bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Motor Symptoms in Parkinson’s Disease Through Wearable Sensors: A Systematic Review of Digital Biomarkers
Authors: Polvorinos-Fernández Carlos , Sigcha Luis , Borzì Luigi , Olmo Gabriella , Asensio César , López Juan Manuel , de Arcas Guillermo , Pavón Ignacio
Published: November 2024

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, entailing several motor-related symptoms that contribute to a reduced quality of life in affected subjects. Recent advances in wearable technologies and computing resources have shown great potential for the assessment of PD-related symptoms. However, the potential applications (e.g., early diagnosis, prognosis and monitoring) and key features of digital biomarkers for motor symptoms of PD (DB-MS-PD) have not been comprehensively studied. This study aims to provide a state-of-the-art review of current digital biomarker definitions for PD, focusing on the use of wearable devices. This review systematically examines research articles from 2012 to 2024, focusing on key features and recent technologies in PD research. A total of 22 studies were included and thoroughly analyzed. Results indicate that DB-MS-PD can accurately distinguish patients with PD (PwPD) from healthy controls (HC), assess disease severity or treatment response, and detect motor symptoms. Large sample sizes, proper validation, non-invasive devices, and ecological monitoring make DB-MS-PD promising for improving PD management. Challenges include sample and method heterogeneity and lack of public datasets. Future studies can leverage evidence of the current literature to provide more effective and ready-to-use digital tools for monitoring PD.
A Scene–Object–Economy Framework for Identifying and Validating Urban–Rural Fringe Using Multisource Geospatial Big Data
Authors: Yin Ganmin , Feng Ying , Jiang Yanxiao , Bao Yi
Published: November 2024

Rapid urbanization has led to the emergence of urban–rural fringes, complex transitional zones that challenge traditional urban–rural dichotomies. While these areas play a crucial role in urban development, their precise identification remains a significant challenge. Existing methods often rely on single-dimensional metrics or administrative boundaries, failing to capture the multi-faceted nature of these zones. This study introduces a novel “Scene–Object–Economy” (SOE) framework to address these limitations and enhance the precision of urban–rural fringe identification. Our approach integrates multisource geospatial big data, including remote sensing imagery, nightlight data, buildings, and Points of Interest (POI), leveraging machine learning techniques. The SOE framework constructs feature from three dimensions: scene (image features), object (buildings), and economy (POIs). This multidimensional methodology allows for a more comprehensive and nuanced mapping of urban–rural fringes, overcoming the constraints of traditional methods. The study demonstrates the effectiveness of the SOE framework in accurately delineating urban–rural fringes through multidimensional validation. Our results reveal distinct spatial patterns and characteristics of these transitional zones, providing valuable insights for urban planners and policymakers. Furthermore, the integration of dynamic population data as a separate layer of analysis offers a unique perspective on population distribution patterns within the identified fringes. This research contributes to the field by offering a more robust and objective approach to urban–rural fringe identification, laying the groundwork for improved urban management and sustainable development strategies. The SOE framework presents a promising tool for future studies in urban spatial analysis and planning.
Exploring the Psychological Mechanism of How the Multidimensional Service Quality of Fitness Centers Affects Consumer Satisfaction and Loyalty Depending on the Level of Exercise Involvement
Authors: Kim Manmin , Kim Daehwan
Published: November 2024

This study aimed to examine the influence of core services and the physical servicescape and social servicescape on consumer satisfaction and loyalty via perceived price fairness, flow experience, and rapport in fitness centers. Additionally, the present study explored how exercise involvement moderates the relationship between perceived price fairness, flow experience, rapport, and consumer satisfaction. For these purposes, targeting adults using fitness centers in South Korea, a total of 763 participants were sampled based on a cross-sectional design and used for data analyses involving confirmatory factor analysis for measurement validation and latent moderated structural equation modeling for hypothesis testing. The results showed that the core services, physical servicescape, and social servicescape enhance perceived price fairness, flow experiences, and rapport between staff and consumers, respectively. The study findings also indicated that exercise involvement significantly moderates the effect of price fairness and flow experience on satisfaction but not rapport. These insights offer practical and theoretical implications for fitness center management, emphasizing the importance of tailored service strategies in retaining loyal customers.
Effect of Green Value Cocreation on Consumer Behavior: A Professional Baseball Franchise’s “Sustainable Party” Event
Authors: Chen Chen-Yueh , Lin Yi-Hsiu , Shih Ming-Ti , Yeh Tzu-Yun
Published: November 2024

This study examined whether participation in green activities affects the green purchase intention, team identification, and subjective well-being of sports fans through green value cocreation. In addition, this study explored the mediating role of team identification and the moderating role of subjective well-being in green value cocreation. Composite reliability and confirmatory factor analyses were conducted to evaluate the validity and reliability of the research instruments, and structural equation modeling was used to test the study hypotheses. The results indicated that green value cocreation significantly predicted green purchase intention, team identification, and subjective well-being. Team identification partially mediated the relationship between green value cocreation and green purchase intention. However, subjective well-being did not moderate the effect of green value cocreation on green purchase intention. This study investigated how green value cocreation enhances fan participation in environmental actions and translates into green purchase intention. The findings provide insights into the emotional connection between fans and teams and the effect of this connection on green value cocreation and green purchase intention. This study addresses a research gap regarding the role of green value cocreation in professional sports and provides practical insights for businesses, teams, and society to promote environmentally conscious consumption and behavior.
The Mediating Role of Teacher Efficacy Between Academic Self-Concept and Teacher Identity Among Pre-Service Physical Education Teachers: Is There a Gender Difference?
Authors: Rubio-Valdivia José María , Granero-Gallegos Antonio , Carrasco-Poyatos María , López-García Ginés David
Published: November 2024

The aim of this study was to analyse the differentiated role played by academic self-concept on teacher identity, taking into account the mediating role of teacher efficacy and the gender of the pre-service physical-education teachers. In this cross-sectional study, 478 master’s degree students in Secondary Education Teacher Training participated (Mean = 27.09; SD = 6.32; 54.8% male, 44.8% female, 0.4% other). The following scales were used: academic self-concept, teaching identity, and teacher self-efficacy. After finding significant differences in academic effort, a structural equation analysis (SEM) with the multigroup option was conducted to answer the research objective. The results revealed that the women had significantly higher mean academic effort values than the men. In addition, the SEM, which showed excellent fit indices, revealed that, for the men, teacher efficacy acted as a mediating variable between academic confidence and teacher identity. In contrast, for the women, teacher efficacy acted as a mediator between academic effort and teacher identity. However, academic effort also acted as a direct predictor of teacher identity in male pre-service teachers. As a main conclusion, it can be said that the findings highlight the importance of academic self-concept in undertaking the master’s degree by increasing teacher identity through the teaching efficacy of pre-service teacher educators.
Multi-Omic Characterization of Single Cells and Cell-Free Components Detected in the Cerebrospinal Fluid of Patients with Leptomeningeal Disease
Authors: Shishido Stephanie N. , Marvit Amelia , Pham Doanna , Luo Theresa , Xu Liya , Mason Jeremy , Priceman Saul J. , Portnow Jana , Kuhn Peter
Published: November 2024

Background/Objectives: Up to 30% of patients with breast cancers will develop brain or leptomeningeal metastases, and this risk is especially high with HER2-positive cancers. For patients with central nervous system metastases, cerebrospinal fluid (CSF) liquid biopsies are a promising opportunity to monitor disease, inform treatment, and predict prognosis. This pilot study investigated CSF liquid biopsy analytes from three patients diagnosed with central nervous system metastases based on imaging but not confirmed via clinical cytology. Methods: The detection of cellular analytes with the non-enrichment high-definition single-cell assay (HDSCA3.0) workflow was compared between the CSF and matched peripheral blood (PB) samples. Results: Circulating tumor cells (CTCs) were detected in the CSF but not the PB and were subsequently molecularly characterized using single-cell genomics and targeted multiplexed proteomics to reveal a clonal population of phenotypically heterogeneous cells. There was a lack of concordance in the copy number alteration profiles between CTCs and cell-free DNA (cfDNA) in the CSF. Extracellular vesicle surface marker analysis in CSF revealed a prominent signal among tetraspanins (CD9/CD63/CD81), with CD81 exhibiting the highest signal across all patients. Conclusions: The data presented suggest that CSF could be a useful tool for diagnosing and assessing disease severity.
Exploring Extracellular Vesicle Surface Protein Markers Produced by Glioblastoma Tumors: A Characterization Study Using In Vitro 3D Patient-Derived Cultures
Authors: Franceschi Sara , Lessi Francesca , Morelli Mariangela , Menicagli Michele , Aretini Paolo , Gambacciani Carlo , Pieri Francesco , Grimod Gianluca , Trapanese Maria Grazia , Valenti Silvia , Paiar Fabiola , Di Stefano Anna Luisa , Santonocito Orazio Santo , Pasqualetti Francesco , Mazzanti Chiara Maria
Published: November 2024

Background/Objectives: Glioblastoma (GBM) is an aggressive brain cancer with limited treatment options. Extracellular vesicles (EVs) derived from GBM cells contain important biomarkers, such as microRNAs, proteins, and DNA mutations, which are involved in tumor progression, invasion, and resistance to treatment. Identifying surface markers on these EVs is crucial for their isolation and potential use in noninvasive diagnosis. This study aimed to use tumor-derived explants to investigate the surface markers of EVs and explore their role as diagnostic biomarkers for GBM. Methods: Tumor explants from nine GBM patients without IDH1/IDH2 mutations or 1p-19q co-deletion were cultured to preserve both tumor viability and cytoarchitecture. EVs were collected from the tumor microenvironment using differential centrifugation, filtration, and membrane affinity binding. Their surface protein composition was analyzed through multiplex protein assays. RNA-Seq data from TCGA and GTEx datasets, along with in silico single-cell RNA-seq data, were used to assess EV surface biomarker expression across large GBM patient cohorts. Results: The in vitro model successfully replicated the tumor microenvironment and produced EVs with distinct surface markers. Biomarker analysis in large datasets revealed specific expression patterns unique to GBM patients compared with healthy controls. These markers demonstrated potential as a GBM-specific signature and were correlated with clinical data. Furthermore, in silico single-cell RNA-seq provided detailed insights into biomarker distribution across different cell types within the tumor. Conclusions: This study underscores the efficacy of the tumor-derived explant model and its potential to advance the understanding of GBM biology and EV production. A key innovation is the isolation of EVs from a model that faithfully mimics the tumor’s original cytoarchitecture, offering a deeper understanding of the cells involved in EV release. The identified EV surface markers represent promising targets for enhancing EV isolation and optimizing their use as diagnostic tools. Moreover, further investigation into their molecular cargo may provide crucial insights into tumor characteristics and evolution.
Synergistic Effects of Nonthermal Plasma and Solid Acid Catalysts in Thermo-Catalytic Glycerol Dehydration
Authors: Liu Lu , Yu Fei , Wang Siqun , Ye Xiaofei Philip
Published: November 2024

To enhance the bio-based synthesis of acrolein from glycerol, a hybrid approach combining in situ nonthermal plasma (NTP) with thermo-catalytic dehydration was employed. This study investigated the impact of the reaction temperature and NTP discharge field strength on glycerol conversion, acrolein selectivity, byproduct formation, and coke deposition using two catalysts of silicotungstic acid supported on mesoporous alumina and silica. The results revealed that, while the reaction temperature and NTP field strength exhibited complex interactions, the in situ application of NTP markedly improved both glycerol conversion and acrolein selectivity when optimized for specific temperature–NTP field strength combinations. Additionally, the reaction mechanisms of glycerol dehydration with the two catalysts, in the presence and absence of NTP, were systematically analyzed and discussed based on the experimental data.
Fluorine-Doped Graphene Oxide-Modified Graphite Felt Cathode for Hydrogen Peroxide Generation
Authors: Hu Junling , Wang Zhaohui , Chen Yongmei , Xu Wei
Published: November 2024

Electrochemical oxygen reduction via the two-electron pathway (2e-ORR) is an emerging method for producing H2O2. It is cleaner, safer, and more convenient compared to the anthraquinone process. Graphite felt is one of the cathode candidates for large-scale cells due to its excellent mechanical properties. However, commercial graphite felt often fails to achieve the desired hydrogen-peroxide yield because of its low catalytic selectivity for the 2e-ORR pathway. Fluorine-doped carbon materials are expected to enhance 2e-ORR selectivity. This is because the electronic structure of carbon atoms adjacent to fluorine atoms may facilitate the production of hydrogen peroxide while hindering its further reduction. In this study, fluorine-doped graphene oxide (FGO) was prepared by the hydrothermal method. Subsequently, graphite felt modified with FGO was fabricated and used as the cathode for H2O2 production. The results indicated that in alkaline media, the graphite felt modified with FGO achieved a catalytic selectivity of 93% and a generation rate of 8.91 mg cm⁻2 h⁻¹. In comparison, commercial graphite felt had a catalytic selectivity of 75% and a generation rate of 2.10 mg cm⁻2 h⁻¹. Moreover, graphite felt modified by FGO also exhibited excellent electrocatalytic performance for H2O2 generation in neutral media. This research provides a fundamental study to promote the application of graphite felt in the environmentally friendly electrocatalytic production of hydrogen peroxide in industries.
A Gain-of-Function Mutation in the Ca2+ Channel ORAI1 Causes Stormorken Syndrome with Tubular Aggregates in Mice
Authors: Pérez-Guàrdia Laura , Lafabrie Emma , Diedhiou Nadège , Spiegelhalter Coralie , Laporte Jocelyn , Böhm Johann
Published: November 2024

Store-operated Ca2+ entry (SOCE) controls Ca2+ homeostasis and mediates multiple Ca2+-dependent signaling pathways and cellular processes. It relies on the concerted activity of the reticular Ca2+ sensor STIM1 and the plasma membrane Ca2+ channel ORAI1. STIM1 and ORAI1 gain-of-function (GoF) mutations induce SOCE overactivity and excessive Ca2+ influx, leading to tubular aggregate myopathy (TAM) and Stormorken syndrome (STRMK), two overlapping disorders characterized by muscle weakness and a variable occurrence of multi-systemic anomalies affecting spleen, skin, and platelets. To date, different STIM1 mouse models exist, but only a single ORAI1 mouse model with muscle-specific TAM/STRMK phenotype has been described, precluding a comparative analysis of the physiopathology in all affected tissues. Here, we generated and characterized mice harboring a prevalent ORAI1 TAM/STRMK mutation and we provide phenotypic, physiological, biochemical, and functional data. Examination of Orai1V109M/+ mice revealed smaller size, spleen enlargement, reduced muscle force, and decreased platelet numbers. Morphological analyses of muscle sections evidenced the presence of tubular aggregates, the histopathological hallmark on biopsies from TAM/STRMK patients absent in all reported STIM1 models. Overall, Orai1V109M/+ mice reliably recapitulate the human disorder and highlight the primary physiological defects caused by ORAI1 gain-of-function mutations. They also provide the possibility to investigate the formation of tubular aggregates and to develop a common therapy for different TAM/STRMK forms.
A Cancer-Specific Anti-Podoplanin Monoclonal Antibody, PMab-117-mG2a Exerts Antitumor Activities in Human Tumor Xenograft Models
Authors: Tanaka Tomohiro , Suzuki Hiroyuki , Ohishi Tomokazu , Kaneko Mika K. , Kato Yukinari
Published: November 2024

Podoplanin (PDPN) overexpression is associated with poor clinical outcomes in various tumors. PDPN is involved in malignant tumor progression by promoting invasiveness and metastasis. Therefore, PDPN is considered a promising target of monoclonal antibody (mAb)-based therapy. Because PDPN also plays an essential role in normal cells such as kidney podocytes, cancer specificity is required to reduce adverse effects on normal cells. We developed a cancer-specific mAb (CasMab) against PDPN, PMab-117 (rat IgM, kappa), by immunizing rats with PDPN-overexpressed glioblastoma cells. The recombinant mouse IgG2a-type PMab-117 (PMab-117-mG2a) reacted with the PDPN-positive tumor PC-10 and LN319 cells but not with PDPN-knockout LN319 cells in flow cytometry. PMab-117-mG2a did not react with normal kidney podocytes and normal epithelial cells from the lung bronchus, mammary gland, and corneal. In contrast, one of the non-CasMabs against PDPN, NZ-1, showed high reactivity to PDPN in both tumor and normal cells. Moreover, PMab-117-mG2a exerted antibody-dependent cellular cytotoxicity in the presence of effector splenocytes. In the human tumor xenograft models, PMab-117-mG2a exhibited potent antitumor effects. These results indicated that PMab-117-mG2a could be applied to antibody-based therapy against PDPN-expressing human tumors while reducing the adverse effects.
Liquid Crystal Ordering in Densely Packed Colloidal Suspensions of Highly Anisotropic Monolayer Nanosheets
Authors: Shi Yue , Shuai Min , Shen Yongqiang , Chen Dong , Maclennan Joseph E. , Cheng Zhengdong , Clark Noel A.
Published: November 2024

Monolayer nanosheets of zirconium phosphate in aqueous suspension exhibit short-range repulsion and long-range attraction, producing, at overall volume fractions larger than about half a percent, phase separation into higher-concentration liquid crystal and lower-concentration isotropic regions. At high concentrations, this phase separation takes the form of an emulsion of condensed, liquid-crystalline droplets, which anneal to form lens-shaped tactoids. These tactoids provide an opportunity to study the liquid crystal ordering of inorganic nanosheets in the limit of large shape anisotropy (diameter/thickness~400) and high packing fraction (volume fraction ≳ 70%). The internal liquid crystal structure of the tactoids remains nematic even under conditions that would usually favor ordering into lamellar smectics. Local lamellar ordering is suggested by short-range, smectic-like layer correlations, but a full transition into a smectic phase appears to be inhibited by the nanosheet edges, which act as a perturbative population of dislocation loops in the system of layers. Under conditions of thermal equilibrium, the nanoplates organize positionally to enable bend deformation of the director, a hallmark of the nematic phase and its principal distinction from the smectic, where bend must be expelled.
Three-Dimensional Axisymmetric Analysis of Annular One-Dimensional Hexagonal Piezoelectric Quasicrystal Actuator/Sensor with Different Configurations
Authors: Li Yang , Gao Yang
Published: November 2024

The presented article is about the axisymmetric deformation of an annular one-dimensional hexagonal piezoelectric quasicrystal actuator/sensor with different configurations, analyzed by the three-dimensional theory of piezoelectricity coupled with phonon and phason fields. The state space method is utilized to recast the basic equations of one-dimensional hexagonal piezoelectric quasicrystals into the transfer matrix form, and the state space equations of a laminated annular piezoelectric quasicrystal actuator/sensor are obtained. By virtue of the finite Hankel transform, the ordinary differential equations with constant coefficients for an annular quasicrystal actuator/sensor with a generalized elastic simple support boundary condition are derived. Subsequently, the propagator matrix method and inverse Hankel transform are used together to achieve the exact axisymmetric solution for the annular one-dimensional hexagonal piezoelectric quasicrystal actuator/sensor. Numerical illustrations are presented to investigate the influences of the thickness-to-span ratio on a single-layer annular piezoelectric quasicrystal actuator/sensor subjected to different top surface loads, and the effect of material parameters is also presented. Afterward, the present model is applied to compare the performance of different piezoelectric quasicrystal actuator/sensor configurations: the quasicrystal multilayer, quasicrystal unimorph, and quasicrystal bimorph.
Demonstration of T-Cell Monotypia Using Anti-TCRbeta1/2 (TRBC1/2) Immunostaining as a Rapid and Cost-Effective Alternative to PCR-Based Clonality Studies for the Diagnosis of T-Cell Lymphoma
Authors: Soilleux Elizabeth J. , Rodgers Daniel T. , Situ Jinlong J. , Evans Shelley C. , Konda Venkata N. , Yang Han-Chieh , Pang Jianxiong , Gilbey Smith Isabella , Rajesh Pete , Salimi Maryam , Ng Soo Weei , Jones Julia , Miller Jodi L. , Etherington Rachel , Ashton-Key Margaret , Ogg Graham
Published: November 2024

Background/Objectives: T-cell lymphomas are often histologically indistinguishable from benign T-cell infiltrates, and diagnosis typically relies on slow, complex, and expensive multiplexed PCR reactions, requiring significant training and experience to interpret them. We aimed to raise highly specific antibodies against the two alternatively used and very similar T-cell receptor beta constant regions, TCRbeta1 and TCRbeta2, encoded by the TRBC1 and TRBC2 gene segments, respectively. We sought to demonstrate the feasibility of detecting TCRbeta1 and TCRbeta2 immunohistochemically in routine clinical (formalin-fixed, paraffin-embedded (FFPE)) tissue sections as a novel diagnostic strategy for T-cell lymphomas. Methods: Recombinant rabbit antibodies were validated using Western blotting and FFPE immunostaining of T-cell leukemia lines. The immunostaining of FFPE tissue containing benign and lymphomatous T-cell populations was undertaken, with corroboration by BaseScopeTM high-sensitivity in situ hybridization and quantitative real-time PCR (Q-PCR). An additional Q-PCR literature review and analysis of publicly available RNAseq data was used to determine the TCRbeta2/TCRbeta1 ratio cut-off to separate benign and malignant T-cell populations. Results: Our TCRbeta1/TCRbeta2 antibody pair gave highly specific FFPE tissue staining. All benign samples analyzed (immunohistochemically, by BaseScopeTM, by Q-PCR, and by RNAseq data analysis) had TCRbeta1/TCRbeta2 or TRBC1/TRBC2 ranges well within the previously published flow cytometric benign range (TCRbeta2/TCRbeta1 = 0.18:1–5.7:1), while samples of T-cell lymphoma did not. One out of thirteen (7.7%) lymphoma samples showed some detectable TCRbeta1/TCRbeta2 protein co-expression, and 4 out of 13 (30.8%) T-cell lymphomas showed a TRBC1/TRBC2 transcript co-expression using BaseScopeTM. Conclusions: Analyzing T-cell monotypia immunohistochemically, analogous to B-cell monotypia (kappa: lambda ratio for B-cell and plasma cell neoplasms), could make the diagnosis of T-cell lymphomas cheaper, quicker, and more accurate. Larger studies are needed to validate our antibodies for clinical use.
Plasma Treatment Technologies for GaN Electronics
Authors: Li Botong , Rahaman Imteaz , Ellis Hunter D. , Fu Houqiang , Zhao Yuji , Cai Yong , Zhang Baoshun , Fu Kai
Published: November 2024

Nowadays, the third-generation semiconductor led by GaN has brought great changes to the semiconductor industry. Utilizing its characteristics of a wide bandgap, high breakdown Electric field, and high electron mobility, GaN material is widely applied in areas such as 5G communication and electric vehicles to improve energy conservation and reduce emissions. However, with the progress in the development of GaN electronics, surface and interface defects have become a main problem that limits the further promotion of their performance and stability, increasing leakage current and causing degradation in breakdown voltage. Thus, to reduce the damage, Plasma treatment technologies are introduced in the fabrication process of GaN electronics. Up to now, designs like the high-resistivity p-GaN cap Layer, passivating termination, and surface recovery process have been established via Plasma treatment, reaching the goals of normally-off transistors, diodes with high breakdown voltage and high-reliability GaN electronics, etc. In this article, hydrogen, fluorine, oxygen, and nitrogen Plasma treatment technologies will be discussed, and their application in GaN electronics will be reviewed and compared.
Closing the Gap Between Electrical and Physical Design Steps with an Analog IC Placement Optimizer Enhanced with Machine-Learning-Based Post-Layout Performance Regressors
Authors: Martins Ricardo
Published: November 2024

The design of integrated circuits in the analog spectrum is intricate due to the signals’ continuous nature. Additionally, it is strongly affected by the physical implementation of their devices and interconnections on the layout, a design task that has stubbornly defied all automation attempts. In this paper, one limitative factor is identified that must be addressed to finally push automation tools into the analog integrated circuit design flow: accurate assessment of post-layout performance degradation. For this purpose, a performance-driven placement generator highly integrated with off-the-shelf tools already adopted by circuit/layout designers, i.e., circuit simulator, verification tools (layout-versus-schematic) and layout extractor, is proposed. Toward maximum post-layout accuracy, this generator promotes an exhaustive simulation-based synthesis, extracting, simulating and verifying the post-layout functional behavior of every candidate floorplan. Additionally, to bypass the time-consuming extractions/simulations and accelerate synthesis, novel post-layout performance regressors based on different highly accurate machine learning techniques are also being developed. The data used to train them can be directly and conveniently acquired from previous precise post-placement simulations. Experimental results over two analog circuit structures show that a set of performance regressors based on tree-based models, while operating on compressed design spaces, allow for the speeding up of synthesis by more than 20×, which represents a step toward an efficient fully automatic performance-driven analog integrated circuit design flow.
Study of Photodegradation of Organic Solar Cells Under Brazilian Climate Conditions
Authors: Moraes Lucas Phillip Z. G. , Diniz Antonia Sonia A. C. , Viana Marcelo Machado , Kazmerski Lawrence L. , Soares Gabriela A.
Published: November 2024

The increasing technical and economic viability of photovoltaic solar energy technologies includes modules with organic photovoltaic (OPV) cells, which have shown significant efficiency increases, reaching 20% for research devices. This study investigated the photodegradation and associated loss mechanisms in OPV devices under tropical conditions in Brazil. The electrical and optical characteristics of the modules were correlated with chemical and structural changes when exposed to sunlight. Electrical parameters were monitored over time on external test benches and measured in solar simulators, while changes in the optical transmission and absorption of the films were analyzed. Scanning electron microscopy, energy-dispersive spectroscopy, and Fourier-transform infrared spectroscopy were used to study the physical and chemical properties of the materials. We found that photodegradation causes bound breakage in the active layer, altering the carbon structure and consequently reducing the module’s output power. The primary reasons for the activation and progression of this mechanism are high temperature and elevated solar irradiance. Therefore, we demonstrate that understanding these mechanisms is essential for the development of more sustainable OPVs in tropical climates.
Purification and Identification of the Nematicidal Activity of S1 Family Trypsin-Like Serine Protease (PRA1) from Trichoderma longibrachiatum T6 Through Prokaryotic Expression and Biological Function Assays
Authors: Ma Nan , Lv Hang , Boamah Solomon , Zhang Shuwu , Xu Bingliang
Published: November 2024

Background/Objectives: Heterodera avenae is a highly significant plant-parasitic nematode, causing severe economic losses to global crop production each year. Trichoderma species have been found to parasitize nematodes and control them by producing enzymes that degrade eggshells. The T. longibrachiatum T6 (T6) strain has been demonstrated the parasitic and lethal effects on H. avenae cysts and eggs, associated with the increased serine protease activity and trypsin-like serine protease gene (PRA1) expression. Methods: Our present study aimed to purify the recombinant PRA1 protease through a prokaryotic expression system and identify its nematicidal activity. Results: The recombinant PRA1 protease was identified as S1 family trypsin-like serine protease, with a molecular weight of 43.16 kDa. The purified soluble protease exhibited the optimal activity at 35 °C and pH 8.0, and also demonstrating higher hydrolytic ability toward casein and skimmed milk. Meanwhile, the Ca2+ and Mg2+ enhanced its activity, while the inhibitor PMSF significantly reduced it. The contents of H. avenae eggs leaked out after treatment with the recombinant PRA1 protease, with egg hatching inhibition and relative hatching inhibition rates at 70.60% and 66.58%, respectively. In contrast, there was no sign of content dissolution, and embryos developed normally in the control group. Conclusions: Our present study revealed that the PRA1 protease of T6 strain has a lethal effect on H. avenae eggs, which providing a theoretical basis for developing biocontrol agents to control nematodes.
The Economic Impact of Post-Traumatic Stress Disorder Among Patients with Systemic Autoimmune Diseases During the COVID-19 Pandemic
Authors: Lorenzoni Valentina , Andreozzi Gianni , Palla Ilaria , Tani Chiara , Carmassi Claudia , Fulvio Giovanni , Trentin Francesca , Fantasia Sara , Conti Lorenzo , Dell’Osso Liliana , Mosca Marta , Turchetti Giuseppe
Published: November 2024

Background: The present work aimed to estimate the economic impact of PTSD following COVID-19 in a population of patients affected by systemic autoimmune disease (SAD) using a cost-of-illness approach and accounting for the perspective of society. Methods: Considering data collected from SAD patients enrolled in a specialized outpatient clinic in the Tuscany region, Italy, generalized linear models and LASSO logistic regression were used to evaluate the impact of PTSD on costs and its relevance as a possible predictor of being a high-cost patient, respectively. Results: Considering 301 SAD patients, 161 (51.2%) of whom were diagnosed with PTSD, the overall costs were EUR 3670 [890; 40,529] per patient/year among patients with PTSD and EUR 2736.7 [283; 21,078] per patient/year among those without PTSD (p-value < 0.001), with differences mainly attributable to significantly greater direct non-healthcare and indirect costs. PTSD was estimated to increase overall costs (β = 0.296 (0.140), p-value = 0.035), direct non-healthcare (β = 1.193 (0.392), p-value = 0.002), and indirect costs (β = 3.741 (1.136), p-value = 0.001). PTSD diagnosis was also significantly associated with the likelihood of being a high-cost patient. Conclusions: Findings from the present study offer a novel perspective on the economic impact of COVID-19 and provide valuable data for policymakers to better understand the demand for healthcare services and associated costs.
Population Distribution Forecasting Based on the Fusion of Spatiotemporal Basic and External Features: A Case Study of Lujiazui Financial District
Authors: Cheng Xianzhou , Wang Xiaoming , Jiang Renhe
Published: November 2024

Predicting the distribution of people in the time window approaching a disaster is crucial for post-disaster assistance activities and can be useful for evacuation route selection and shelter planning. However, two major limitations have not yet been addressed: (1) Most spatiotemporal prediction models incorporate spatiotemporal features either directly or indirectly, which results in high information redundancy in the parameters of the prediction model and low computational efficiency. (2) These models usually incorporate certain basic and external features, and they can neither change spatiotemporal addressed features according to spatiotemporal features nor change them in real-time according to spatiotemporal features. The spatiotemporal feature embedding methods for these models are inflexible and difficult to interpret. To overcome these problems, a lightweight population density distribution prediction framework that considers both basic and external spatiotemporal features is proposed. In the study, an autoencoder is used to extract spatiotemporal coded information to form a spatiotemporal attention mechanism, and basic and external spatiotemporal feature attention is fused by a fusion framework with learnable weights. The fused spatiotemporal attention is fused with Resnet as the prediction backbone network to predict the people distribution. Comparison and ablation experimental results show that the computational efficiency and interpretability of the prediction framework are improved by maximizing the scalability of the spatiotemporal features of the model by unleashing the scalability of the spatiotemporal features of the model while enhancing the interpretability of the spatiotemporal information as compared to the classical and popular spatiotemporal prediction frameworks. This study has a multiplier effect and provides a reference solution for predicting population distributions in similar regions around the globe.
The Role of T Cells in the Pathogenesis of Narcolepsy Type 1: A Narrative Review
Authors: Xu Wenqi , Ding Wenting , Zhang Yu , Wang Shuanshuan , Yan Xianyu , Xu Yirui , Zhi Xiaoying , Liu Rongzeng
Published: November 2024

Narcolepsy type 1 (NT1) is an uncommon, persistent sleep disorder distinguished by significant daytime sleepiness, episodes of cataplexy, and irregularities in rapid eye movement sleep. The etiology of NT1 is linked to the destruction of hypothalamic neurons responsible for the synthesis of the wake-promoting neuropeptide known as hypothalamic orexin. The pathophysiological mechanisms underlying NT1 remain inadequately elucidated; however, a model that incorporates the interplay of genetic predisposition, environmental influences, immune system factors, and a deficiency in hypocretin (HCRT) provides a framework for elucidating the pathogenesis of NT1. The prevalence of NT1 has been observed to rise following influenza A (H1N1) pdm09 and the administration of the Pandemrix influenza vaccine. The strong association between narcolepsy and the HLA-DQB1*06:02 allele strongly indicates an autoimmune etiology for this condition. Increasing evidence suggests that T cells play a critical role in this autoimmune-mediated HCRT neuronal loss. Studies have identified specific T cell subsets, including CD4+ and CD8+ T cells, that target HCRT neurons, contributing to their destruction. Clarifying the pathogenesis of NT1 driven by autoimmune T cells is crucial for the development of effective therapeutic interventions for this disorder. This review examines the risk factors associated with the pathogenesis of NT1, explores the role of T cells within the immune system in the progression of NT1, and evaluates immune-mediated animal models alongside prospective immunotherapeutic strategies.
DLK1 Is Associated with Stemness Phenotype in Medullary Thyroid Carcinoma Cell Lines
Authors: da Silva Danilo Dias , Araldi Rodrigo Pinheiro , Belizario Mariana Rocha , Rocha Welbert Gomes , Maciel Rui Monteiro de Barros , Cerutti Janete Maria
Published: November 2024

Medullary thyroid carcinoma (MTC) is a rare and aggressive tumor, often requiring systemic treatment in advanced or metastatic stages, where drug resistance presents a significant challenge. Given the role of cancer stem cells (CSCs) in cancer recurrence and drug resistance, we aimed to identify CSC subpopulations within two MTC cell lines harboring pathogenic variants in the two most common MEN2-associated codons. We analyzed 15 stemness-associated markers, along with well-established thyroid stem cell markers (CD133, CD44, and ALDH1), a novel candidate (DLK1), and multidrug resistance proteins (MRP1 and MRP3). The ability to efflux the fluorescent dye Hoechst 3342 and form spheroids, representing CSC behavior, was also assessed. MZ-CRC-1 cells (p.M918T) displayed higher expressions of canonical markers, DLK1, and MRP proteins than TT cells (p.C634W). MZ-CRC-1 cells also formed more spheroids and showed less dye accumulation (p < 0.0001). Finally, we observed that DLK1+ cells (those expressing DLK1) in both cell lines exhibited significantly higher levels of stemness markers compared to DLK1− cells (those lacking DLK1 expression). These findings underscore DLK1’s role in enhancing the stemness phenotype, providing valuable insights into MTC progression and resistance and suggesting potential therapeutic implications.
Complete Mitogenomes of Xinjiang Hares and Their Selective Pressure Considerations
Authors: Wang Ruijie , Tursun Mayinur , Shan Wenjuan
Published: November 2024

Comparative analysis based on the mitogenomes of hares in Xinjiang, China, is limited. In this study, the complete mitochondrial genomes of seven hare samples including four hare species and their hybrids from different environments were sequenced, assembled, and annotated. Subsequently, we performed base content and bias analysis, tRNA analysis, phylogenetic analysis, and amino acid sequence analysis of the annotated genes to understand their characteristics and phylogenetic relationship. Their mitogenomes are circular molecules (from 16,691 to 17,598 bp) containing 13 protein-coding genes, two rRNA genes, 22 tRNA genes, and a control region, which are similar with other Lepus spp. worldwide. The relative synonymous codon usage analysis revealed that the adaptation of Lepus yarkandensis to its unique arid and hot environment might be associated with synthesizing amino acids like alanine, leucine, serine, arginine, and isoleucine and the terminator caused by the different usage of codons. Further, we utilized the MEME model and identified two positive selection genes (ND4, ND5) in Lepus tibetanus pamirensis and one (ND5) in L. yarkandensis that might be important to their adaptation to the plateau and dry and hot basin environments, respectively. Meanwhile, Lepus tolai lehmanni and Lepus timidus may have evolved different adaptive mechanisms for the same cold environment. This study explored the evolutionary dynamics of Xinjiang hares’ mitochondrial genomes, providing significant support for future research into their adaptation mechanisms in extreme environments.
Discrete Fourier Transform in Unmasking Deepfake Images: A Comparative Study of StyleGAN Creations
Authors: Convertini Vito Nicola , Impedovo Donato , Lopez Ugo , Pirlo Giuseppe , Sterlicchio Gioacchino
Published: November 2024

This study proposes a novel forgery detection method based on the analysis of frequency components of images using the Discrete Fourier Transform (DFT). In recent years, face manipulation technologies, particularly Generative Adversarial Networks (GANs), have advanced to such an extent that their misuse, such as creating deepfakes indistinguishable to human observers, has become a significant societal concern. We reviewed two GAN architectures, StyleGAN and StyleGAN2, generating synthetic faces that were compared with real faces from the FFHQ and CelebA-HQ datasets. The key results demonstrate classification accuracies above 99%, with F1 scores of 99.94% for Support Vector Machines and 97.21% for Random Forest classifiers. These findings underline the fact that performing frequency analysis presents a superior approach to deepfake detection compared to traditional spatial detection methods. It provides insight into subtle manipulation cues in digital images and offers a scalable way to enhance security protocols amid rising digital impersonation threats.
Maternal Nutritional Factors Enhance Birthweight Prediction: A Super Learner Ensemble Approach
Authors: Mursil Muhammad , Rashwan Hatem A. , Cavallé-Busquets Pere , Santos-Calderón Luis A. , Murphy Michelle M. , Puig Domenec
Published: November 2024

Birthweight (BW) is a widely used indicator of neonatal health, with low birthweight (LBW) being linked to higher risks of morbidity and mortality. Timely and precise prediction of LBW is crucial for ensuring newborn health and well-being. Despite recent machine learning advancements in BW classification based on physiological traits in the mother and ultrasound outcomes, maternal status in essential micronutrients for fetal development is yet to be fully exploited for BW prediction. This study aims to evaluate the impact of maternal nutritional factors, specifically mid-pregnancy plasma concentrations of vitamin B12, folate, and anemia on BW prediction. This study analyzed data from 729 pregnant women in Tarragona, Spain, for early BW prediction and analyzed each factor’s impact and contribution using a partial dependency plot and feature importance. Using a super learner ensemble method with tenfold cross-validation, the model achieved a prediction accuracy of 96.19% and an AUC-ROC of 0.96, outperforming single-model approaches. Vitamin B12 and folate status were identified as significant predictors, underscoring their importance in reducing LBW risk. The findings highlight the critical role of maternal nutritional factors in BW prediction and suggest that monitoring vitamin B12 and folate levels during pregnancy could enhance prenatal care and mitigate neonatal complications associated with LBW.
Drosophila as a Model for Human Disease: Insights into Rare and Ultra-Rare Diseases
Authors: Casas-Tintó Sergio
Published: November 2024

Rare and ultra-rare diseases constitute a significant medical challenge due to their low prevalence and the limited understanding of their origin and underlying mechanisms. These disorders often exhibit phenotypic diversity and molecular complexity that represent a challenge to biomedical research. There are more than 6000 different rare diseases that affect nearly 300 million people worldwide. However, the prevalence of each rare disease is low, and in consequence, the biomedical resources dedicated to each rare disease are limited and insufficient to effectively achieve progress in the research. The use of animal models to investigate the mechanisms underlying pathogenesis has become an invaluable tool. Among the animal models commonly used in research, Drosophila melanogaster has emerged as an efficient and reliable experimental model for investigating a wide range of genetic disorders, and to develop therapeutic strategies for rare and ultra-rare diseases. It offers several advantages as a research model including short life cycle, ease of laboratory maintenance, rapid life cycle, and fully sequenced genome that make it highly suitable for studying genetic disorders. Additionally, there is a high degree of genetic conservation from Drosophila melanogaster to humans, which allows the extrapolation of findings at the molecular and cellular levels. Here, I examine the role of Drosophila melanogaster as a model for studying rare and ultra-rare diseases and highlight its significant contributions and potential to biomedical research. High-throughput next-generation sequencing (NGS) technologies, such as whole-exome sequencing and whole-genome sequencing (WGS), are providing massive amounts of information on the genomic modifications present in rare diseases and common complex traits. The sequencing of exomes or genomes of individuals affected by rare diseases has enabled human geneticists to identify rare variants and identify potential loci associated with novel gene–disease relationships. Despite these advances, the average rare disease patient still experiences significant delay until receiving a diagnosis. Furthermore, the vast majority (95%) of patients with rare conditions lack effective treatment or a cure. This scenario is enhanced by frequent misdiagnoses leading to inadequate support. In consequence, there is an urgent need to develop model organisms to explore the molecular mechanisms underlying these diseases and to establish the genetic origin of these maladies. The aim of this review is to discuss the advantages and limitations of Drosophila melanogaster, hereafter referred as Drosophila, as an experimental model for biomedical research, and the applications to study human disease. The main question to address is whether Drosophila is a valid research model to study human disease, and in particular, rare and ultra-rare diseases.
Temperature-Dependent Pupation Depth in the Oriental Fruit Fly Bactrocera dorsalis and Its Implications for Biological Control
Authors: Lin Mu-Rung , Okuyama Toshinori
Published: November 2024

The oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), is a notable agricultural pest that undergoes pupation in the soil. Mortality risk from predation and parasitism decreases as the depth of the pupal location increases from the ground surface, with a one-centimetre increase in depth causing a significant change. Soil properties, such as moisture and hardness, influence pupation depth, but the effect of temperature has not been fully tested. This laboratory study examined whether a biologically important variation in pupation depth (e.g., one centimetre) is caused by naturally experienced temperature variations (20 to 35 °C) in B. dorsalis. The temperature–pupation depth relationship revealed a unimodal pattern, with the deepest pupation occurring at intermediate temperature levels and shallower pupation at the two extreme temperature ranges. Strong quantitative effects were observed, with the highest mean pupation depth of 40.8 mm at 27.5 °C and the lowest mean pupation depth of 15 mm at 35 °C. The observed quantitative effect suggests that temperature can strongly affect pupal mortality from predators and parasitoids by influencing pupation depth. Future studies that reveal the ability of biological control agents to forage underground for pupae at different temperatures are awaited, as this is key information for evaluating the effectiveness of these agents.