind Cyclostationary-Based Carrier Number and Spacing Estimation for Carrier-Aggregated Direct Sequence Spread Spectrum Cellular Signals
Authors: Görçin Ali
Published: September 2024

Automatic and blind parameter estimation based on the inherent features of wireless signals is a major research area due to the fact that these techniques lead to the simplification of receivers, especially in terms of coarse synchronization, and more importantly reduce the signaling load at the control channels. Thus, in the literature, many techniques are proposed to estimate a vast set of parameters including modulation types and orders, data and chip rates, phase and frequency offsets, and so on. In this paper, a cyclostationary feature detection (CFD) based method is proposed to estimate the carrier numbers and carrier spacing of carrier-aggregated direct sequence spread spectrum (DSSS) cellular signals blindly. The particular chip rate of the signal is also estimated through the process jointly. The proposed CFD-based method unearths the inhered and hidden second-order periodicities of carrier-aggregated DSSS signals, particularly targeting repeated pseudorandom noise sequences of users over the carriers. Throughout the paper, after the proposed method is formulated, the measurement setup that is developed to collect the data for the validation of the method is introduced. The measurement results are post-processed for performance analysis purposes. To that end, the method is investigated in terms of signal-to-noise ratio (SNR) values, different channel conditions, and measurement durations. Furthermore, the performance of the proposed method is compared with that of energy detection. The measurement results indicate superior performance of the proposed method under significant wireless channel impairments and in low-SNR regions, e.g., for 0 dB the proposed method provides more than 0.9 detection performance for the case of 0.1 false alarm rate, while the performance of ED is 0.6 under the same wireless channel impairments. The raw outputs of the method can be utilized to train a convolutional neural network to eliminate the statistical estimation process in future work.