bluuebunny/crossref_metadata_2025 huggingface dataset:
Applications of CRISPR Technology to Breast Cancer and Triple Negative Breast Cancer Research
Authors: Pont Mariona , Marqués Marta , Sorolla Maria Alba , Parisi Eva , Urdanibia Izaskun , Morales Serafín , Salud Antonieta , Sorolla Anabel
Published: September 2023

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology has transformed oncology research in many ways. Breast cancer is the most prevalent malignancy globally and triple negative breast cancer (TNBC) is one of the most aggressive subtypes with numerous challenges still to be faced. In this work, we have explained what CRISPR consists of and listed its applications in breast cancer while focusing on TNBC research. These are disease modelling, the search for novel genes involved in tumour progression, sensitivity to drugs and immunotherapy response, tumour fitness, diagnosis, and treatment. Additionally, we have listed the current delivery methods employed for the delivery of CRISPR systems in vivo. Lastly, we have highlighted the limitations that CRISPR technology is subject to and the future directions that we envisage. Overall, we have provided a round summary of the aspects concerning CRISPR in breast cancer/TNBC research.
Swallowing after Oral Oncological Treatment: A Five-Year Prospective Study
Authors: Speksnijder Caroline M. , Ortiz-Comino Lucía , de Haan Anton F. J. , Fernández-Lao Carolina , de Bree Remco , Merkx Matthias A. W.
Published: September 2023

Background: Swallowing rehabilitation in curative treated patients with oral cancer is still a challenge. Different factors may influence these patients’ swallowing function. The aim of this study was to identify factors associated with swallowing function up to 5 years after cancer treatment. Methods: Swallowing duration and frequency of 5 mL water and 15 mL applesauce were measured in 123 patients treated for oral cancer. Mixed model analyses were performed to identify associated factors. Results: Age influenced all measured swallowing outcomes. Assessment moment, gender, tumor location, maximum tongue force, and tactile sensory function of the tongue were associated with both water and applesauce swallowing duration, tumor classification was associated with water swallowing duration, and alcohol consumption was associated with applesauce swallowing duration. Assessment moment, cancer treatment, maximum tongue force, and tactile sensory function of the tongue were associated with water and applesauce swallowing frequency. Conclusion: Patients who are older at diagnosis, women, and patients who regularly consume alcohol before their treatment may have poorer swallow functioning after curative oral cancer treatment. Patients that fit these criteria should have their swallowing evaluated during clinical follow-ups and sent to swallowing therapy when needed. During this therapy, optimizing tongue function needs attention to maintain an optimal swallowing function.
Unravelling the Glioblastoma Tumour Microenvironment: Can Aptamer Targeted Delivery Become Successful in Treating Brain Cancers?
Authors: Giles Breanna , Nakhjavani Maryam , Wiesa Andrew , Knight Tareeque , Shigdar Sarah , Samarasinghe Rasika M.
Published: September 2023

The key challenges to treating glioblastoma multiforme (GBM) are the heterogeneous and complex nature of the GBM tumour microenvironment (TME) and difficulty of drug delivery across the blood–brain barrier (BBB). The TME is composed of various neuronal and immune cells, as well as non-cellular components, including metabolic products, cellular interactions, and chemical compositions, all of which play a critical role in GBM development and therapeutic resistance. In this review, we aim to unravel the complexity of the GBM TME, evaluate current therapeutics targeting this microenvironment, and lastly identify potential targets and therapeutic delivery vehicles for the treatment of GBM. Specifically, we explore the potential of aptamer-targeted delivery as a successful approach to treating brain cancers. Aptamers have emerged as promising therapeutic drug delivery vehicles with the potential to cross the BBB and deliver payloads to GBM and brain metastases. By targeting specific ligands within the TME, aptamers could potentially improve treatment outcomes and overcome the challenges associated with larger therapies such as antibodies.
Modern Approach to Melanoma Adjuvant Treatment with Anti-PD1 Immune Check Point Inhibitors or BRAF/MEK Targeted Therapy: Multicenter Real-World Report
Authors: Placzke Joanna , Rosińska Magdalena , Sobczuk Paweł , Ziętek Marcin , Kempa-Kamińska Natasza , Cybulska-Stopa Bożena , Kamińska-Winciorek Grażyna , Bal Wiesław , Mackiewicz Jacek , Galus Łukasz , Las-Jankowska Manuela , Jankowski Michał , Dziura Robert , Drucis Kamil , Borkowska Aneta , Świtaj Tomasz , Rogala Paweł , Kozak Katarzyna , Klimczak Anna , Jagodzińska-Mucha Paulina , Szumera-Ciećkiewicz Anna , Koseła-Paterczyk Hanna , Rutkowski Piotr
Published: September 2023

Background: The landscape of melanoma management changed as randomized trials have launched adjuvant treatment. Materials and Methods: An analysis of data on 248 consecutive melanoma stage III and IV patients given adjuvant therapy in eight centers (February 2019 to January 2021) was conducted. Results: The analyzed cohort comprised 147 melanoma patients given anti-PD1 (33% nivolumab, 26% pembrolizumab), and 101 (41%) were given dabrafenib plus trametinib (DT). The 2-year overall survival (OS), relapse-free survival (RFS), and distant-metastases-free survival (DMFS) rates were 86.7%, 61.4%, and 70.2%, respectively. The disease stage affected only the RFS rate; for stage IV, it was 52.2% (95% CI: 33.4–81.5%) vs. 62.5% (95% CI: 52.3–74.8%) for IIIA-D, p = 0.0033. The type of lymph node surgery before adjuvant therapy did not influence the outcomes. Completion of lymph node dissection cessation after positive SLNB did not affect the results in terms of RFS or OS. Treatment-related adverse events (TRAE) were associated with longer 24-month RFS, with a rate of 68.7% (55.5–84.9%) for TRAE vs. 56.6% (45.8–70%) without TRAE, p = 0.0031. For TRAE of grade ≥ 3, a significant decline in OS to 60.6% (26.9–100%; p = 0.004) was observed. Conclusions: Melanoma adjuvant therapy with anti-PD1 or DT outside clinical trials appears to be effective and comparable with the results of registration studies. Our data support a de-escalating surgery approach in melanoma treatment.
Non-Conventional Oilseeds: Unlocking the Global Potential for Sustainable Biofuel Production
Authors: Alhammad Bushra Ahmed , Jamal Aftab , Carlucci Claudia , Saeed Muhammad Farhan , Seleiman Mahmoud F. , Pompelli Marcelo F.
Published: September 2023

Renewable energy sources have become an urgent worldwide concern due to the impacts of global warming. Globally, biofuels can significantly reduce greenhouse gas emissions, which are major contributors to global warming. The use of biofuels has the potential to transform the energy landscape while mitigating the adverse effects of traditional fossil fuels. This study examines the water features, biochemical compositions, and fatty acid profiles among various plant species. The results reveal significant variations in water features as a consequence of the relative water content and water potential of each seed. Also, we note that some non-edible species like A. blanchetii, C. procera, E. oleracea, P. juliflora, M. oleifera, and J. curcas have good attributes that confer a biofuel-like species. These attributes are high in oil content and have a good profile content of long-chain polyunsaturated fatty acids (LC-PUFAs), ranging from 35% to 80% among the different oilseeds. Fatty acid profiling reveals distinct compositions among the plant species. Stearic acid (C18:0), oleic acid (C18:1), and linoleic acid (C18:2) were the principal oils in A. blanchetii, J. curcas, P. juliflora, M. oleifera, and S. tuberosa compared to other species. M. oleifera stands out with a high linoleic acid (C18:1) content, while C. maxima, J. curcas, and P. juliflora are even higher (C18:2). A principal component analysis (PCA) and Pearson correlations analysis also confirmed that alternative oilseeds exhibited similarities to standard oilseeds and have the potential to replace them for biofuel production. These findings demonstrate the potential of non-conventional oilseeds for sustainable biofuel production. By unlocking their global potential, we can advance towards mitigating environmental impacts and fostering a sustainable biofuel industry.
Efficient Photocatalytic Degradation of Aqueous Atrazine over Graphene-Promoted g-C3N4 Nanosheets
Authors: Altendji Khaoula , Hamoudi Safia
Published: September 2023

Atrazine is a systemic herbicide widely used in weed control. In recent years, it has been largely detected in surface and groundwater in several locations all over the world. Photocatalysis is a green and sustainable technology with huge application prospects in pollution control and the degradation of organic water pollutants. In this work, photodegradation of aqueous atrazine was investigated over pristine graphitic carbon nitride (g-C3N4) synthesized via urea pyrolysis and graphene/g-C3N4 composite synthesized via the in situ growth method involving direct deposition of g-C3N4 nanosheets on the graphene surface. The obtained photocatalysts were characterized using transmission and scanning electron microscopy, Fourier-transformed infrared spectroscopy, UV-visible spectroscopy, photoluminescence spectroscopy, X-ray diffraction, and surface area measurements. It was demonstrated that the composite material exhibited remarkable photocatalytic properties for the efficient degradation of aqueous atrazine under visible light at ambient temperature. After 5 h of reaction, atrazine conversion reached 100% in the presence of graphene/g-C3N4 composite, while the pristine g-C3N4 allowed 40% conversion under the same conditions, thus demonstrating the positive effect of graphene on the photocatalytic activity of g-C3N4. Moreover, graphene/g-C3N4 was shown to keep its activity even when it was recycled five times, thus proving its stability and its potential to be used at the industrial scale.
Novel Electrochemical Sensor Based on MnO2 Nanowire Modified Carbon Paper Electrode for Sensitive Determination of Tetrabromobisphenol A
Authors: Zhu Chunmao , Wu Qi , Yuan Fanshu , Liu Jie , Wang Dongtian , Zhang Qianli
Published: September 2023

In this paper, a MnO2 nanowire (MnO2-NW) modified carbon paper electrode (CP) was developed as a novel electrochemical sensor for the sensitive determination of tetrabromobisphenol A (TBBPA). The MnO2 nanowire was prepared by a hydrothermal synthesis method, and the morphology and structure of MnO2 were characterized using scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The electrochemical performance of TBBPA on MnO2-NW/CP was investigated by cyclic voltammetry, and the result confirmed that MnO2-NW/CP exhibited excellent sensitivity for the determination of TBBPA due to the high specific surface area and good electrical conductivity of the nanowire-like MnO2. Moreover, the important electrochemical factors such as pH value, incubation time and modified material proportion were systematically studied to improve the determination sensitivity. The interferences from similar structure compounds on TBBPA have also been investigated. Under the optimal conditions, MnO2-NW/CP displayed a linear range of 70~500 nM for TBBPA with a detection limit of 3.1 nM. This was superior to some electrochemical methods in reference. The work presents a novel and simple method for the determination of TBBPA.
High-Intensity Interval Training in Female Adolescents with Moderate or Severe Obesity
Authors: Racil Ghazi , Russo Luca , Migliaccio Gian Mario , Signorelli Paola , Larion Alin , Padulo Johnny , Jlid Mohamed Chedly
Published: September 2023

This study aimed to investigate the impact of moderate- or high-intensity interval training (MIIT or HIIT) on anthropometric and biological measurements in four groups of females with obesity. Fifty-seven participants were divided into a moderate obesity group (MOG, n = 29) and a severe obesity group (SOG, n = 28). Two sub-groups were established to practice HIIT and MIIT programs (SOGHI, n = 14; SOGMI, n = 14; MOGHI, n = 14; MOGMI, n = 15). During the training sessions, each group performed two sets of 4 × 1 min intervals on a cycle ergometer. The intervals were conducted at 65% and 85% of the heart rate reserve (HRR) for MIIT and HIIT, respectively. Between each repetition, there was an active recovery phase at 50% HRR, and, between sets, there was a 4 min period of free pedaling. All groups significantly improved their anthropometric data, while only MOGHI and SOGHI significantly improved their lean body mass (LBM) and blood lactate (BL), with p ˂ 0.05; the higher percentage of change in blood insulin levels (−25.49 and −25.34) and the homeostasis model assessment of the insulin resistance index (−31.42 and −28.88) were noted. Only MOGHI showed improvements in growth hormone (GH) and blood glucose (p < 0.05), which were negatively correlated with body fat percentage (r = −0.76 and r = −0.72) and waist circumference (r = −0.77 and r = −0.82), respectively. We may conclude that HIIT was an effective method of managing anthropometric and biological parameters, as confirmed by the pronounced body fat reduction in the moderate obesity group.
Effect of Y2O3 Content on Microstructure and Corrosion Properties of Laser Cladding Ni-Based/WC Composite Coated on 316L Substrate
Authors: Liang Feilong , Li Kaiyue , Shi Wenqing , Zhu Zhikai
Published: September 2023

To improve the corrosion resistance of 316L substrate and lengthen its useful life in marine environments, Ni-based/WC/Y2O3 cladding layers with different Y2O3 contents were fabricated on 316L stainless steel using laser cladding technology. The influence of Y2O3 additives on the microstructure and properties of the cladding coatings was investigated by using scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction, a microhardness tester, an electrochemical workstation and a tribometer. Results show that the metallurgical bonding is well formed between the coating and the 316L substrate. The coating consisted primarily of γ-Ni phase and carbides. Adding an appropriate amount of Y2O3 can effectively refine the microstructure and inhibit the precipitation of the carbide hard phase; in addition, the added rare earth element can promote the solid-solution-strengthening effect of the cladding coatings, thus improving the microhardness and wear resistance of the cladding coatings and their electrochemical corrosion property in 3.5 wt% NaCl solution. The hardness of the Ni-based/WC coatings was substantially higher than that of the substrate, and it was greatest at a Y2O3 content of 1%. The corrosion and wear resistance of Y2O3-modified Ni-based/WC composite coatings are significantly better than those of the composite coating without Y2O3.
Influence of Elution Characteristics of Steelmaking Slags on Major Bacterial Communities in Biofilms
Authors: Ogawa Akiko , Mizutani Yukino , Tanaka Reiji , Ochiai Tatsuki , Ohashi Ruu , Hirai Nobumitsu , Suzuki Masanori
Published: September 2023

Steelmaking slags are prospective base materials for seaweed beds, resulting from a continuous process of biofouling, starting from biofilm formation and leading to growing algae. While focusing on biofilm formation, we investigated specific features of steelmaking slags when utilized as a base for seaweed beds by comparing the bacterial communities in marine biofilms between steelmaking slags and artificially produced ones. Genomic DNA was extracted from the biofilms collected on days 3 and 7, and partial 16S rRNA libraries were generated and sequenced by second-generation next-generation sequencing. The read sequences were analyzed using QIIME 2™, then heatmaps and non-metric multidimensional scaling based on the Bray–Curtis dissimilarity index in the R program. Rhodobacteraceae and Flavobacteriaceae were the most dominant family members in all samples on both days 3 and 7. However, Mariprofundus, comprising iron-oxidative bacteria, was predominantly detected in the samples of steelmaking slags on day 7. This suggested that the growth of Mariprofundus was dependent on Fe(II) ion concentration and that steelmaking slags eluted Fe(II) ions more easily than artificial slags. In contrast, Sulfurovaceae, sulfur-oxidizing bacteria, were dominantly present in all samples on day 3, but decreased by day 7, regardless of the sulfur content. It was supposed that engine oil-derived sulfur compounds strongly influenced Sulfurovaceae growth, whereas slag-derived sulfur compounds did not. Heatmap analysis indicated that the submersion period significantly influenced the bacterial communities, regardless of the differences in the main slag content ratios. Summarizing these results, the elution characteristics of steelmaking slags have the potential to influence the formation of marine biofilms, and this formation is significantly influenced by environmental conditions.
Preparation of ZnO Piezoelectric Thin-Film Material for Ultrasonic Transducers Applied in Bolt Stress Measurement
Authors: Zhang Yuxia , Jiang Yanghui , Ma Chi , Zhang Jun , Yang Bing
Published: September 2023

The measurement of bolt preload by using ultrasound can be accurate, convenient, and can realize the real-time monitoring of the change in the residual axial stress of a bolt during use. In order to realize the ultrasonic measurement of bolt preload, the use of zinc oxide (ZnO) piezoelectric thin-film material as an ultrasonic transducer material to stimulate an ultrasonic signal on the bolt is a feasible solution. In this paper, we choose to use RF magnetron sputtering technology to prepare ZnO piezoelectric thin-film materials and study the effects of sputtering power and target substrate distance on the structure and ultrasonic properties of ZnO piezoelectric thin films during the preparation process, in order to lay the foundation for realizing the application of ZnO piezoelectric thin films in the field of bolt preload measurement. The experimental results show that too-large sputtering power or too-small target substrate distance will result in the particles having too much kinetic energy during sputtering and exhibiting a structure of multiorientation growth, which excites ultrasonic longitudinal–transverse waves. A sputtering power of 600 W, sputtering time of 4 h, and target substrate distance of 100 mm are ideal experimental parameters for a ZnO piezoelectric thin-film material to be excited by an ultrasonic longitudinal wave signal, and its ideal operating frequency is 41 MHZ. These research results of bolt stress detection demonstrate good application prospects.
Automated Optimization-Based Deep Learning Models for Image Classification Tasks
Authors: Migayo Daudi Mashauri , Kaijage Shubi , Swetala Stephen , Nyambo Devotha G.
Published: September 2023

Applying deep learning models requires design and optimization when solving multifaceted artificial intelligence tasks. Optimization relies on human expertise and is achieved only with great exertion. The current literature concentrates on automating design; optimization needs more attention. Similarly, most existing optimization libraries focus on other machine learning tasks rather than image classification. For this reason, an automated optimization scheme of deep learning models for image classification tasks is proposed in this paper. A sequential-model-based optimization algorithm was used to implement the proposed method. Four deep learning models, a transformer-based model, and standard datasets for image classification challenges were employed in the experiments. Through empirical evaluations, this paper demonstrates that the proposed scheme improves the performance of deep learning models. Specifically, for a Virtual Geometry Group (VGG-16), accuracy was heightened from 0.937 to 0.983, signifying a 73% relative error rate drop within an hour of automated optimization. Similarly, training-related parameter values are proposed to improve the performance of deep learning models. The scheme can be extended to automate the optimization of transformer-based models. The insights from this study may assist efforts to provide full access to the building and optimization of DL models, even for amateurs.
The Current Trend of Radiation Therapy for Patients with Localized Prostate Cancer
Authors: Numakura Kazuyuki , Kobayashi Mizuki , Muto Yumina , Sato Hiromi , Sekine Yuya , Sobu Ryuta , Aoyama Yu , Takahashi Yoshiko , Okada Syuhei , Sasagawa Hajime , Narita Shintaro , Kumagai Satoshi , Wada Yuki , Mori Naoko , Habuchi Tomonori
Published: September 2023

A recent approach to radiotherapy for prostate cancer is the administration of high doses of radiation to the prostate while minimizing the risk of side effects. Thus, image-guided radiotherapy utilizes advanced imaging techniques and is a feasible strategy for increasing the radiation dose. New radioactive particles are another approach to achieving high doses and safe procedures. Prostate brachytherapy is currently considered as a combination therapy. Spacers are useful to protect adjacent organs, specifically the rectum, from excessive radiation exposure.
Perspectives on Virtual Care for Childhood Cancer Survivors in Non-Metropolitan Areas during the COVID-19 Pandemic
Authors: Phelan Rachel , Aremu Taiwo Opeyemi , Karst Jeffrey , Anderson Lynnette , Jordan Anna , Morin Jocelyn , Nichols Julie , Singh Ashima , Schmidt Debra , Hoag Jennifer A. , Napurski Char , Zweber Haley , Sadak Karim Thomas
Published: September 2023

The COVID-19 pandemic paved the way for the widespread use of virtual care for childhood cancer survivors (CCSs). CCSs were virtual recipients of diverse care, including long-term follow-up (LTFU), primary care, mental health care, and several others. Virtual care comes with well-documented benefits and challenges. These are further magnified for CCSs living in rural or non-metropolitan areas. Here, we describe the virtual care of CCSs from two Upper Midwest cities with well-established childhood cancer survivor programs within large comprehensive cancer centers in the United States. CCSs from non-metropolitan areas, especially CCSs with two or more late effects, used virtual care more often during the COVID-19 pandemic compared to CCSs from metropolitan areas. A review of the related literature is also included and the identified challenges in providing virtual care, such as privacy concerns, technology-connectivity constraints, and medical license restrictions. Despite these limitations, the care of CCSs has evolved to leverage virtual care and its ability to increase access for patients and promote continuity of care for CCSs living in rural areas.
The Influence of Macroclimatic Drivers on the Macrophyte Phylogenetic Diversity in South African Estuaries
Authors: Veldkornet Dimitri Allastair
Published: September 2023

The geographical distribution of plants is influenced by macroclimate and dispersal limitations, which have led to lineage isolation and subsequent diversification within and across various environmental gradients. Macroclimatic variables in coastal wetlands influence plant species and lineages across biogeographical boundaries. This study aimed to determine the influence of macroclimatic variables on species and phylogenetic richness in South African estuaries. Open-source chloroplast DNA barcoding sequences, species distribution and climatic data layers were used to determine the relationship between species richness, MPD, MNTD and each bioclimatic variable individually. Temperate species richness and phylogenetic diversity were positively correlated with temperature bioclimatic variables whereas subtropical and tropical species were associated with increases in precipitation. Phylogenetic niche conservatism is evident in malvids and rosids which are restricted to tropical and subtropical regions due to their physiological adaptations to tropical climates. Caryophylales was mostly associated with temperate regions. Poales and Alismatales showed wide distributions that is likely attributed to traits related to wind pollination and hydrochory, rapid, clonal, and high reproductive output, tolerance to stressful conditions, and intraspecific genetic diversity. The findings highlight the importance of considering macroclimate and phylogenetic factors in understanding the distribution and diversity of coastal wetland plants.
Meiofauna: Biodiversity, Ecology, and Role in Ecosystems
Authors: Chertoprud Elena , Novichkova Anna
Published: September 2023

The meiofauna is currently considered to be a group of microscopic metazoans ranging in size from 30 to 1000–2000 μm, forming a distinct size class [...]
A New Genus and Two New Species of Short-Palped Crane Flies (Diptera: Limoniidae) from Central Asia
Authors: Podenas Sigitas , Gelhaus Jon , Podeniene Virginija , Devyatkov Vladimir , Yadamsuren Oyunchuluun , Torres Jimenez Maria Fernanda
Published: September 2023

A new genus of Limoniidae crane flies, Tauroconopa gen. nov., is described from specimens of two new species from north-central and western Mongolia, Kazakhstan, and Russia. Descriptions and illustrations of the distinguishing morphological features, including wing venation, male and female genitalia, and larval and pupal stages are provided. A discussion is presented of the possible classification of Tauroconopa gen. nov., and three species of western North American Symplecta (Psiloconopa) are transferred to Tauroconopa gen. nov. based primarily on their aedeagal structure. Certain deficiencies are outlined in the current identification keys for Holarctic Chioneinae crane flies, and this new genus does not key satisfactorily in the present generic keys. The use of molecular sequences (DNA “barcoding”) allowed for initial identification of the larval stages of Tauroconopa gen. nov. from unreared but associated specimens. A phylogenetic analysis of Tauroconopa gen. nov. is presented based on DNA barcoding evidence and confirms the isolated position of this new genus from other Chioneinae. Habitat information for each species is presented.
Empowering Foot Health: Harnessing the Adaptive Weighted Sub-Gradient Convolutional Neural Network for Diabetic Foot Ulcer Classification
Authors: Alqahtani Abdullah , Alsubai Shtwai , Rahamathulla Mohamudha Parveen , Gumaei Abdu , Sha Mohemmed , Zhang Yu-Dong , Khan Muhammad Attique
Published: September 2023

In recent times, DFU (diabetic foot ulcer) has become a universal health problem that affects many diabetes patients severely. DFU requires immediate proper treatment to avert amputation. Clinical examination of DFU is a tedious process and complex in nature. Concurrently, DL (deep learning) methodologies can show prominent outcomes in the classification of DFU because of their efficient learning capacity. Though traditional systems have tried using DL-based models to procure better performance, there is room for enhancement in accuracy. Therefore, the present study uses the AWSg-CNN (Adaptive Weighted Sub-gradient Convolutional Neural Network) method to classify DFU. A DFUC dataset is considered, and several processes are involved in the present study. Initially, the proposed method starts with pre-processing, excluding inconsistent and missing data, to enhance dataset quality and accuracy. Further, for classification, the proposed method utilizes the process of RIW (random initialization of weights) and log softmax with the ASGO (Adaptive Sub-gradient Optimizer) for effective performance. In this process, RIW efficiently learns the shift of feature space between the convolutional layers. To evade the underflow of gradients, the log softmax function is used. When logging softmax with the ASGO is used for the activation function, the gradient steps are controlled. An adaptive modification of the proximal function simplifies the learning rate significantly, and optimal proximal functions are produced. Due to such merits, the proposed method can perform better classification. The predicted results are displayed on the webpage through the HTML, CSS, and Flask frameworks. The effectiveness of the proposed system is evaluated with accuracy, recall, F1-score, and precision to confirm its effectual performance.
The Reliability of Ultrasonographic Assessment of Depth of Invasion: A Systematic Review with Meta-Analysis
Authors: Nisi Marco , Gennai Stefano , Graziani Filippo , Izzetti Rossana
Published: September 2023

Depth of invasion (DOI) has been recognized to be a strong prognosticator for oral squamous cell carcinoma (OSCC). Several diagnostic techniques can be employed for DOI assessment, however intraoral ultrasonography has been increasingly applied for the intraoral evaluation of OSCCs. The aim of the present study is to review the evidence on the application of intraoral ultrasonography to the assessment of DOI in patients affected by OSCC. A systematic electronic and manual literature search was performed, and data from eligible studies were reviewed, selected, and extracted. The studies had to report the correlation between DOI estimated with ultrasonography versus histopathology. A meta-analysis was conducted on the quantitative data available. Sixteen articles were included in the review following the screening of the initial 228 studies retrieved from the literature. The meta-analysis showed a significant correlation between ultrasonographic and histopathologic measurements (p < 0.01). The studies were all at low/moderate risk of bias. Ultrasonography appears a valuable tool for DOI assessment.
Crohn’s Disease Prediction Using Sequence Based Machine Learning Analysis of Human Microbiome
Authors: Unal Metehan , Bostanci Erkan , Ozkul Ceren , Acici Koray , Asuroglu Tunc , Guzel Mehmet Serdar
Published: September 2023

Human microbiota refers to the trillions of microorganisms that inhabit our bodies and have been discovered to have a substantial impact on human health and disease. By sampling the microbiota, it is possible to generate massive quantities of data for analysis using Machine Learning algorithms. In this study, we employed several modern Machine Learning techniques to predict Inflammatory Bowel Disease using raw sequence data. The dataset was obtained from NCBI preprocessed graph representations and converted into a structured form. Seven well-known Machine Learning frameworks, including Random Forest, Support Vector Machines, Extreme Gradient Boosting, Light Gradient Boosting Machine, Gaussian Naïve Bayes, Logistic Regression, and k-Nearest Neighbor, were used. Grid Search was employed for hyperparameter optimization. The performance of the Machine Learning models was evaluated using various metrics such as accuracy, precision, fscore, kappa, and area under the receiver operating characteristic curve. Additionally, Mc Nemar’s test was conducted to assess the statistical significance of the experiment. The data was constructed using k-mer lengths of 3, 4 and 5. The Light Gradient Boosting Machine model overperformed over other models with 67.24%, 74.63% and 76.47% accuracy for k-mer lengths of 3, 4 and 5, respectively. The LightGBM model also demonstrated the best performance in each metric. The study showed promising results predicting disease from raw sequence data. Finally, Mc Nemar’s test results found statistically significant differences between different Machine Learning approaches.
Synchronous High-Grade Squamous Intraepithelial Lesion of the Fimbria of the Fallopian Tube in a 51-Year-Old Woman with Invasive Squamous Cell Carcinoma of the Uterine Cervix
Authors: Wegscheider Anne-Sophie , Tauber Nikolas , Graubner Kirsten , Ziegeler Gudrun , Behr Michael , Lindner Christoph , Niendorf Axel
Published: September 2023

Primary squamous cell carcinoma or squamous intraepithelial lesion of the fallopian tube is a very rare finding with only a small number of cases worldwide. We describe the case of a 51-year-old woman, undergoing an abdominal hysterectomy after the diagnosis of an HPV-associated invasive squamous cell carcinoma of the uterine cervix with the unexpected detection of an HPV16-positive high-grade squamous intraepithelial lesion of the fimbria of the right fallopian tube in the resection specimen. The finding of an isolated, HPV-associated squamous intraepithelial lesion in the fallopian tube raises the question of a de novo development in this body compartment (after exclusion of a continuous metastatic spread from the uterine cervix) by taking a virus-associated field effect into account and should encourage the inclusion of this possibility when examining the fallopian tube in a routine setting.
The Role of Temporomandibular Joint Arthroscopy for Diagnosis and Surgical Management of Synovial Chondromatosis
Authors: Sembronio Salvatore , Raccampo Luca , Tel Alessandro , Di Cosola Michele , Troise Stefania , Dell’Aversana Orabona Giovanni , Robiony Massimo
Published: September 2023

Objective: We report the experience of our maxillo-facial surgery unit into the diagnostic and the therapeutic role of arthroscopy of temporomandibular joint (TMJ) synovial chondromatosis (SC). Materials and Methods: A series of sixteen patients with an imaging, arthroscopical, and histological diagnosis of SC treated with arthroscopy was selected. The surgeries were conducted in the Department of Maxillo-facial surgery, Academic hospital of Udine, from January 2016 to December 2022. Medical history, clinical examination, imaging, arthroscopical, and histological characteristics were recorded and then reviewed and discussed. Results: Clinical improvement, both in pain and in maximum incisal opening (MIO), were noticed in whole patients. Histologically, according to Milgram’s classification, the sample was fairly homogeneous. Arthroscopic treatment was successful in 87.5% of the patients. Only two cases of SC relapse were registered and were then submitted to open surgery to perform a total sinovectomy. The data collected were used to develop an SC classification proposal based on clinical, radiological (magnetic resonance imaging), arthroscopical, and histopathological characteristics. Conclusions: TMJ arthroscopy must be considered the first line of treatment for SC, leaving open surgery to relapses cases and those cases with extraarticular extension. A univocal classification is essential to best stage and prognostically characterise this pathology.
Endoscopic Ultrasound-Guided Fine Needle Biopsy in the Diagnostic Work-Up of Deep-Seated Lymphadenopathies and Spleen Lesions: A Monocentric Experience
Authors: Bellisario Flaminia , Attili Fabia , Campana Fabrizia , Borrelli de Andreis Federica , Bellesi Silvia , Maiolo Elena , Alma Eleonora , Malafronte Rosalia , Macis Giuseppe , Larocca Luigi Maria , Annunziata Salvatore , D’Alò Francesco , Hohaus Stefan
Published: September 2023

EUS-FNB has been introduced in clinical practice as a less invasive diagnostic approach with respect to surgery. We performed a single-center retrospective study on the diagnostic efficacy of EUS-guided FNB, including 171 patients with lymph nodes, splenic, and extranodal lesions that underwent EUS for FNB at our institution. Excluding 12 patients who did not undergo FNB and 25 patients with a previous diagnosis of a solid tumor, we included 134 patients with clinical/radiological suspect of a lymphoproliferative disease, including 20 patients with a previous history of lymphoma. Out of the 134 biopsies, material of diagnostic quality was obtained in 111 procedures (84.3%). Histological examination of the EUS-FNB samples produced an actionable diagnosis in 100 cases (74.6%). Among the patients without an actionable diagnosis, a second, different diagnostic procedure produced a further eight diagnoses of lymphoma. Therefore, the sensitivity of EUS-FNB for diagnosing lymphomas was calculated to be 86.4% (51/59). Assignment of lymphomas to WHO classification subtypes was possible in 47/51 (92%) of the cases. In conclusion, EUS-FNB is an effective procedure for the histological characterization of lesions that are suspected to be lymphoproliferative disease, allowing for an actionable diagnosis in 75% of cases.
Dynamic Power Reduction in TCAM Using Advanced Selective Pre-Charging of Match Lines
Authors: Doo Su-Yeon , Kwon Kee-Won
Published: September 2023

In this paper, we propose a power-efficient memory operation, selective match line precharge, based on an analysis of power consumption in ternary content-addressable memory (TCAM). A statistical study reveals that, on average, 58% of power dissipation related to the match line operation is saved by deactivating the unnecessary swing of match lines. The improvement has been simulated and proved using 180 nm CMOS technology.
Seismic Image Identification and Detection Based on Tchebichef Moment Invariant
Authors: Lu Andong , Honarvar Shakibaei Asli Barmak
Published: September 2023

The research focuses on the analysis of seismic data, specifically targeting the detection, edge segmentation, and classification of seismic images. These processes are fundamental in image processing and are crucial in understanding the stratigraphic structure and identifying oil and natural gas resources. However, there is a lack of sufficient resources in the field of seismic image detection, and interpreting 2D seismic image slices based on 3D seismic data sets can be challenging. In this research, image segmentation involves image preprocessing and the use of a U-net network. Preprocessing techniques, such as Gaussian filter and anisotropic diffusion, are employed to reduce blur and noise in seismic images. The U-net network, based on the Canny descriptor is used for segmentation. For image classification, the ResNet-50 and Inception-v3 models are applied to classify different types of seismic images. In image detection, Tchebichef invariants are computed using the Tchebichef polynomials’ recurrence relation. These invariants are then used in an optimized multi-class SVM network for detecting and classifying various types of seismic images. The promising results of the SVM model based on Tchebichef invariants suggest its potential to replace Hu moment invariants (HMIs) and Zernike moment invariants (ZMIs) for seismic image detection. This approach offers a more efficient and dependable solution for seismic image analysis in the future.
Enhancing Image Clarity: A Non-Local Self-Similarity Prior Approach for a Robust Dehazing Algorithm
Authors: Li Wujing , Liu Yuze , Ou Xianfeng , Wu Jianhui , Guo Longyuan
Published: September 2023

When light propagates in foggy weather, it is affected and scattered by suspended particles in the air. As a result, images taken in this environment often suffer from blurring, reduced contrast, loss of details, and other issues. The primary challenge in dehazing images is to estimate the transmission coefficient map in the atmospheric degradation model. In this paper, we propose a dehazing algorithm based on the optimization of the “haze-line” prior and non-local self-similarity prior. First, we divided the input haze image into small blocks and used the nearest neighbor classification algorithm to cluster the small patches, which were referred to as “patch-lines”. Based on the characteristics of these “patch-lines”, we could estimate the transmission coefficient map for the image. We then applied the transmission map to a weighted least squares filter to smooth it. Finally, we calculated the clear image using the haze degradation model. The experimental results demonstrate that our algorithm enhanced the image contrast and preserved the fine details, both qualitatively and quantitatively.
A Multi-Stage Adaptive Copy-Paste Data Augmentation Algorithm Based on Model Training Preferences
Authors: Yu Xiaoyu , Li Fuchao , Liu Yan , Wang Aili
Published: September 2023

Datasets play an important role in the field of object detection. However, the production of the dataset is influenced by objective environment and human subjectivity, resulting in class imbalanced or even long-tailed distribution in the datasets. At present, the optimization methods based on data augmentation still rely on subjective parameter adjustments, which is tedious. In this paper, we propose a multi-stage adaptive Copy-Paste augmentation (MSACP) algorithm. This algorithm divides model training into multiple training stages, each stage forming unique training preferences for that stage. Based on these training preferences, the class information of the training set is adaptively adjusted, which not only alleviates the problem of class imbalance in training, but also expands different sample sizes for categories with insufficient information at different training stages. Experimental verification of the traffic sign dataset Tsinghua–Tencent 100K (TT100K) was carried out and showed that the proposed method not only can improve the class imbalance in the dataset, but can also improve the detection performance of models. By using MSACP to transplant the trained optimal weights to an embedded platform, and combining YOLOv3-tiny, the model’s accuracy in detecting traffic signs in autonomous driving scenarios was improved, verifying the effectiveness of the MSACP algorithm in practical applications.
Black-Box Watermarking and Blockchain for IP Protection of Voiceprint Recognition Model
Authors: Zhang Jing , Dai Long , Xu Liaoran , Ma Jixin , Zhou Xiaoyi
Published: September 2023

Deep neural networks are widely used for voiceprint recognition, whilst voiceprint recognition models are vulnerable to attacks. Existing protection schemes for voiceprint recognition models are insufficient to withstand various robustness attacks and cannot prevent model theft. This paper proposes a black-box voiceprint recognition model protection framework that combines active and passive protection. It embeds key information into the Mel spectrogram to generate trigger samples that are difficult to detect and remove and injects them into the host model as watermark W, thereby enhancing the copyright protection performance of the voiceprint recognition model. To restrict the use of the model by unauthorized users, the index number corresponding to the model and the encrypted model information are stored on the blockchain, and then, an exclusive smart contract is designed to restrict access to the model. Experimental results show that this framework effectively protects voiceprint recognition model copyrights and restricts unauthorized access.
Brief Comparison of High-Side Gate Drivers for Series Capacitor Buck Converters
Authors: Abramovitz Alexander , Tali Ran , Tayar Tal , Shmilovitz Doron
Published: September 2023

This short article is concerned with the floating high-side gate driver suitable for driving the high side MOSFET/IGBT switch in the series capacitor buck converter family or converters with similar topological features. Biasing the high-side driver in series capacitor buck converters presents an engineering challenge. To alleviate the problem, a modified high-side driver with a voltage lift circuit for driving a high-side switch is proposed. The suggested solution, while being simple and low cost, has several benefits over the earlier propositions. The primary advantage of the proposed circuit is that it relies on a regulated supply to recharge its boot capacitor so to properly bias the high-side driver. Moreover, the proposed driver can operate in a wide range of input voltages while self-adjusting the correct voltage lift according to the operating point of a particular phase of the series buck converter. Thus, any number of phases can be implemented, avoiding cross-coupling effects and providing the high-switch with gating pulses of same amplitude.
Human Action Recognition Based on Skeleton Information and Multi-Feature Fusion
Authors: Wang Li , Su Bo , Liu Qunpo , Gao Ruxin , Zhang Jianjun , Wang Guodong
Published: September 2023

Action assessment and feedback can effectively assist fitness practitioners in improving exercise benefits. In this paper, we address key challenges in human action recognition and assessment by proposing innovative methods that enhance performance while reducing computational complexity. Firstly, we present Oct-MobileNet, a lightweight backbone network, to overcome the limitations of the traditional OpenPose algorithm’s VGG19 network, which exhibits a large parameter size and high device requirements. Oct-MobileNet employs octave convolution and attention mechanisms to improve the extraction of high-frequency features from the human body contour, resulting in enhanced accuracy with reduced model computational burden. Furthermore, we introduce a novel approach for action recognition that combines skeleton-based information and multiple feature fusion. By extracting spatial geometric and temporal characteristics from actions, we employ a sliding window algorithm to integrate these features. Experimental results show the effectiveness of our approach, demonstrating its ability to accurately recognize and classify various human actions. Additionally, we address the evaluation of traditional fitness exercises, specifically focusing on the BaDunJin movements. We propose a multimodal information-based assessment method that combines pose detection and keypoint analysis. Label sequences are obtained through a pose detector and each frame’s keypoint coordinates are represented as pose vectors. Leveraging multimodal information, including label sequences and pose vectors, we explore action similarity and perform quantitative evaluations to help exercisers assess the quality of their exercise performance.
Analysis of Backchannel Inviting Cues in Dyadic Speech Communication
Authors: Ondáš Stanislav , Kiktová Eva , Pleva Matúš , Juhár Jozef
Published: September 2023

The paper aims to study speaker and listener behavior in dyadic speech communication. A multimodal (speech and video) corpus of dyadic face-to-face conversations on various topics was created. The corpus was manually labeled on several layers (text transcription, backchannel modality and function, POS tags, prosody, and gaze). The statistical analysis was done on the proposed corpus. We focused on backchannel inviting cues on the speaker side and backchannels on the listener side and their patterns. We aimed to study interlocutor backchannel behavior and backchannel-related signals. The results of the analysis show similar patterns in the case of backchannel inviting cues between Slovak and English data and highlight the importance of gaze direction in a face-to-face speech communication scenario. The described corpus and results of the analysis are one of the first steps leading towards natural artificial intelligence-driven human–computer speech conversation.
Biogas Steam Reforming in Wastewater Treatment Plants: Opportunities and Challenges
Authors: González Juan Félix , Álvez-Medina Carmen María , Nogales-Delgado Sergio
Published: September 2023

Hydrogen as an energy vector is going to play an important role in the global energy mix. On the other hand, wastewater management has become a worldwide concern, as urban settlements have been considerably increasing for decades. Consequently, biodigestion to produce biogas (rich in methane) in water treatment plants could be an interesting starting point to obtain a valuable gas that can be converted into hydrogen through steam reforming. The aim of this work was to review the main aspects concerning steam reforming of biogas from wastewater treatment plants. For this purpose, the whole chain, from water treatment to hydrogen production and purification, was considered, paying attention to the main challenges and new technologies for its optimization. Thus, a wide range of possibilities is offered, from direct energy use of syngas to high purification of hydrogen (mainly through pressure swing adsorption or membrane reactors), presenting advantages and disadvantages. In any case, the role of catalysts seems to be essential, and aspects such as hydrogen sulfide and coke deposition control should be addressed. In conclusion, biogas steam reforming applied to wastewater treatment plants is a reality, with serious possibilities for its global implementation at the industrial level, according to techno-economic assessment.