bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual Power Transformation and Yeo–Johnson Techniques for Static and Dynamic Reliability Assessments
Authors: Liu Bao-Hua , Zhang Long-Wen , Wei Yi-Qiang , Chen Chen
Published: November 2024

This paper addresses key challenges in the static and dynamic reliability analysis of engineering structures, particularly the difficulty in accurately estimating large reliability indices and small failure probabilities. For static reliability problems, a dual power transformation is employed to transform the performance function into a form approaching a normal distribution. The high-order unscented transformation is then applied to compute the first four moments of the transformed performance function. Subsequently, the fourth-moment method is used to calculate large reliability indices, offering a novel improvement over traditional methods such as FORM and SORM. For dynamic reliability problems, the low-discrepancy sampling technique is integrated to efficiently compute structural responses under random seismic excitation, improving computational efficiency for complex dynamic systems. The Yeo–Johnson transformation is introduced to normalize the extreme values of dynamic responses, and the first four moments of the transformed extreme values are statistically evaluated. Additionally, a third-order polynomial transformation (TPT) is applied to approximate the probability density function, leading to the derivation of the probability of exceedance (POE) curve. The optimal transformation parameters for both the dual power and Yeo–Johnson transformations are determined using the Jarque–Bera (JB) test. Four numerical examples, coupled with Monte Carlo simulation, validate the proposed framework’s accuracy and efficiency, providing a robust tool for static and dynamic reliability analysis. This unified approach represents a significant advancement by integrating novel transformations and fourth-moment method, providing a powerful and efficient tool for static and dynamic reliability analysis of engineering structures.
Impact of Screening on Mortality for Patients Diagnosed with Hepatocellular Carcinoma in a Safety-Net Healthcare System: An Opportunity for Addressing Disparities
Authors: Narra Kalyani , Hull Madison , Teigen Kari J. , Reddy Vedaamrutha , Bullock Jolonda C. , Basha Riyaz , Alawi-Kakomanolis Nadia , Gerber David E. , Brown Timothy J.
Published: November 2024

Purpose: We describe the impact of screening on outcomes of patients diagnosed with hepatocellular carcinoma (HCC) in an urban safety-net healthcare system compared to a non-screened cohort diagnosed with HCC. Methods: Patients diagnosed with HCC at John Peter Smith Health Network were identified by querying the hospital tumor registry and allocated to the screened cohort if they had undergone any liver imaging within one year prior to HCC diagnosis, while the remainder were allocated to the non-screened cohort. Kaplan–Meier methods and log-rank tests were used to compare 3-year survival curves from an index date of HCC diagnosis. Cox proportional hazard models were used to calculate unadjusted and adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). The Duffy adjustment was used to address lead-time bias. Results: A total of 158 patients were included (n = 53 screened, n = 105 non-screened). The median overall survival (OS) for the screened cohort was 19.0 months (95% CI: 9.9–NA) and that for the non-screened cohort was 5.4 months (95% CI: 3.7–8.5) [HR death (non-screened vs. screened) = 2.4, 95% CI: 1.6-3.6; log rank p < 0.0001]. The benefit of screening remained after adjusting for lead-time bias (HR 2.19, 95% CI 1.4–3.3, p = 0.0002). Conclusions: In an urban safety-net population, screening for HCC was associated with improved outcomes compared to patients diagnosed with HCC outside of a screening protocol.
Etching Processing of InGaAs/InAlAs Quantum Cascade Laser
Authors: Wu Qi , Zhu Yana , Xu Dongxin , Li Zaijin , Qu Yi , Qiao Zhongliang , Liu Guojun , Zhao Zhibin , Zeng Lina , Chen Hao , Li Lin
Published: November 2024

The 3–5 μm mid-infrared band is the atmospheric window band, where there are absorption peaks of many molecules. It plays an important role in trace gas detection, directional infrared countermeasures, biomedicine, and free-space optical communications. The wet etching process of the designed InGaAs/InAlAs quantum cascade laser with superlattice structure was explored to provide a good experimental basis for the research and development of lasers. The HBr:HNO3:H2O series of etching solutions were selected for corrosion experiments, and the surface morphology was observed by scanning electron microscopy (SEM) and metallographic microscopy to obtain the corrosion rate of the etching solution. The experimental results show that the etching liquid ratio is HBr:HNO3:H2O = 1:1:10, and the etching rate is 0.6 μm/min. A quantum cascade laser that works continuously at room temperature was prepared, with an injection strip width of 7 μm, a cavity length of 4mm, and an operating temperature of 20 °C. The device works in continuous mode (CW), with a maximum continuous output power of about 186 mW, a threshold current of about 0.4 A, a threshold current density of about 1.428 kA/cm2, a device center wavelength of about 4424 nm, a side mode suppression ratio of 28 dB, and a spectrum full width at half maximum of 2 nm.
Cracking Resistance of Selected PVD Hard Coatings
Authors: Panjan Peter , Miletić Aleksandar , Drnovšek Aljaž , Terek Pal , Čekada Miha , Kovačević Lazar , Panjan Matjaž
Published: November 2024

In this study, we used the depth-sensing indentation technique to determine the cracking resistance of different PVD hard coatings deposited on tool steel substrates. By comparison, with the load–displacement curves, measured at the sites of carbide inclusion and a tempered martensite matrix in the D2 tool steel substrate surface, we observed different fracture mechanisms on TiAlN hard coating prepared by sputtering. Additional information about the deformation and fracture phenomena was obtained from the SEM images of FIB cross-sections of both types of indents. We found that the main deformation mechanism in the coating is the shear sliding along the columnar boundaries, which causes the formation of steps on the substrate surface under individual columns. Using nanoindentation test, we also analyzed the cracking resistance of a set of nl-(Cr,Al)N nanolayer coatings with different Cr/Al atomic ratios, which were sputter deposited in a single batch. From the indentation curves, we determined the loads (Fc) at which the first pop-in appears and compared them with the plasticity index H3/E2. A good correlation of both parameters was found. We also compared the indentation curves of the TiAlN coating, which were prepared by cathodic arc evaporation using 1-fold, 2-fold and 3-fold rotation of the substrates. Additionally, on the same set of samples, the fracture toughness measurements were performed by micro-cantilever deflection test. The impact of growth defects on the cracking resistance of the hard coatings was also confirmed.
Understanding the Interface Characteristics Between TiB2(0001) and L12-Al3Zr(001): A First-Principles Investigation
Authors: Pang Xingzhi , Yang Loujiang , Nong Hang , Pang Mingjun , Wang Gaobao , Li Jian , Chen Zhenchao , Zeng Wei , Xiao Zhihang , Yang Zengxiang , Tang Hongqun
Published: November 2024

This study employs first-principles calculation methods to explore the characteristics of the TiB2(0001)/L12-Al3Zr(001) interface, including the atomic structure, adhesion work, interfacial energy, and electronic structure of various interface models. Considering four different terminations and three different stacking positions, twelve potential interface models were investigated. Surface tests revealed that a stable interface could be formed when a 9-layer TiB2(0001) surface is combined with a 7-layer ZrAl-terminated and a 9-layer Al-terminated Al3Zr(001) surface. Among these interfaces, the bridge-site stacking at the T/Al termination (TAB), hollow-site stacking at the Ti/ZrAl termination (TZH), top-site stacking at the B/Al termination (BAT), and hollow-site stacking at the B/ZrAl termination (BZH) were identified as the optimal structures. Particularly, the TAB interface exhibits the strongest adhesion strength and the lowest surface energy, indicating the highest stability. A Detailed analysis of the electronic structure further reveals that most interfaces predominantly exhibit covalent bonding, with the TAB, TZH, and BZH interfaces primarily featuring covalent bonds, while the BAT interface displays a combination of ionic and covalent bonds. The study ultimately ranks the stability of the interfaces from highest to lowest as TAB, BZH, TZH, and BAT.
Population Pharmacokinetics of Tamibarotene in Pediatric and Young Adult Patients with Recurrent or Refractory Solid Tumors
Authors: Azechi Takuya , Fukaya Yutaka , Nitani Chika , Hara Junichi , Kawamoto Hiroshi , Taguchi Tomoaki , Yoshimura Kenichi , Sato Akihiro , Hattori Naoko , Ushijima Toshikazu , Kimura Toshimi
Published: November 2024

Tamibarotene is a synthetic retinoid that inhibits tumor cell proliferation and promotes differentiation. We previously reported on the safety and tolerability of tamibarotene in patients with recurrent or refractory solid tumors. Therefore, in this study, we aimed to evaluate the pharmacokinetic properties of tamibarotene and construct a precise pharmacokinetic model. We also conducted a non-compartmental analysis and population pharmacokinetic (popPK) analysis based on the results of a phase I study. Targeted pediatric and young adult patients with recurrent or refractory solid tumors were administered tamibarotene at doses of 4, 6, 8, 10, and 12 g/m2/day. Serum tamibarotene concentrations were evaluated after administration, and a popPK model was constructed for tamibarotene using Phoenix NLME. During model construction, we considered the influence of various parameters (weight, height, body surface area, and age) as covariates. Notably, 22 participants were included in this study, and 109 samples were analyzed. A two-compartment model incorporating lag time was selected as the base model. In the final model, the body surface area was included as a covariate for apparent total body clearance, the central compartment volume of distribution, and the peripheral compartment volume of distribution. Visual prediction checks and bootstrap analysis confirmed the validity and predictive accuracy of the final model as satisfactory.
Evaluating the Effect of Image Enhancement on Diagnostic Reliability in Dry Eye Disease Using a Portable Imaging Device
Authors: Mizukami Takahiro , Sato Shinri , Asai Kazuki , Inoue Takanobu , Shimizu Eisuke , Shimazaki Jun , Shimomura Yoshikazu
Published: November 2024

Background: This study aimed to evaluate the impact of image enhancement techniques on the interobserver reliability of tear break-up time (TBUT), tear meniscus height (TMH), corneal fluorescein staining (CFS) scoring, and conjunctivochalasis detection using the Smart Eye Camera (SEC), a portable device for anterior segment examination. Methods: A retrospective analysis was conducted on video recordings captured by the SEC from 46 patients with dry eye disease (DED). Separate sets of images were created for each level of enhancement: unenhanced (G0), mildly enhanced (G3), and strongly enhanced (G7). These sets were not intermixed, ensuring that each enhancement level was assessed independently. Three observers—two DED specialists and one general ophthalmologist—assessed TBUT, TMH, CFS scores, and conjunctivochalasis. Interobserver reliability was evaluated using intraclass correlation coefficients (ICCs) for each image set. Results: Interobserver reliability for CFS scores significantly improved with G3, yielding an ICC of 0.8413. In contrast, G7 improved reliability for TBUT measurements (ICC = 0.7381), but led to a notable decrease in reliability for both CFS scoring (ICC = 0.2259) and conjunctivochalasis detection (ICC = 0.0786). Furthermore, the assessment of TMH demonstrated a progressive decline in accuracy with increasing levels of image enhancement. Conclusions: Image enhancement using the SEC improved the diagnostic consistency of dry eye specialists and general ophthalmologists, especially for TBUT and CFS assessments. However, excessive enhancement may obscure key diagnostic features, indicating the need for careful optimization of image processing techniques depending on the diagnostic focus.
Deep Learning-Based Slice Thickness Reduction for Computer-Aided Detection of Lung Nodules in Thick-Slice CT
Authors: Jeong Jonghun , Park Doohyun , Kang Jung-Hyun , Kim Myungsub , Kim Hwa-Young , Choi Woosuk , Ham Soo-Youn
Published: November 2024

Background/Objectives: Computer-aided detection (CAD) systems for lung nodule detection often face challenges with 5 mm computed tomography (CT) scans, leading to missed nodules. This study assessed the efficacy of a deep learning-based slice thickness reduction technique from 5 mm to 1 mm to enhance CAD performance. Methods: In this retrospective study, 687 chest CT scans were analyzed, including 355 with nodules and 332 without nodules. CAD performance was evaluated on nodules, to which all three radiologists agreed. Results: The slice thickness reduction technique significantly improved the area under the receiver operating characteristic curve (AUC) for scan-level analysis from 0.867 to 0.902, with a p-value < 0.001, and nodule-level sensitivity from 0.826 to 0.916 at two false positives per scan. Notably, the performance showed greater improvements on smaller nodules than larger nodules. Qualitative analysis confirmed that nodules mistaken for ground glass on 5 mm scans could be correctly identified as part-solid on the refined 1 mm CT, thereby improving the diagnostic capability. Conclusions: Applying a deep learning-based slice thickness reduction technique significantly enhances CAD performance in lung nodule detection on chest CT scans, supporting the clinical adoption of refined 1 mm CT scans for more accurate diagnoses.
Cultural Education in Nature Through the Lens of Sámi Practitioners
Authors: Krempig Inger Wallem , Enoksen Elisabeth
Published: November 2024

The recent reforms in the Norwegian early childhood/primary/secondary education curriculum explicitly highlight the inclusion of Sámi perspectives across various subjects. In this context, one of several suggested educational practices is to include Sámi traditional practitioners in teaching activities. Against this backdrop, this paper explores the perspectives of five Sámi practitioners, concentrating on their experiences and pedagogical practices when engaging students of various ages and kindergarten children in Sámi culture in a nature-based setting. The study reveals the practitioners’ arguments for sharing their culture and skills through such learning activities and their suggestions for inclusion in teaching practices. The qualitative-based research methodology comprises semi-structured interviews with Sámi practitioners who are involved in different cooperative projects within our region. These different practitioners offer learners the chance to engage with Sámi nature-based traditional practices by participating in activities in close collaboration with reindeer herders, duodji (handicraft) practitioners, coastal Sámi caretakers, and similar cultural educators in an outdoor setting. This study advocates for the significance of involving Sámi traditional practitioners and Sámi practices on all educational levels and proposes that nature-based activities are of specific value in such practices.
Fault Diagnosis Method for Hydropower Station Measurement and Control System Based on ISSA-VMD and 1DCNN-BiLSTM
Authors: Wang Lin , Zhang Fangqing , Wang Jiefei , Ren Gang , Wang Dengxian , Gao Ling , Ming Xingyu
Published: November 2024

Sudden failures of measurement and control circuits in hydropower plants may lead to unplanned shutdowns of generating units. Therefore, the diagnosis of hydropower station measurement and control system poses a great challenge. Existing fault diagnosis methods suffer from long fault identification time, inaccurate positioning, and low diagnostic efficiency. In order to improve the accuracy of fault diagnosis, this paper proposes a fault diagnosis method for hydropower station measurement and control system that combines variational modal decomposition (VMD), Pearson’s correlation coefficient, a one-dimensional convolutional neural network, and a bi-directional long and short-term memory network (1DCNN-BiLSTM). Firstly, the VMD parameters are optimised by the Improved Sparrow Search Algorithm (ISSA). Secondly, signal decomposition of the original fault signals is carried out by using ISSA-VMD, and meanwhile, the optimal intrinsic modal components (IMFs) are screened out by using Pearson’s correlation coefficient, and the optimal set of components is subjected to signal reconstruction in order to obtain the new signal sequences. Then, the 1DCNN-BiLSTM-based fault diagnosis model is proposed, which achieves accurate diagnosis of the faults of hydropower station measurement and control system. Finally, experimental verification reveals that, in comparison with other methods such as 1DCNN, BiLSTM, ELM, BP neural network, SVM, and DBN, the proposed approach in this paper achieves an exceptionally high average recognition accuracy of 99.8% in both simulation and example analysis. Additionally, it demonstrates faster convergence speed, indicating not only its superior diagnostic precision but also its high application value.
Analysis of Gas-Steam CHP Plants Without and with Heat Accumulator and HTGR Reactor
Authors: Bartnik Ryszard , Hnydiuk-Stefan Anna , Buryn Zbigniew
Published: November 2024

This study analyzes the thermodynamic and economic viability of modified high-temperature gas-cooled reactor (HTGR) gas-steam combined heat and power (CHP) systems compared to conventional CHP plants. The research addresses the critical need for efficient and sustainable energy production methods. Using comprehensive thermodynamic modeling and economic analysis, the study evaluates system performance under various operating conditions. Key findings reveal that modified CHP plants with HTGR and turboexpanders (TEs) demonstrate significantly higher efficiency and lower heat generation costs compared to conventional gas turbine (GT) CHP plants, despite higher initial capital investments. The modified systems achieve electricity generation efficiencies up to 48%, surpassing traditional nuclear power plants. The absence of CO2 emissions and lower fuel costs in HTGR systems contribute to their economic advantage. This research provides novel insights into the potential of HTGR technology in CHP applications, offering a promising solution for future energy systems. The study’s originality lies in its comprehensive comparison of conventional and modified CHP systems, considering both thermodynamic and economic aspects, which has not been extensively explored in existing literature.
Chlorophyll Content Estimation of Ginkgo Seedlings Based on Deep Learning and Hyperspectral Imagery
Authors: Yue Zilong , Zhang Qilin , Zhu Xingzhou , Zhou Kai
Published: November 2024

Accurate estimation of chlorophyll content is essential for understanding the growth status and optimizing the cultivation practices of Ginkgo, a dominant multi-functional tree species in China. Traditional methods based on chemical analysis for determining chlorophyll content are labor-intensive and time-consuming, making them unsuitable for large-scale dynamic monitoring and high-throughput phenotyping. To accurately quantify chlorophyll content in Ginkgo seedlings under different nitrogen levels, this study employed a hyperspectral imaging camera to capture canopy hyperspectral images of seedlings throughout their annual growth periods. Reflectance derived from pure leaf pixels of Ginkgo seedlings was extracted to construct a set of spectral parameters, including original reflectance, logarithmic reflectance, and first derivative reflectance, along with spectral index combinations. A one-dimensional convolutional neural network (1D-CNN) model was then developed to estimate chlorophyll content, and its performance was compared with four common machine learning methods, including Gaussian Process Regression (GPR), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest (RF). The results demonstrated that the 1D-CNN model outperformed others with the first derivative spectra, achieving higher CV-R2 and lower RMSE values (CV-R2 = 0.80, RMSE = 3.4). Furthermore, incorporating spectral index combinations enhanced the model’s performance, with the 1D-CNN model achieving the best performance (CV-R2 = 0.82, RMSE = 3.3). These findings highlight the potential of the 1D-CNN model in strengthening the chlorophyll estimations, providing strong technical support for the precise cultivation and the fertilization management of Ginkgo seedlings.
Towards a Decentralized Collaborative Framework for Scalable Edge AI
Authors: Abdelmoniem  Ahmed M. , Jaber  Mona , Anwar  Ali , Zhang  Yuchao , Gao  Mingliang
Published: November 2024

Nowadays, Edge Intelligence has seen unprecedented growth in most of our daily life applications. Traditionally, most applications required significant efforts into data collection for data-driven analytics, raising privacy concerns. The proliferation of specialized hardware on sensors, wearable, mobile, and IoT devices has led to the growth of Edge Intelligence, which has become an integral part of the development cycle of most modern applications. However, scalability issues hinder their wide-scale adoption. We aim to focus on these challenges and propose a scalable decentralized edge intelligence framework. Therefore, we analyze and empirically evaluate the challenges of existing methods, and design an architecture that overcomes these challenges. The proposed approach is client-driven and model-centric, allowing models to be shared between entities in a scalable fashion. We conduct experiments over various benchmarks to show that the proposed approach presents an efficient alternative to the existing baseline method, and it can be a viable solution to scale edge intelligence.
SBNNR: Small-Size Bat-Optimized KNN Regression
Authors: Seyghaly Rasool , Garcia Jordi , Masip-Bruin Xavi , Kuljanin Jovana
Published: November 2024

Small datasets are frequent in some scientific fields. Such datasets are usually created due to the difficulty or cost of producing laboratory and experimental data. On the other hand, researchers are interested in using machine learning methods to analyze this scale of data. For this reason, in some cases, low-performance, overfitting models are developed for small-scale data. As a result, it appears necessary to develop methods for dealing with this type of data. In this research, we provide a new and innovative framework for regression problems with a small sample size. The base of our proposed method is the K-nearest neighbors (KNN) algorithm. For feature selection, instance selection, and hyperparameter tuning, we use the bat optimization algorithm (BA). Generative Adversarial Networks (GANs) are employed to generate synthetic data, effectively addressing the challenges associated with data sparsity. Concurrently, Deep Neural Networks (DNNs), as a deep learning approach, are utilized for feature extraction from both synthetic and real datasets. This hybrid framework integrates KNN, DNN, and GAN as foundational components and is optimized in multiple aspects (features, instances, and hyperparameters) using BA. The outcomes exhibit an enhancement of up to 5% in the coefficient of determination (R2 score) using the proposed method compared to the standard KNN method optimized through grid search.
Characteristics and Yield of Modern Approaches for the Diagnosis of Genetic Causes of Kidney Stone Disease
Authors: Spasiano Andrea , Treccani Mirko , De Tomi Elisa , Malerba Giovanni , Gambaro Giovanni , Ferraro Pietro
Published: November 2024

Background: Kidney stone disease (KSD) is characterized by an increasing prevalence worldwide, representing an important clinical issue and a financial burden for healthcare systems. A KSD-causing monogenic variant is traditionally expected in up to 30% of children and 1–5% of adults forming stones, confirmed by a strong connection between a positive family history and KSD. The insufficient use of genetic testing in these patients is associated with a lack of perceived benefit and a scarce awareness of inherited kidney diseases. Genetic testing has important practical implications, such as the possibility of earlier diagnoses, familial counseling, and tailored therapy, based on the evaluation of fine-mapped pathogenic variants. Our aim is to analyze the current evidence on genetic testing in KSD patients to whom genetic tests were applied without strict a priori selection criteria, to provide an overview of its diagnostic yield and factors potentially affecting it (such as the age of KSD onset, a familial history of KSD, consanguinity, and extrarenal features). Methods: A literature review was performed, selecting original articles published in the last 10 years concerning genetic investigations in patients affected by nephrolithiasis or nephrocalcinosis. Available data were subsequently extracted and analyzed. Results: In total, 13 studies on 1675 patients (77% pediatric populations) were included; 333 patients were determined to be affected by a monogenic disorder, with an overall yield of about 20%. The likelihood of a positive genetic finding was much higher in pediatric (26%) than adult populations (8%). Cystinuria was the most common diagnosis in both populations. After the removal of conditions that could be identified with a stone composition analysis or urinary chemistry investigation, the diagnostic yield dropped to 19% among pediatric patients and below 5% for adults. Conclusions: Genetic testing should be considered in KSD pediatric patients and in selected subgroups of adults with suggestive features when a diagnosis is not established after stone examination and blood as well as urine metabolic profiling.
Retinal Patterns and the Role of Autofluorescence in Choroideremia
Authors: Poli Federica E. , MacLaren Robert E. , Cehajic-Kapetanovic Jasmina
Published: November 2024

Background: Choroideremia is a monogenic inherited retinal dystrophy that manifests in males with night blindness, progressive loss of peripheral vision, and ultimately profound sight loss, commonly by middle age. It is caused by genetic defects of the CHM gene, which result in a deficiency in Rab-escort protein-1, a key element for intracellular trafficking of vesicles, including those carrying melanin. As choroideremia primarily affects the retinal pigment epithelium, fundus autofluorescence, which focuses on the fluorescent properties of pigments within the retina, is an established imaging modality used for the assessment and monitoring of affected patients. Methods and Results: In this manuscript, we demonstrate the use of both short-wavelength blue and near-infrared autofluorescence and how these imaging modalities reveal distinct disease patterns in choroideremia. In addition, we show how these structural measurements relate to retinal functional measures, namely microperimetry, and discuss the potential role of these retinal imaging modalities in clinical practice and research studies. Moreover, we discuss the mechanisms underlying retinal autofluorescence patterns by imaging with a particular focus on melanin pigment. Conclusions: This could be of particular significance given the current progress in therapeutic options, including gene replacement therapy.
The Evolution of Complex Multicellularity in Land Plants
Authors: Madhani Hossein , Nejad Kourki Arsham
Published: November 2024

The evolution of complex multicellularity in land plants represents a pivotal event in the history of life on Earth, characterized by significant increases in biological complexity. This transition, classified as a Major Evolutionary Transition (MET), is best understood through the framework of Evolutionary Transitions in Individuality (ETIs), which focuses on formerly independent entities forming higher-level units that lose their reproductive autonomy. While much of the ETI literature has concentrated on the early stages of multicellularity, such as the formation and maintenance stages, this paper seeks to address the less explored transformation stage. To do so, we apply an approach that we call Transitions in Structural Complexity (TSCs), which focuses on the emergence of new units of organization via the three key evolutionary processes of modularization, subfunctionalization, and integration to the evolution of land plants. To lay the groundwork, we first explore the relationships between sex, individuality, and units of selection to highlight a sexual life cycle-based perspective on ETIs by examining the early stages of the transition to multicellularity (formation) in the sexual life cycle of the unicellular common ancestor of land plants, emphasizing the differences between the transition to multicellularity in eumetazoans and land plants. We then directly apply the TSC approach in this group, identifying key evolutionary events such as the distinct evolutionary innovations like shoot, root, vascular systems, and specialized reproductive structures, arguing that bringing these under the broader rubric of TSCs affords a degree of explanatory unification. By examining these evolutionary processes, this paper provides a new perspective on the evolution of multicellularity in land plants, highlighting both parallels and distinctions with the animal kingdom.
Use of Mobile Phones and Radiofrequency-Emitting Devices in the COSMOS-France Cohort
Authors: Deltour Isabelle , Guida Florence , Ribet Céline , Zins Marie , Goldberg Marcel , Schüz Joachim
Published: November 2024

COSMOS-France is the French part of the COSMOS project, an international prospective cohort study that investigates whether the use of mobile phones and other wireless technologies is associated with health effects and symptoms (cancers, cardiovascular diseases, neurologic pathologies, tinnitus, headaches, or sleep and mood disturbances). Here, we provide the first descriptive results of COSMOS-France, a cohort nested in the general population-based cohort of adults named Constances. Methods: A total of 39,284 Constances volunteers were invited to participate in the COSMOS-France study during the pilot (2017) and main recruitment phase (2019). Participants were asked to complete detailed questionnaires on their mobile phone use, health conditions, and personal characteristics. We examined the association between mobile phone use, including usage for calls and Voice over Internet Protocol (VoIP), cordless phone use, and Wi-Fi usage with age, sex, education, smoking status, body mass index (BMI), and handedness. Results: The participation rate was 48.4%, resulting in 18,502 questionnaires in the analyzed dataset. Mobile phone use was reported by 96.1% (N = 17,782). Users reported typically calling 5–29 min per week (37.1%, N = 6600), making one to four calls per day (52.9%, N = 9408), using one phone (83.9%, N = 14,921) and not sharing it (80.4% N = 14,295), mostly using the phone on the side of the head of their dominant hand (59.1%, N = 10,300), not using loudspeakers or hands-free kits, and not using VoIP (84.9% N = 15,088). Individuals’ age and sex modified this picture, sometimes markedly. Education and smoking status were associated with ever use and call duration, but neither BMI nor handedness was. Cordless phone use was reported by 66.0% of the population, and Wi-Fi use was reported by 88.4%. Conclusion: In this cross-sectional presentation of contemporary mobile phone usage in France, age and sex were important determinants of use patterns.
Relationship Between the Occurrence of Depression and DROSHA (rs6877842, rs10719) and XPO5 (rs11077) Single-Nucleotide Polymorphisms in the Polish Population: A Case–Control Study
Authors: Kowalczyk Mateusz , Kowalczyk Edward , Talarowska Monika , Majsterek Ireneusz , Skrzypek Maciej , Popławski Tomasz , Sienkiewicz Monika , Wiktorowska-Owczarek Anna , Sokołowska Paulina , Jóźwiak-Bębenista Marta
Published: November 2024

Although the epidemiology and symptoms of major depressive disorder (MDD) have been well-documented, the etiology and pathophysiology of the disease have not yet been fully explained. Depression arises from intricate interplay among social, psychological, and biological factors. Recently, there has been growing focus on the involvement of miRNAs in depression, with suggestions that abnormal miRNA processing locally at the synapse contributes to MDD. Changes in miRNAs may result from altered expression and/or function of the miRNA biogenesis machinery at the synapse. The aim of our research was to assess the relationship between the occurrence of depression and single-nucleotide polymorphisms (SNP) in the following genes in the Polish population: DROSHA (rs6877842; rs10719) and XPO5 (rs11077). This study involved 200 individuals, including 100 with depressive disorders in the study group (SG) and 100 healthy people without MDD in the control group (CG). All participants were unrelated native Caucasian Poles from central Poland. Blood samples were collected to evaluate the single-nucleotide polymorphism of the genes. Findings indicated that within our patient cohort, the risk of depression is increased by polymorphic variants of the rs10719/DROSHA and rs11077/XPO5 genes and lowered by rs6877842/DROSHA. Our study sheds light on the understanding of the genetic basis of depression, which can be used in the rapid diagnosis of this disease.
C60 Fullerene Reduces the Development of Post-Traumatic Dysfunction in Rat Soleus Muscle
Authors: Prylutskyy Yuriy , Nozdrenko Dmytro , Motuziuk Olexandr , Prylutska Svitlana , Bogutska Kateryna , Abramchuk Olga , Morenko Alevtyna , Franskevych Daria , Scharff Peter , Ritter Uwe
Published: November 2024

Traumatic skeletal muscle injury is a complex pathology caused by high-energy trauma to muscle tissue. Previously, a positive effect was established when C60 fullerene was administered against the background of muscle ischemia, mechanical muscle injury, and other muscle dysfunctions, which probably protected the muscle tissue from damage caused by oxidative stress. Using tensiometry and biochemical analysis, the biomechanical parameters of skeletal muscle contraction and biochemical indices of the blood of rats 15 days after traumatic injury of the soleus muscle caused by myocyte destruction by compression were studied. The intraperitoneal administration of C60 fullerene aqueous solution (C60FAS) in a daily dose of 1 mg/kg improved its contractile function by 28–40 ± 2% and the values of the investigated biochemical indices of the animals’ blood by 15–34 ± 2% relative to the trauma group. The obtained results indicate the potential ability of C60 fullerenes, as powerful antioxidants, to reduce the development of post-traumatic dysfunction of the soleus muscle.
Dual Photonics Probing of Nano- to Submicron-Scale Structural Alterations in Human Brain Tissues/Cells and Chromatin/DNA with the Progression of Alzheimer’s Disease
Authors: Alharthi Fatemah , Apachigawo Ishmael , Solanki Dhruvil , Khan Sazzad , Singh Himanshi , Khan Mohammad Moshahid , Pradhan Prabhakar
Published: November 2024

Understanding alterations in structural disorders in tissue/cells/building blocks, such as DNA/chromatin in the human brain, at the nano to submicron level provides us with efficient biomarkers for Alzheimer’s detection. Here, we report a dual photonics technique to detect nano- to submicron-scale alterations in brain tissues/cells and DNA/chromatin due to the early to late progression of Alzheimer’s disease in humans. Using a recently developed mesoscopic light transport technique, fine-focused nano-sensitive partial wave spectroscopy (PWS), we measure the degree of structural disorder in tissues. Furthermore, the chemical-specific inverse participation ratio technique (IPR) was used to measure the DNA/chromatin structural alterations. The results of the PWS and IPR experiments showed a significant increase in the degree of structural disorder at the nano to submicron scale at different stages of AD relative to their controls for both the tissue/cell and DNA cellular levels. The increase in the structural disorder in cells/tissues and DNA/chromatin in the nuclei can be attributed to higher mass density fluctuations in the tissue and DNA/chromatin damage in the nuclei caused by the rearrangements of macromolecules due to the deposition of the amyloid beta protein and damage in DNA/chromatin with the progress of AD.
Acute and Chronic Resistance Training, Acute Endurance Exercise, nor Physiologically Plausible Lactate In Vitro Affect Skeletal Muscle Lactylation
Authors: Mattingly Madison L. , Anglin Derick A. , Ruple Bradley A. , Scarpelli Maira C. , Bergamasco Joao G. , Godwin Joshua S. , Mobley Christopher B. , Frugé Andrew D. , Libardi Cleiton A. , Roberts Michael D.
Published: November 2024

We examined changes in skeletal muscle protein lactylation and acetylation in response to acute resistance exercise, chronic resistance training (RT), and a single endurance cycling bout. Additionally, we performed in vitro experiments to determine if different sodium lactate treatments affect myotube protein lactylation and acetylation. The acute and chronic RT study (12 college-aged participants) consisted of 10 weeks of unilateral leg extensor RT with vastus lateralis (VL) biopsies taken at baseline, 24 h following the first RT bout, and the morning of the last day of the RT bout. For the acute cycling study (9 college-aged participants), VL biopsies were obtained before, 2 h after, and 8 h after 60 min of cycling. For in vitro experiments, C2C12 myotubes were treated with varying levels of sodium lactate, including LOW (1 mM for 24 h), HIGH (10 mM for 24 h), and PULSE (10 mM for 30 min followed by 1 mM for 23.5-h). Neither acute nor chronic RT significantly affected nuclear or cytoplasmic protein lactylation. However, cytoplasmic protein acetylation was significantly reduced following one RT bout (−15%, p = 0.002) and chronic RT (−16%, p = 0.006). Cycling did not acutely alter post-exercise global protein lactylation or acetylation patterns. Lastly, varying 24 h lactate treatments did not alter nuclear or cytoplasmic protein lactylation or acetylation, cytoplasmic protein synthesis levels, or myotube diameters. These findings continue to support the idea that exercise induces more dynamic changes in skeletal muscle protein acetylation, but not lactylation. However, further human research with more sampling timepoints and a lactylomics approach are needed to determine if, at all, different exercise modalities affect skeletal muscle protein lactylation.
Mechanisms Behind the Impact of PIWI Proteins on Cancer Cells: Literature Review
Authors: Limanówka Piotr , Ochman Błażej , Świętochowska Elżbieta
Published: November 2024

The P-Element-induced wimpy testis (PIWI) group of proteins plays a key role in RNA interference, particularly in the regulation of small non-coding RNAs. However, in recent years, PIWIs have gained attention in several diseases, mainly cancer. Therefore, the aim of this review was to evaluate current knowledge about the impact of PIWI proteins on cancer cells. PIWIs alter a number of pathways within cells, resulting in significant changes in cell behavior. Basic processes of cancer cells have been shown to be altered by either overexpression or inhibition of PIWIs. Regulation of apoptosis, metastasis, invasion, or proliferation of cancerous cells by these proteins proves their involvement in the progression of the malignancy. It has been revealed that PIWIs are also connected with cancer stem cells (CSCs), which proves their ability to become a therapeutic target. However, research on this topic is still fairly limited, and with significant differences between cancer types, it is necessary to refrain from making any decisive conclusions.
Integrated Transcriptome Profiling and Pan-Cancer Analyses Reveal Oncogenic Networks and Tumor-Immune Modulatory Roles for FABP7 in Brain Cancers
Authors: Lee Yool , Flores Carlos C. , Lefton Micah , Bhoumik Sukanya , Owada Yuji , Gerstner Jason R.
Published: November 2024

Fatty acid binding protein 7 (FABP7) is a multifunctional chaperone involved in lipid metabolism and signaling. It is primarily expressed in astrocytes and neural stem cells (NSCs), as well as their derived malignant glioma cells within the central nervous system. Despite growing evidence for FABP7’s tumor-intrinsic onco-metabolic functions, its mechanistic role in regulating the brain tumor immune microenvironment (TIME) and its impact on prognosis at the molecular level remain incompletely understood. Utilizing combined transcriptome profiling and pan-cancer analysis approaches, we report that FABP7 mediates the expression of multiple onco-immune drivers, collectively impacting tumor immunity and clinical outcomes across brain cancer subtypes. An analysis of a single-cell expression atlas revealed that FABP7 is predominantly expressed in the glial lineage and malignant cell populations in gliomas, with nuclear localization in their parental NSCs. Pathway and gene enrichment analysis of RNA sequencing data from wild-type (WT) and Fabp7-knockout (KO) mouse brains, alongside control (CTL) and FABP7-overexpressing (FABP7 OV) human astrocytes, revealed a more pronounced effect of FABP7 levels on multiple cancer-associated pathways. Notably, genes linked to brain cancer progression and tumor immunity (ENO1, MUC1, COL5A1, and IL11) were significantly downregulated (>2-fold) in KO brain tissue but were upregulated in FABP7 OV astrocytes. Furthermore, an analysis of data from The Cancer Genome Atlas (TCGA) showed robust correlations between the expression of these factors, as well as FABP7, and established glioma oncogenes (EGFR, BRAF, NF1, PDGFRA, IDH1), with stronger associations seen in low-grade glioma (LGG) than in glioblastoma (GBM). TIME profiling also revealed that the expression of FABP7 and the genes that it modulates was significantly associated with prognosis and survival, particularly in LGG patients, by influencing the infiltration of immunosuppressive cell populations within tumors. Overall, our findings suggest that FABP7 acts as an intracellular regulator of pro-tumor immunomodulatory genes, exerting a synergistic effect on the TIME and clinical outcomes in brain cancer subtypes.
Improving Interpretation Consistency of Serum Capillary Electrophoresis by Development of Quantitative Graphic Indexes
Authors: Yu Jia-Ruei , Wu Yu-Tan , Sung Yi-Juan , Chiueh Tzong-Shi , Yu Wei-Hsuan , Hwang Feng-Nan , Wu Zong-Qi , Anwar Zayd , Lin Wan-Ying , Wang Hsin-Yao
Published: November 2024

Capillary zone electrophoresis–immunosubtraction (CZE-IS) is an essential laboratory test in diagnosing plasma cell neoplasms. However, the current interpretation of the test results is subjective. To evaluate CZE-IS in a more precise manner, this study proposed five key indexes, namely sharpness index, light chain index, immunoglobulin G index, immunoglobulin A index, and immunoglobulin M index. The reference intervals of these indexes were established using CZE-IS curve data from a clinical laboratory of a referral medical center. A total of 1000 cases with normal electrophoretic patterns were sampled for reference intervals establishment, and an additional 20 cases were included for validation. The following reference intervals in the γ zone were established: 1-6 (sharpness index), 1.06-2.71 (light chain index), 37-454 (immunoglobulin G index), (−9)-41 (immunoglobulin A index), and (−16)-46 (immunoglobulin M index). For the β2 zone, the reference intervals were 3-17 (sharpness index), 0.44-1.90 (light chain index), (−7)-61 (immunoglobulin G index), 2-117 (immunoglobulin A index), and (−12)-35 (immunoglobulin M index). The diagnostic performance of reference intervals of the proposed indexes in validation ranged from 95% to 100%. CZE-IS indexes provide the objective quantification of key characteristics of CZE-IS curves and improve the precision of CZE-IS interpretation.
Assessing the Prognostic Value of Cytoplasmic and Stromal Caveolin-1 in Early Triple-Negative Breast Cancer Undergoing Neoadjuvant Chemotherapy
Authors: Teruel Iris , Castellà Eva , Recalde Sabela , Viñas Gemma , Petit Anna , Trigueros Macedonia , Martínez-Balibrea Eva , Felip Eudald , Bergamino Milana , Bernat-Peguera Adrià , Cirauqui Beatriz , Quiroga Vanesa , Ferrando-Díez Angelica , Pous Anna , López Assumpció , Boronat Laia , Soler Gemma , Recuero Jordi , Romeo Margarita , Guillén Pau , Mesía Ricard , Ballana Ester , Martínez-Cardús Anna , Margelí Mireia
Published: November 2024

Triple-negative breast cancer (TNBC) is a highly aggressive subtype with limited therapeutic options, leading to higher relapse rates and mortality. Identifying prognostic biomarkers like caveolin-1 (CAV1) is crucial for personalized treatment. CAV1 influences tumor progression and chemotherapy response, particularly through its interaction with the tumor microenvironment (TME) and cancer metabolism. Understanding the prognostic value of CAV1 in different cellular compartments is essential for its clinical application in TNBC. In the methods section CAV1 gene expression in TNBC was evaluated using in silico analysis, followed by the immunohistochemical staining of tumor cytoplasm (cCAV1) and stromal cells (sCAV1) in 58 early-stage TNBC patients. Statistical analyses were performed to correlate CAV1 expression with clinicopathological features and survival. In the results section, in silico analysis revealed higher CAV1 expression in TNBC, correlating with shorter overall survival. In the patient samples, cCAV1 was observed in 10.3% of cases, and was associated with larger tumors, higher grades, and poorer prognoses. sCAV1 was detected in 42% of cases, associated with less proliferative and less aggressive tumors, but did not significantly impact prognoses. In conclusion, cCAV1 expression is a significant prognostic marker in early-stage TNBC, highlighting the importance of assessing CAV1 in different cellular compartments. Further research is needed to explore the mechanisms and clinical implications of cCAV1.
Functional Divergence of the Closely Related Genes PhARF5 and PhARF19a in Petunia hybrida Flower Formation and Hormone Signaling
Authors: Ding Yiqing , Miao Yunfeng , Huang Lingxuan , Zhu Huijun , Li Wenle , Zou Wei , Yu Shumin , Dong Bin , Zhong Shiwei
Published: November 2024

The ARF gene family plays a vital role in regulating multiple aspects of plant growth and development. However, detailed research on the role of the ARF family in regulating flower development in petunia and other plants remains limited. This study investigates the distinct roles of PhARF5 and PhARF19a in Petunia hybrida flower development. Phylogenetic analysis identified 29 PhARFs, which were grouped into four clades. VIGS-mediated silencing of PhARF5 and PhARF19a led to notable phenotypic changes, highlighting their non-redundant functions. PhARF5 silencing resulted in reduced petal number and limb abnormalities, while PhARF19a silencing disrupted corolla tube formation and orientation. Both genes showed high expression in the roots, leaves, and corollas, with nuclear localization. The transcriptomic analysis revealed significant overlaps in DEGs between PhARF5 and PhARF19a silencing, indicating shared pathways in hormone metabolism, signal transduction, and stress responses. Phytohormone analysis confirmed their broad impact on phytohormone biosynthesis, suggesting involvement in complex feedback mechanisms. Silencing PhARF5 and PhARF19a led to differential transcription of numerous genes related to hormone signaling pathways beyond auxin signaling, indicating their direct or indirect crosstalk with other phytohormones. However, significant differences in the regulation of these signaling pathways were observed between PhARF5 and PhARF19a. These findings reveal the roles of ARF genes in regulating petunia flower development, as well as the phylogenetic distribution of the PhARFs involved in this process. This study provides a valuable reference for molecular breeding aimed at improving floral traits in the petunia genus and related species.