bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Impact of No-Tillage Duration on Soil Aggregate Size Distribution, Stability and Aggregate Associated Organic Carbon
Authors: Phefadu Kopano Conferance , Munjonji Lawrence
Published: October 2024

Soil aggregation results from the rearrangement, flocculation and cementation of primary soil particles. Furthermore, the aggregates undergo transformation under no-tillage (NT) overtime. Soil organic carbon (OC) is the major component of soil organic matter and is protected within aggregates and can serve as a proxy for soil structural stability. Organic matter contributes significantly to the formation of soil aggregates and the carbon within them is protected against degradation. This study assessed the impact of tillage systems, soil depth and no-till duration on soil aggregate size distribution, stability and aggregate associated carbon. It was carried out in Thohoyandou (Tshivhilwi and Dzingahe), Vhembe district, Limpopo province, South Africa. The soil samples were collected from NT, conventional tillage (CT) and virgin (VG) fields in the topsoil (0–30 cm) and subsoil (30–60 cm) at each location. The duration of NT for fields in Tshivhilwi and Dzingahe were 8 years (short-term) and >40 years (long-term), respectively. The results showed that macro-aggregates constituted the largest proportion of aggregates, with a percentage contribution of >60% during the short-term and long-term. The mean weight diameter (MWD) varied significantly between NT and VG in the subsoil for the short-term NT. The aggregates were more stable in the short-term NT than long-term NT. Organic carbon in all aggregate fractions between the tillage systems in the topsoil was not significantly affected after more than 40 years. The MWD was higher in the subsoil than topsoil in NT and CT during both periods. Micro-aggregates contained greater OC than other fractions. The study showed that the impact of NT on aggregation, structural stability and the capacity to store carbon vary overtime. It is recommended that the aggregation and/or structural stability of different soil textures under NT with different cropping systems and management practices should be studied periodically.
Corn Straw Mulching Mechanized No-Tillage Approach Optimizes Farmland Soil Temperature to Increase Potato Yield in Regions of Northwestern China
Authors: Li Hui , Liu Pengxia , Zhang Hua , Liu Xiaolong , Chang Lei , Sun Wei
Published: October 2024

Straw mulching cultivation technology can improve the soil environment of farmland, and it is applied in the dry farming area of Northwestern China. There are few studies on the effect of corn straw mulching on the soil temperature and yield of potato fields in dry land in Northwestern China. In this paper, three treatments, black film ridge (HM), corn straw mulching mechanized no-tillage planting (JG) and no-covering open field flat planting (CK), were set up in the period of 2022 to 2023. A field plot experiment was carried out to determine the soil temperature, growth index, and yield data during the key growth period. The statistical analysis results show that JG and HM significantly increased the potato yield, by 12.27~18.30% and 13.09~18.10%, compared with CK, but there was no significant difference between JG and HM. The yield was significantly positively correlated with tuber weight per plant at the tuber expansion stage, starch accumulation stage, and harvest stage (0.47 *~0.60 **), and significantly negatively correlated with the number of tubers at the harvest stage (−0.54 *). Compared with CK, HM increased the average soil temperature over the whole growth period by 0.27~0.92 °C. In 2022, the increase in the 5 cm soil layer in the tuber expansion period was the largest, reaching 0.83 °C. In 2023, the increase in the 5 cm soil layer in the starch accumulation period was the largest, reaching 3.08 °C. JG reduced the soil temperature over the whole growth period by 0.52 °C, and the 20 cm soil layer in the tuber formation period decreased the most, reaching 1.45 °C, which aggravated the soil temperature change over the whole growth period (the amplitude was 4.13~4.53 °C). The temperature difference between day and night in different growth periods in 2022 was 2.14~5.41 °C, and the soil temperature in some growth periods in 2022 even exceeded that with HM. The results showed that JG could regulate soil temperature and optimize the relationship between tuber weight per plant, tuber number per plant, and biomass allocation during tuber formation, which are beneficial for the improvement of the potato yield in the dry farming area of Northwestern China.
Cropping System and Technology Responses of Rainfed Agriculture to Conservation Set-Asides in China Under the Grain for Green Program
Authors: Yao Shunbo , Lin Ying , Wang Yao
Published: October 2024

Conservation set-asides face a trade-off between soil erosion control and grain security. Using the Grain for Green Program (GGP) in China’s Loess Plateau as a case study, this study aims to reveal the main source of productivity improvements that help offset the possible negative effect of conservation set-asides on grain supply. For empirical estimation purposes, we combine county-level remote sensing data with detailed grain production information from 209 counties in the Loess Plateau, spanning from 2000 to 2015. The satellite image interpretation and statistical records show that the area of arable land has decreased while the grain supply has been increasing in the Loess Plateau since 2000. A multiple-mediation analysis reveals that the GGP has a negligible total effect on the grain supply, which contributes to the positive mediating effect of multiple cropping, rather than technological progress. Further analysis shows that the increasing land-use intensity exerts higher water stress on areas with less rainfall. The results indicate that studies investigating conservation set-asides and food security relationships should not overlook the changes in land-use intensity, especially in water-scarce areas.
Incorporation of Ceragenins into Medical Adhesives and Adhesive Scar Tape to Prevent Microbial Colonization Common in Healthcare-Associated Infections
Authors: Zaugg Aaron , Sherren Elliot , Yi Rebekah , Farnsworth Alex , Pauga Fetutasi , Linder Anna , Kelly Lauren , Takara Meg , Hoather McKenna , Stump Sierra , Behunin Christine , Boyack Boston , Tolley Morgan , Holland Kayla , Salmon Morgann , Deng Shenglou , Patterson James E. , Savage Paul B.
Published: October 2024

Background/Objectives: Healthcare-associated infections involving surgical sites, skin trauma, and devices penetrating the skin are a frequent source of increased expense, hospitalization periods, and adverse outcomes. Medical adhesives are often employed to help protect compromised skin from infection and to secure medical devices, but adhesives can become contaminated by pathogens, exposing wounds, surgical sites, and medical devices to colonization. We aimed to incorporate ceragenins, a class of antimicrobial agents, into silicone- and polyacrylate-based adhesives with the goal of reducing adhesive contamination and subsequent infections. Methods: Three adhesives were developed and evaluated for the release of ceragenins, antimicrobial efficacy, adhesive strength, and dermal irritation. Results: Elution profiles over two weeks showed a high initial release followed by steady, long-term release. Standard microbial challenges of the adhesives by methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, or Candida albicans demonstrated microbial reduction for 6 to 68 days. Lap shear adhesive strength was not reduced for polyacrylate adhesives containing ceragenins, and no dermal irritation was observed in an in vivo model. Conclusions: Ceragenin-containing adhesive materials appear well suited for prevention of bacterial and fungal infections associated with medical devices and bandages.
VULREM: Fine-Tuned BERT-Based Source-Code Potential Vulnerability Scanning System to Mitigate Attacks in Web Applications
Authors: Gürfidan Remzi
Published: October 2024

Software vulnerabilities in web applications are one of the sensitive points in data and application security. Although closing a vulnerability after it is detected in web applications seems to be a solution, detecting vulnerabilities in the source code before the vulnerability is detected effectively prevents malicious attacks. In this paper, we present an improved and automated Bidirectional Encoder Representations from Transformers (BERT)-based approach to detect vulnerabilities in web applications developed in C-Sharp. For the training and testing of the proposed VULREM (Vulnerability Remzi) model, a dataset of eight different CVE (Common Vulnerabilities and Exposures)-numbered critical vulnerabilities was created from the source code of six different applications specific to the study. In the VULREM model, fine-tuning was performed within the BERT model to obtain maximum accuracy from the dataset. To obtain the optimum performance according to the number of source-code lines, six different input lengths were tested with different batch sizes. Classification metrics were used for the testing and performance evaluation of the model, and an average F1-score of 99% was obtained for the best sequence length according to eight different vulnerability classifications. In line with the findings obtained, this will play an important role in both vulnerability detection in web applications of the C-Sharp language and in detecting and correcting critical vulnerabilities in the developmental processes of web applications, with an accuracy of 99%.
The Influence of Ionizing Radiation on Fluoride Release from Restorative Dental Materials: A Comparative In Vitro Study
Authors: Čekalović Agović Sara , Klarić Eva , Ivanišević Ana , Soče Majana , Grego Timor , Radin Nujić Irena
Published: October 2024

To examine the effect of ionizing radiation on fluoride release from restorative dental materials, samples of Equia Forte HT, Fuji Triage, Fuji IX, Cention Forte, Activa Presto, Beautifil II, and Luminos (n = 10) were made in Teflon molds and divided into a control group and an experimental group. The experimental group was exposed to ionizing radiation for a total of 35 days (70 Gy, 2 Gy per day). The fluoride release was measured with a fluorine-selective electrode. The median recorded fluoride values were higher with Equia Forte HT, Fuji Triage, and Fuji IX compared to others during the entire period in both groups. With Activa Presto, a higher release of fluoride was recorded in the experimental group on the first day of irradiation, while a higher release was recorded in the control group, as well as with Luminos and Beautifil II. With Cention Forte, there was no significant difference in fluoride release between the experimental and control groups except on the sixth day. With Fuji Triage and Fuji IX, the release of fluoride was higher in the experimental group compared to the control group, while with Equia Forte HT, there was no difference between the groups. In conclusion, ionizing radiation has no major effect on fluoride release in all the tested materials.
MSSI System Combined with Dispersion-Managed Link Configured with Random-Based RDPS Differently Controlled by Fiber Length
Authors: Chung Jae-Pil , Lee Seong-Real
Published: October 2024

We numerically demonstrate the dispersion map configured by random-based residual dispersion per span (RDPS) applied into the mid-span spectral inversion (MSSI) system to mitigate the impact of chromatic dispersion and the fiber nonlinearity in wavelength division multiplexed (WDM) signals. The dispersion map proposed was a scheme in which the RDPS of all optical fiber spans in the front section of the midway optical phase conjugator (OPC) are randomly selected, and the arrangement order of the RDPS in the rear section is inverted from that of the front section. Numerical simulations were performed by evaluating the compensation of the distorted 960 Gb/s WDM signal as a function of the variation of the DCF length and the SMF length, which are involved in determining RDPS. It was confirmed that the compensation effect of the proposed dispersion maps has improved compared to the conventional dispersion map since the dispersion maps examined in this paper have antipodal symmetry around the midway OPC. In particular, it was confirmed that the method of randomly determining the RDPSs by varying the DCF length slightly improved system performance compared to the variation of SMF lengths. We also found that the feature of the RDPS random distribution patterns can achieve excellent compensation for the distorted WDM signal through 50 iterations.
Special Issue: Recent Advances in Pathogenesis and Management of Eye Diseases
Authors: Maugeri Grazia , D’Agata Velia
Published: October 2024

The pathogenesis and management of eye diseases have seen significant advancements in recent years, driven by technological innovations, a deeper understanding of molecular mechanisms, and novel therapeutic approaches [...]
Numerical Simulation and Analysis of the Manufacturing Process of Pre-Bulged Rupture Discs
Authors: Treude Benjamin , Anders Denis , Weinberg Kerstin
Published: October 2024

Rupture discs, also known as bursting discs, are indispensable components in fluid-operated systems providing effective protection against hazardous over-pressure or partial vacuum. They belong to a special class of safety devices and are found in a variety of technical applications including pressure vessels, piping systems, reactors and boilers. In all application scenarios, rupture discs act as sacrificial parts that have to fail precisely at a predetermined differential pressure, opening a relief flow path for the working fluid. The membrane employed within rupture discs is usually made out of specific metal alloys or different material layers depending on the particular application. However, for many manufacturers of rupture discs, the production process is characterized by a lack of systematic procedures, relying instead on trial and error as well as empirical values. By means of thorough finite-element-based modeling and simulation of the bulge-forming process of rupture discs, including an elastic–plastic material law, large deformation, as well as contact mechanics, it is possible to accurately predict the resulting stress–strain behavior. All simulation results are rigorously validated through corresponding experiments conducted during the bulge-forming process. Therefore, this contribution provides a reliable basis for the parameter set-up during the manufacturing process of rupture discs.
Impact of Various High Intensity Earthquake Characteristics on the Inelastic Seismic Response of Irregular Medium-Rise Buildings
Authors: Pachla Filip , Tatara Tadeusz , Aldabbik Waseem
Published: October 2024

In the twenty-first century, the seismic design of buildings seems to have become a fully recognized topic. There are guidelines and standards which should be taken into account by designers in seismic areas. Designers using modern international guidelines have ascertained that the behavior of structures is not as expected. New challenges in the construction industry result in the construction of structures with new, unusual shapes. These are structures that do not meet the assumptions of safe construction in seismic areas. Contemporary buildings are also characterized by their irregular distribution of structural elements. Such solutions are not beneficial from the point of view of seismic engineering and can lead to reduced dynamic resistance and damage in such structures. In this paper, a five-storey, irregular-shaped reinforced concrete (RC) building model was subjected to different earthquakes with varying magnitudes, PGA (peak ground acceleration) and PGV (peak ground velocity) values, and durations of the intense shock phase. Once the model was verified using previous in situ measurements, the building model was subjected to five earthquakes. A numerical nonlinear analysis of the building was performed using a verified FEA (finite element analysis) model in the time domain through non-linear time history analysis with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method. The building’s dynamic properties were measured using various methods of excitation. The model was influenced, among others, by two far-field representative events caused by the last earthquake in Turkey, which resulted in strong ground motion. The analysis results identified the locations of structural damage and allowed for the assessment of the structure’s dynamic resistance. The results of the calculations prove that the duration of the intensive phase of extortion is one of the reasons for building damage in earthquake-prone areas. Building damage occurs with earthquakes that are characterized by an intensive phase of excitation with a long duration and high values of velocity in the earthquake components. The article highlights the inadequate dynamic resistance of the building, leading to excessive displacements and unfavorable structural solutions. Damage to buildings at this earthquake intensity caused damage to the load-bearing structure, which was not designed for such intensities. This paper is a research report with a specific case study of medium-rise irregular RC buildings.
Proteomic Analysis to Understand the Promotive Effect of Ethanol on Soybean Growth Under Salt Stress
Authors: Komatsu Setsuko , Nishiuchi Takumi
Published: October 2024

Finding solutions to mitigate the impact of salinity on crops is important for global food security because soil salinity significantly reduces plant growth and grain yield. Ethanol may play an important role in mitigating the negative salt-induced effects on crops. Soybean root growth was significantly reduced under salt stress; however, it was restored and comparable to control values by ethanol application even under stress. To study the positive mechanism of ethanol on soybean growth, a proteomic approach was carried out. The categories with the greatest changes in protein numbers were protein metabolism, transport, and cell organization in biological processes, nucleus and cytosol in cellular components, and nucleic acid binding activity in molecular functions. Proteomic data were confirmed using immunoblot analysis. Reactive oxygen species enzymes increased under salt stress; among them, mitochondrial ascorbate peroxidase was further accumulated by ethanol application. Among the cell wall and membrane-associated proteins, xyloglucan xyloglucosyl transferase and H+-ATPase increased and decreased, respectively, under salt stress; however, they were restored to control levels by ethanol application. These results suggest that soybeans were adversely affected by salt stress and recovered with ethanol application via the regulation of cell wall and membrane functions through the detoxification of reactive oxygen species.
Identification of Single Nucleotide Polymorphisms Through Genome-Wide Association Studies of pH Traits in Goose Meat
Authors: Wang Haiwei , Chen Zhuping , Ma Lin , Wu Yifan , Zhao Xianzhi , Zhang Keshan , Xue Jiajia , Luo Yi , Wang Chao , Liu Zuohua , Xie Youhui , Chen Ying , Gao Guangliang , Wang Qigui
Published: October 2024

The genetic regulation of goose meat quality traits remains relatively unexplored, and the underlying mechanisms are yet to be elucidated. This study aims to employ single nucleotide polymorphism (SNP) genotyping in conjunction with genome-wide association studies (GWAS) to investigate critical candidate regions and genes associated with the pH trait of meat in Sichuan white geese. A cohort of 203 healthy male Sichuan white geese was randomly selected and slaughtered at 70 days of age. Measurements were taken of meat pH, growth parameters, body dimensions, and post-slaughter traits. High-throughput sequencing on the Illumina HiSeq X Ten platform facilitated gene resequencing and SNP evaluation, and GWAS was employed to detect key genes within quantitative trait loci (QTL) intervals. The sequencing of 203 individuals yielded a total of 2601.19 Gb of genomic data, with an average sequencing depth of 10.89×. Through GWAS analysis, a total of 30 SNPs associated with pH were identified. These SNPs were identified on multiple chromosomes, including on chromosome 17 (chr: 23.57–23.68 Mb) and chromosome 13 (chr13: 31.52–31.61 Mb). By annotating these associated SNPs, nine candidate genes (including C19L2, AMFR, POL, RERGL, ZN484, GMDS, WAC) associated with the pH of goose meat were identified. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) genotyping of 10 SNPs centered on these nine candidate genes was confirmed. GO enrichment analysis revealed that genes within 1 Mb of the associated SNPs are significantly enriched in pathways involved in lymphocyte activation, in response to hydrogen peroxide, Salmonella infection, and other metabolic processes. This study explores the gene regulatory pathways influencing pH traits in goose meat and provides molecular markers for enhancing meat quality. These findings are expected to facilitate the advancement of molecular breeding programs in geese.
Metabolic and Inflammatory Profiles in Children and Adolescents with Autism Spectrum Disorder: A Cross-Sectional Study
Authors: Gaspar Joana M. , Ferreira José Pedro , Carvalho Humberto M. , Toscano Chrystiane V. A.
Published: October 2024

Background/Objectives: Autism spectrum disorder (ASD) is associated with several coexisting diseases or comorbidities, including inflammatory and metabolic disorders. In fact, ASD symptoms may be associated with immune system dysfunction. However, studies investigating the peripheral blood levels of immune cells are lacking and have provided mixed findings. In this study, we evaluated the relationship between the intensity level of ASD symptoms and the inflammatory and metabolic profiles in 154 children and adolescents (2–17 years). Methods: Bayesian multilevel models were used to examine the relationship between their symptom intensities and inflammatory/metabolic profiles. Results: Heavier children had higher values for triglyceride and insulin levels. Children with a level 3 of ASD intensity had higher free fatty acids levels. However, when adjusting for ASD intensity, gender, medication use, or weight status, older children appeared to have higher values of triglycerides, insulin levels, and free fatty acids. Conclusions: We concluded that as Brazilian children with ASD became older, they had a higher risk for insulin resistance.
The Impact of Social Media and Infection Perception on the Intentions of Recreational Vehicle Tours: An Extended Model of Goal-Directed Behavior
Authors: Zeng Chao , Yang Zihan , Zhai Yufan , Yu Li
Published: October 2024

Despite the rapid expansion of China’s RV (recreational vehicle) tourism industry, research on RV tourist behavior remains limited. This study develops an extended model of goal-directed behavior (EMGB) that more comprehensively explains the formation of tourists’ intentions to engage in RV tourism. The EMGB incorporates critical factors, including the perception of infection (PI), social media influence (SM), infrastructure perception (IP), and perceived advantages of drive tourism (PAD), into the original goal-directed behavior model (MGB). Results from a survey involving 545 RV tourists reveal that the EMGB achieves a satisfactory fit with the data and explains a larger proportion of variance in behavioral intentions. Notably, all variables within the original MGB remain significant predictors of both desire and intention. Furthermore, this study identifies factors such as Time and Economy capability, age, and region as significant moderators of the decision-making process for RV tourists. These findings offer valuable insights to marketers and governmental bodies, empowering them to make more reasonable decisions and devise strategies that cater to the diverse needs and preferences of RV tourists in the future.
Optimizing Allocation to Telehealth and In-Person Prolonged Exposure for Women Veterans with Military Sexual Trauma: A Precision Medicine Approach
Authors: Argyriou Evangelia , Gros Daniel F. , Hernandez Tejada Melba A. , Muzzy Wendy A. , Acierno Ron
Published: October 2024

Military sexual trauma-related post-traumatic stress disorder (PTSD) is highly prevalent and costly among women veterans, making the need for effective and accessible treatment of critical importance. Access to care is a key mechanism of mental health disparities and might affect differential response to treatment. The goal of this study was to estimate an individualized treatment rule based on readily available individual characteristics related to access to care to optimize allocation to in-person vs. telehealth delivery of prolonged exposure for PTSD in military sexual trauma survivors. The following variables were used as prescriptive factors: age, race, disability status, socioeconomic status, rural vs. urban status, and baseline PTSD level. The rule was estimated using a machine-learning approach, Outcome Weighted Learning. The estimated optimal rule outperformed a one-size-fits-all rule where everyone is universally assigned to telehealth; it led to markedly lower mean PTSD levels following 6 months from treatment (Vdopt − VTelehealth = −14.55, 95% CI: −27.24, −1.86). However, the rule did not significantly discriminate for in-person therapy (Vdopt − VIn-person = −11.86, 95% CI: −25.83, 2.12). Upon further validation with larger and more diverse samples, such a rule may be applied in practice settings to aid clinical decision-making and personalization of treatment assignment.
Mechanistic Analysis of the Evolution of Trust Level Between Owner and PMC Contractor Based on Dynamic Bayesian Network
Authors: Li Hongyan , Bari Abdul , Yue Aobo
Published: October 2024

The Project Management Contracting (PMC) project espouses a non-confrontational cooperation model. This paper employs a dynamic Bayesian network approach, grounded in social exchange theory, to construct a dynamic model of the evolution of trust levels between owners and PMC contractors. The findings of the study suggest that the trust level between the owner and the PMC contractor is primarily influenced by the extent of calculative and relational trust. Furthermore, the reciprocal behaviours and contractual flexibility emerge as the key drivers of both calculative and relational trust. Furthermore, reciprocal behaviours exert a more pronounced influence on the advancement of relational trust, whereas contract flexibility exerts a more pronounced influence on the advancement of calculative trust. Additionally, the level of calculative trust is higher at the outset of project implementation, with the generation of calculative trust subsequently leading to the generation of relational trust in the middle and later stages. In the middle and later stages of the project, the importance of relational trust increases, reaching a point where it surpasses that of calculative trust. Furthermore, the decline of relational trust has a greater negative impact on the overall trust level than calculative trust. The results of the research can provide theoretical guidance for the construction body to solve the problem of a low level of trust in the process of PMC project implementation.
Study on Compression Bearing Capacity of Tapered Concrete-Filled Double-Skin Steel Tubular Members Based on Heuristic-Algorithm-Optimized Backpropagation Neural Network Model
Authors: Liu Xianghong , Dangi Sital Kumar , Yang Zixuan , Song Yinxuan , Sun Qing , Wang Jiantao
Published: October 2024

A tapered concrete-filled double-skin steel tubular (TCFDST) structure has been used as the main framework in transmission towers, offshore facility platforms, and turbine towers owing to its excellent mechanical properties. In order to solve the difficulties of calculating the axial compressive capacity of TCFDST members due to the variations in cross-section, this paper applied heuristic optimization algorithms such as Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Ant Colony Optimization (ACO) to enhance a Backpropagation Neural Network (BPNN) model. A predictive model incorporating both global and local optimization strategies for the axial compressive capacity of a TCFDST structure is proposed. A comprehensive axial database for TCFDST members, comprising 1327 sets of experimental and finite element analysis results, was established, with ten types of component dimensions and material parameters selected as input variables and compressive bearing capacity as the output variable. This study developed and assessed four BPNN models, each optimized by a different heuristic algorithm, against various machine learning algorithms and standards. The heuristic-algorithm-optimized BPNN models demonstrated superior accuracy in predicting the axial compressive capacity of TCFDST members. Through parametric analysis, this study identified the relationship between the model’s bearing capacity predictions and each input parameter, confirming the model’s broad applicability. The optimized BPNN model, refined with heuristic algorithms, provides a significant reference for addressing the computational challenges associated with the load-bearing capacity of TCFDST structures and facilitating their application.
Metal Peroxide Nanoparticles for Modulating the Tumor Microenvironment: Current Status and Recent Prospects
Authors: Rajaram Jagadeesh , Kuthati Yaswanth
Published: October 2024

Background: The significant expansion of nanobiotechnology and nanomedicine has led to the development of innovative and effective techniques to combat various pathogens, demonstrating promising results with fewer adverse effects. Metal peroxide nanoparticles stand out among the crucial yet often overlooked types of nanomaterials, including metals. These nanoparticles are key in producing oxygen (O2) and hydrogen peroxide (H2O2) through simple chemical reactions, which are vital in treating various diseases. These compounds play a crucial role in boosting the effectiveness of different treatment methods and also possess unique properties due to the addition of metal ions. Methods: This review discusses and analyzes some of the most common metal peroxide nanoparticles, including copper peroxide (CuO2), calcium peroxide (CaO2), magnesium peroxide (MgO2), zinc peroxide (ZnO2), barium peroxide (BaO2), and titanium peroxide (TiOx) nanosystems. These nanosystems, characterized by their greater potential and treatment efficiency, are primarily needed in nanomedicine to combat various harmful pathogens. Researchers have extensively studied the effects of these peroxides in various treatments, such as catalytic nanotherapeutics, photodynamic therapy, radiation therapy, and some combination therapies. The tumor microenvironment (TME) is particularly unique, making the impact of nanomedicine less effective or even null. The presence of high levels of reactive oxygen species (ROS), hypoxia, low pH, and high glutathione levels makes them competitive against nanomedicine. Controlling the TME is a promising approach to combating cancer. Results: Metal peroxides with low biodegradability, toxicity, and side effects could reduce their effectiveness in treating the TME. It is important to consider the distribution of metal peroxides to effectively target cancer cells while avoiding harm to nearby normal cells. As a result, modifying the surface of metal peroxides is a key strategy to enhance their delivery to the TME, thereby improving their therapeutic benefits. Conclusions: This review discussed the various aspects of the TME and the importance of modifying the surface of metal peroxides to enhance their therapeutic advantages against cancer, as well as address safety concerns. Additionally, this review covered the current challenges in translating basic research findings into clinical applications of therapies based on metal peroxide nanoparticles.
A Review of Non-Invasive Skin Imaging in Merkel Cell Carcinoma: Diagnostic Utility and Clinical Implications
Authors: Badiu Iulia Maria , Korecka Katarzyna , Orzan Anca Olguta , Spadafora Marco , Longo Caterina , Forsea Ana-Maria , Lallas Aimilios
Published: October 2024

Background/Objectives: Merkel cell carcinoma (MCC) is a rare and aggressive cutaneous neuroendocrine malignancy characterized by its propensity for rapid growth and early regional and distant metastasis. Given its potentially lethal nature, accurate and timely diagnosis of MCC is of utmost importance. This review aims to describe non-invasive imaging methods that can serve as additional tools in the examination of MCC. Methods: In this narrative review, we describe the up-to-date spectrum of non-invasive skin-imaging methods that can serve as additional tools in the examination of MCC based on the available literature. Dermoscopy might enhance the clinical diagnosis of MCC, facilitate differentiation from other benign and malignant tumors, and help optimize the treatment plan. New imaging technologies might also provide useful information at a sub-macroscopic level and support clinical diagnosis. These techniques include high-frequency ultrasound (HFUS), reflectance confocal microscopy (RCM) and optical coherence tomography (OCT). Results: Clinically, MCC typically presents as a rapidly growing, red, purple or skin-colored painless and firm nodule. Diagnosis is usually established with histopathological assessment and immunohistochemistry. However, dermoscopy and new imaging technologies might enhance the clinical diagnosis of MCC, facilitate differentiation from other benign and malignant tumors, and help optimize the treatment plan.
Cannabidiol (CBD) Protects Lung Endothelial Cells from Irradiation-Induced Oxidative Stress and Inflammation In Vitro and In Vivo
Authors: Bauer Lisa , Alkotub Bayan , Ballmann Markus , Hasanzadeh Kafshgari Morteza , Rammes Gerhard , Multhoff Gabriele
Published: October 2024

Objective: Radiotherapy, which is commonly used for the local control of thoracic cancers, also induces chronic inflammatory responses in the microvasculature of surrounding normal tissues such as the lung and heart that contribute to fatal radiation-induced lung diseases (RILDs) such as pneumonitis and fibrosis. In this study, we investigated the potential of cannabidiol (CBD) to attenuate the irradiation damage to the vasculature. Methods: We investigated the ability of CBD to protect a murine endothelial cell (EC) line (H5V) and primary lung ECs isolated from C57BL/6 mice from irradiation-induced damage in vitro and lung ECs (luECs) in vivo, by measuring the induction of oxidative stress, DNA damage, apoptosis (in vitro), and induction of inflammatory and pro-angiogenic markers (in vivo). Results: We demonstrated that a non-lethal dose of CBD reduces the irradiation-induced oxidative stress and early apoptosis of lung ECs by upregulating the expression of the cytoprotective mediator heme-oxygenase-1 (HO-1). The radiation-induced increased expression of inflammatory (ICAM-2, MCAM) and pro-angiogenic (VE-cadherin, Endoglin) markers was significantly reduced by a continuous daily treatment of C57BL/6 mice with CBD (i.p. 20 mg/kg body weight), 2 weeks before and 2 weeks after a partial irradiation of the lung (less than 20% of the lung volume) with 16 Gy. Conclusions: CBD has the potential to improve the clinical outcome of radiotherapy by reducing toxic side effects on the microvasculature of the lung.
p70S6K as a Potential Anti-COVID-19 Target: Insights from Wet Bench and In Silico Studies
Authors: Shechter Sharon , Pal Rajat Kumar , Trovato Fabio , Rozen Or , Gage Matthew J. , Avni Dorit
Published: October 2024

The onset of SARS-CoV-2 infection in 2019 sparked a global COVID-19 pandemic. This infection is marked by a significant rise in both viral and host kinase activity. Our primary objective was to identify a pivotal host kinase essential for COVID-19 infection and the associated phenomenon of the cytokine storm, which may lead to long-term COVID-19 complications irrespective of viral genetic variations. To achieve this, our study tracked kinase phosphorylation dynamics in RAW264.7 macrophages following SPIKE transfection over time. Among the kinases surveyed, p70S6K (RPS6KB1) exhibited a 3.5-fold increase in phosphorylation at S418. This significant change prompted the selection of p70S6K for in silico investigation, utilizing its structure bound to M2698 (PDB: 7N93). M2698, an oral dual Akt/p70S6K inhibitor with an IC50 of 1.1 nM, exhibited psychosis side effects in phase I clinical trials, potentially linked to its interaction with Akt2. Our secondary objective was to discover a small-molecule analogue of M2698 that exhibits a distinct binding preference for p70S6K over Akt2 through computational modeling and analysis. The in silico part of our project began with validating the prediction accuracy of the docking algorithm, followed by an OCA analysis pinpointing specific atoms on M2698 that could be modified to enhance selectivity. Subsequently, our investigation led to the identification of an analog of M2698, designated as S34, that showed a superior docking score towards p70S6K compared to Akt2. To further assess the stability of S34 in its protein–ligand (PL) complexes with p70S6K and Akt2, MD simulations were conducted. These simulations suggest that S34, on average, forms two hydrogen bond interactions with p70S6K, whereas it only forms one hydrogen bond interaction with Akt2. This difference in hydrogen bond interactions likely contributed to the observed larger root mean square deviation (RMSD) of 0.3 nm in the S34-Akt2 complex, compared to 0.1 nm in the S34-p70S6K complex. Additionally, we calculated free binding energy to predict the strength of the binding interactions of S34 to p70S6K and Akt2, which showed ~2-fold favorable binding affinity of S34 in the p70S6K binding pocket compared to that in the Akt2 binding pocket. These observations may suggest that the S34-p70S6K complex is more stable than the S34-Akt2 complex. Our work focused on identifying a host kinase target and predicting the binding affinity of a novel small molecule to accelerate the development of effective treatments. The wet bench results specifically highlight p70S6K as a compelling anti-COVID-19 target. Meanwhile, our in silico investigations address the known off-target effects associated with M2698 by identifying a close analog called S34. In conclusion, this study presents novel and intriguing findings that could potentially lead to clinical applications with further investigations.
Designing of WS2@NiCoS@ZnS Nanocomposite Electrode Material for High-Performance Energy Storage Applications
Authors: Imran Muhammad , Afzal Amir Muhammad , Alqarni Areej S. , Iqbal Muhammad Waqas , Mumtaz Sohail
Published: October 2024

Researchers are developing innovative electrode materials with high energy and power densities worldwide for effectual energy storage systems. Transition metal dichalcogenides (TMDs) are arranged in two dimensions (2D) and have shown great promise as materials for photoelectrochemical activity and supercapacitor batteries. This study reports on the fabrication of WS2@NiCoS and WS2@NiCoS@ZnS hybrid nano-architectures through a simple hydrothermal approach. Because of the strong interfacial contact between the two materials, the resultant hierarchical hybrids have tunable porosity nanopetal decorated morphologies, rich exposed active edge sites, and high intrinsic activity. The specific capacities of the hybrid supercapacitors built using WS2@NiCoS and WS2@NiCoS@ZnS electrodes are 784.38 C g−1 and 1211.58 C g−1 or 2019.3 F g−1, respectively, when performed at 2 A g−1 using a three-electrode setup. Furthermore, an asymmetric device (WS2@NiCoS@ZnS//AC) shows a high specific capacity of 190.5 C g−1, an energy density of 49.47 Wh kg−1, and a power density of 1212.30 W kg−1. Regarding the photoelectrochemical activity, the WS2@NiCoS@ZnS catalyst exhibits noteworthy characteristics. Our findings pave the way for further in-depth research into the use of composite materials doped with WS2 as systematic energy-generating devices of the future.
Depression, Anxiety, and Pain Predict Quality of Life in Patients with Differentiated Thyroid Cancer Postradiotherapy Ablation in Taiwan: A 48-Week Follow-Up Study
Authors: Hsieh Kuan-Ying , Cheng Kai-Da , Chu Che-Sheng , Yen Yung-Chieh , Changchien Te-Chang
Published: October 2024

Despite the generally good prognosis of differentiated thyroid cancer (DTC), impairments in health-related quality of life (HRQoL) remain a major concern in these patients. This study examined the patterns and predictors of change in mental and physical HRQoL in DTC survivors following radiotherapy ablation. Two hundred patients with DTC who received radiotherapy ablation in southern Taiwan between 2015 and 2018 were interviewed using the Taiwan version of the 36-item Short-form Health Survey (SF-36), the Taiwanese Depression Questionnaire (TDQ), and the Hamilton Rating Scale for Anxiety (HAM-A) at baseline and after 24 and 48 weeks of treatment. The demographic characteristics, thyroid-related factors, recombinant human thyroid-stimulating hormone (rhTSH), and serum calcium level were also collected. Improvements in both mental and physical HRQoL were noted over the first 24 weeks following radiotherapy ablation. Between 24 and 48 weeks, mental HRQoL was increasing, whereas physical HRQoL decreased. Higher levels of anxiety and pain predicted both poor physical and mental HRQoL. Further, higher levels of depression predicted poor mental HRQoL. Additionally, factors such as low income, rhTSH use, elevated TSH levels, low free T4, and higher physical HRQoL were associated with poorer mental HRQoL during the follow-up period. The early detection and intervention of depression, anxiety, and pain should be the objective for programs aiming to improve HRQoL.
The Accuracy of Intraoral Scanners in Maxillary Defects with Different Model Variations
Authors: Murat Sema , Batak Burcu , Aydoğ Özge , Öztürk Caner
Published: October 2024

Background: Advances in digital technology and intraoral scanners (IOSs) have the potential to enable accurate digital impressions for patients with maxillary defects. This study aimed to compare the accuracy of IOSs in completely and partially edentulous models with maxillary defects. Methods: Three polyurethane models—one completely edentulous (CE) and two partially edentulous, following Aramany classifications I (ACI) and II (ACII)—were created using stereolithography. These models were scanned with a desktop scanner to create reference models. Ten scans were performed using three different intraoral scanners (TRIOS 3, Primescan, and Virtuo Vivo). The IOS datasets were analyzed to assess trueness and precision using a two-way ANOVA and multiple-comparison tests with Bonferroni corrections (α = 0.05). Results: Both the model type and the IOS significantly influenced trueness and precision. The interaction between the model type and the IOS was found to be statistically significant (trueness: p = 0.001; precision: p = 0.005). The highest trueness was observed in the ACII model scanned with TRIOS 3 and Primescan. TRIOS 3 and Primescan also exhibited the highest precision in the ACII model. For Virtuo Vivo, there were no significant differences among the models (p = 0.48). Conclusions: Although intraoral scanners (IOSs) demonstrated significant differences in trueness when used in completely and partially edentulous models with maxillary defects, these differences may be considered clinically insignificant.
DQKNet: Deep Quasiconformal Kernel Network Learning for Image Classification
Authors: Zhai Jia , Zhang Zikai , Ye Fan , Wang Ziquan , Guo Dan
Published: October 2024

Compared to traditional technology, image classification technology possesses a superior capability for quantitative analysis of the target and background, and holds significant applications in the domains of ground target reconnaissance, marine environment monitoring, and emergency response to sudden natural disasters, among others. Currently, the enhancement of spatial spectral resolution heightens the difficulty and reduces the efficiency of classification, posing a substantial challenge to the aforementioned applications. Hence, the classification algorithm is required to take both computing power and classification accuracy into account. Research indicates that the deep kernel mapping network can accommodate both computing power and classification accuracy. By employing the kernel mapping function as the network node function of deep learning, it effectively enhances the classification accuracy under the condition of limited computing power. Therefore, to address the issue of network structure optimization of deep mapping networks and the insufficient application of line feature learning and expression in existing network structures, considering the adaptive optimization of network structures, deep quasiconformal kernel network learning (DQKNet) is proposed for image classification. Firstly, the structural parameters and learning parameters of the deep kernel mapping network are optimized. This approach can adaptively adjust the network structure based on the distribution characteristics of the data and enhance the performance of image classification. Secondly, the computational network node optimization method of quasiconformal kernel learning is applied to this network, further elevating the performance of the deep kernel learning mapping network in image classification. The experimental results demonstrate that the improvement in the deep kernel mapping network from the perspectives of accounting children, mapping network nodes, and network structure can effectively enhance the feature extraction and classification performance of the data. On the five public datasets, the average AA, OA, and KC values of our algorithm are 91.99, 91.25, and 85.99, respectively, outperforming the currently most-advanced algorithms.
SS-Trans (Single-Stream Transformer for Multimodal Sentiment Analysis and Emotion Recognition): The Emotion Whisperer—A Single-Stream Transformer for Multimodal Sentiment Analysis
Authors: Ji Mingyu , Wei Ning , Zhou Jiawei , Wang Xin
Published: October 2024

Multimodal sentiment analysis enables machines to interact with people more naturally. The integration of multimodalities can enhance the machines’ ability to accurately predict emotions. The main obstacle to multimodal sentiment analysis is integrating information from different modalities. Previous research has used a variety of techniques, including long short-term memory networks (LSTM) and transformers. However, traditional fusion methods cannot better utilize the information from each modality, and some intra- and inter-modal features may be overlooked due to possible differences in feature representations. Therefore, to address this problem, we use a combined transformer that can connect different modal inputs and introduce SS-Trans (Single-Stream Transformer for Multimodal Sentiment Analysis and Emotion Recognition), a single-stream transformer that fuses textual, visual, and speech modalities. The model was pre-trained on the CMU-MOSI and CMU-MOSEI datasets: multi-modal masked image language modeling (MLM) and text–image matching (TIA). Compared to other existing models, SS-Trans improves ACC-2 on these two datasets by 1.06% and 1.33%, and improves F1 values by 1.50% and 1.62%, respectively. The experimental results show that our method achieves the state-of-the-art level. In addition, ablation experiments validate the model and the pre-training task, proving the effectiveness of the proposed model.