bluuebunny/crossref_metadata_2025 huggingface dataset:
A Formal Model of the Exploitation Process for Railway Signalling Devices
Authors: Kornaszewski Mieczysław , Ciszewski Tomasz , Nowakowski Waldemar , Pniewski Roman
Published: December 2024

Railway signalling devices are used to ensure the safety of trains running on the railroad network. With the passage of time, the technical state of railway signalling devices deteriorates. During the exploitation of these devices, processes dependent on changes in technical states and changes in exploitation states occur. Achieving the maximum efficiency in the operation of a railway signalling system requires a shift from traditional corrective servicing to preventive service based on ongoing diagnosis of the technical state of the devices involved in train movements. An even greater opportunity is provided by the introduction of mathematical modelling methods into the exploitation testing of railway signalling devices and the prediction of their basic reliability indices well in advance. The proposed method allows the exploitation strategies for the signalling systems to be changed from a service-life-based strategy to a current-technical-state-based strategy while ensuring the required safety level.
Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting
Authors: Özüağ Simge , Ertuğrul Ömer
Published: December 2024

The objective of this study was to develop an artificial intelligence (AI)-driven model for the detection of helmet usage among workers in tractor and agricultural machinery factories with the aim of enhancing occupational safety. A transfer learning approach was employed, utilizing nine pre-trained neural networks for the extraction of deep features. The following neural networks were employed: MobileNetV2, ResNet50, DarkNet53, AlexNet, ShuffleNet, DenseNet201, InceptionV3, Inception-ResNetV2, and GoogLeNet. Subsequently, the extracted features were subjected to iterative neighborhood component analysis (INCA) for feature selection, after which they were classified using the k-nearest neighbor (kNN) algorithm. The classification outputs of all networks were combined through iterative majority voting (IMV) to achieve optimal results. To evaluate the model, an image dataset comprising 662 images of individuals wearing helmets and 722 images of individuals without helmets sourced from the internet was constructed. The proposed model achieved an accuracy of 90.39%, with DenseNet201 producing the most accurate results. This AI-driven helmet detection model demonstrates significant potential in improving occupational safety by assisting safety officers, especially in confined environments, reducing human error, and enhancing efficiency.
Research on Omnidirectional Gait Switching and Attitude Control in Hexapod Robots
Authors: Yue Min , Jiang Xiaoyun , Zhang Liqiang , Zhang Yujin
Published: December 2024

To tackle the challenges of poor stability during real-time random gait switching and precise trajectory control for hexapod robots under limited stride and steering conditions, a novel real-time replanning gait switching control strategy based on an omnidirectional gait and fuzzy inference is proposed, along with an attitude control method based on the single-neuron adaptive proportional–integral–derivative (PID). To start, a kinematic model of a hexapod robot was developed through the Denavit–Hartenberg (D-H) kinematics analysis, linking joint movement parameters to the end foot’s endpoint pose, which formed the foundation for designing various gaits, including omnidirectional and compound gaits. Incorporating an omnidirectional gait could effectively resolve the challenge of precise trajectory control for the hexapod robot under limited stride and steering conditions. Next, a real-time replanning gait switching strategy based on an omnidirectional gait and fuzzy inference was introduced to tackle the issue of significant impacts and low stability encountered during gait transitions. Finally, in view of further enhancing the stability of the hexapod robot, an attitude adjustment algorithm based on the single-neuron adaptive PID was presented. Extensive experiments confirmed the effectiveness of this approach. The results show that our approach enabled the robot to switch gaits seamlessly in real time, effectively addressing the challenge of precise trajectory control under limited stride and steering conditions; moreover, it significantly improved the hexapod robot’s dynamic stability during its motion, enabling it to adapt to complex and changing environments.
Conceptual Validation of High-Precision Fish Feeding Behavior Recognition Using Semantic Segmentation and Real-Time Temporal Variance Analysis for Aquaculture
Authors: Kong Han , Wu Junfeng , Liang Xuelan , Xie Yongzhi , Qu Boyu , Yu Hong
Published: December 2024

Aquaculture plays an important role in the global economy. However, unscientific feeding methods often lead to problems such as feed waste and water pollution. This study aims to address this issue by accurately recognizing fish feeding behaviors to provide automatic bait casting machines with scientific feeding strategies, thereby reducing farming costs. We propose a fish feeding behavior recognition method based on semantic segmentation, which overcomes the limitations of existing methods in dealing with complex backgrounds, water splash interference, fish target overlapping, and real-time performance. In this method, we first accurately segment fish targets in the images using a semantic segmentation model. Then, these segmented images are input into our proposed fish feeding behavior recognition model. By analyzing the aggregation characteristics during the feeding process, we can identify fish feeding behaviors. Experiments show that the proposed method has excellent robustness and real-time performance, and it performs well in the case of complex water background and occlusion of fish targets. We provide the aquaculture industry with an efficient and reliable method for recognizing fish feeding behavior, offering new scientific support for intelligent aquaculture and delivering powerful solutions to improve aquaculture management and production efficiency. Although the algorithm proposed in this study has shown good performance in fish feeding behavior recognition, it requires certain lighting conditions and fish density, which may affect its adaptability in different environments. Future research could explore integrating multimodal data, such as sound information, to assist in judgment, thereby enhancing the robustness of the model and promoting the development of intelligent aquaculture.
Elucidating Collapse-Resistant Mechanisms of Pore Geometries in Fire Ant Nest Cavities
Authors: Felgenhauer Tyler , Venkataraman Satchi , Mullen Ethan
Published: December 2024

Porous materials and structures, such as subterranean fire ant nests, are abundant in nature. It is hypothesized that these structures likely have evolved biological adaptations that enhance their collapse resistance. This research aims to elucidate the collapse-resistant mechanisms of pore geometries in fire ant nests. Finite Element Models of ant nests in soil were generated using X-ray CT imaging of aluminum castings of ant nests. Representative volume elements of the ant nests, representing porous structures at various depths, were analyzed under confined compression. This work on investigating fire ant (sp. Solenopsis Invicta) nests found them to be hierarchical and graded at various depths that affect how they resist loads and collapse. The top portion acts as a protective shield by distributing damage and absorbing energy. In contrast, the lower chambers localize stress, contributing to damage tolerance. This research provides evidence to suggest that ant nests have developed properties that allow them to resist collapse. These findings could inform the design of lightweight and durable cellular structures in various engineering fields.
Nucleic Acid Lateral Flow Assay Implemented with Isothermal Gene Amplification of SARS-CoV-2 RNA
Authors: Kyung Kangwuk , Lee Hyojin , Kim Soo-Kyung , Kim Dong-Eun
Published: December 2024

We developed a rapid and sensitive diagnostic platform that integrates isothermal viral gene amplification with a nucleic acid lateral flow assay (NALFA) to detect SARS-CoV-2 RNA. Isothermal gene amplification was performed by combining reverse transcription of viral RNA with recombinase polymerase amplification (RPA). In our diagnostic platform, DNA primers for the RPA reaction were modified by appending DNA tails, enabling the synthesis of tailed amplicon DNAs. These tailed amplicon DNAs were subsequently annealed to the complementary capture DNA probe affixed to the lateral flow strip during the NALFA of the reaction samples. The other side of each amplicon DNA tail was annealed to the reporter probe DNA conjugated with gold nanoparticles to visually detect the test line in the strip. This diagnostic platform reduces the time required to obtain readouts to within 1 h and can detect viral RNA concentrations as low as 3.1 cp/μL. Furthermore, when applied to nasopharyngeal clinical samples, our NALFA diagnostic platform yielded highly reliable molecular diagnostic readouts that were 100% consistent with the results of conventional RT-qPCR.
In-House Immunoglobulin Y-Based Immunoassay for Detecting Benzo[a]pyrene in Grilled Pork Samples
Authors: Jeeno Peerapong , Yadoung Sumed , Thongkham Marninphan , Yana Pichamon , Jaitham Udomsap , Ounjaijean Sakaewan , Xu Zhen-Lin , Sringarm Korawan , Hongsibsong Surat
Published: December 2024

Benzo[a]pyrene (B[a]P) is a hazardous polycyclic aromatic hydrocarbon that accumulates in several environmental matrices as a result of incomplete combustion. Its presence, carcinogenic properties, and tendency for bioaccumulation provide significant risks to human health and the environment. The objective of this study is to create an immunoassay for the detection of benzo[a]pyrene utilizing immunoglobulin Y antibodies. An indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) was utilized to develop a speedy, straightforward, sensitive, and economical approach for detecting B[a]P residues. Following the immunization of hens with the hapten pyrenebutyric acid-bovine serum albumin (PyBA-BSA), the IgY antibody extracted from egg yolk was utilized to identify B[a]P residues. To evaluate antibody specificity, six PAH derivatives—PyBA, B[a]P, Chrysene, Benzo[b]fluoranthene, Benzo[a]anthracene, and Benzo[k]fluoranthene—were examined in the experiment to compete for binding with PyBA. The findings indicate that the antibody had considerable affinity for Chrysene (1.15%), Benzo[b]fluoranthene (311.32%), Benzo[k]fluoranthene (10.62%), Benzo[a]anthracene (22.82%), and PyBA (9.55%). Nonetheless, its affinity for B[a]P remained at 100%. The recovery range for grilled pork samples spiked with B[a]P doses of 10.00–0.1 μg/mL was 74.99% to 143.11%. This study utilized a polyclonal antibody, employing the IgY antibody for the inaugural development of an immunoassay to detect benzo[a]pyrene. The ELISA had a higher IC50 value compared to the other immunoassays; however, it yielded good results. This immunoassay signifies a substantial progression in environmental analytical chemistry, offering a cost-effective and accessible technique for the detection of B[a]P to protect human health and the environment.
An Unlabeled Electrochemical Immunosensor Uses Poly(thionine) and Graphene Quantum Dot-Modified Activated Marigold Flower Carbon for Early Prostate Cancer Detection
Authors: Cotchim Suparat , Kongkaew Supatinee , Thavarungkul Panote , Kanatharana Proespichaya , Limbut Warakorn
Published: December 2024

The activated carbon from marigold flowers (MG) was used to make an unlabeled electrochemical immunosensor to determine prostate cancer. MG was synthesized by hydrothermal carbonization and pyrolysis. MG had a large surface area, was highly conductive, and biocompatible. MG modified with graphene quantum dots produced excellent electron transfer for grafting poly(thionine) (PTH). The amine group of PTH bonded with anti-prostate-specific antigen (Anti-PSA) via glutaraldehyde, forming a layer that improved electron transfer. The binding affinity of the immunosensor, presented as the dissociation constant (Kd), was calculated using the Langmuir isotherm model. The results showed that a lower Kd value indicated greater antibody affinity. The immunosensor exhibited two different linear ranges under optimized conditions: 0.0125 to 1.0 ng mL−1 and 1.0 to 80.0 ng mL−1. The sensor could detect concentrations as low as 0.005 ng mL−1, and had a quantification limit of 0.017 ng mL−1. This immunosensor accurately quantified PSA levels of human serum, and the results were validated using enzyme-linked fluorescence assay (ELFA).
Composition, Seasonal Dynamics and Metabolic Potential of the Rhizosphere Microbiome Associated with Wild White Poplar
Authors: Popchenko Mikhail I. , Karpov Dmitry S. , Gladysh Natalya S. , Kovalev Maxim A. , Volodin Vsevolod V. , Krasnov George S. , Bogdanova Alina S. , Bolsheva Nadezhda L. , Fedorova Maria S. , Kudryavtseva Anna V.
Published: December 2024

The white poplar (Populus alba) is a dioecious woody plant with significant potential for the phytoremediation of soils. To realize this potential, it is necessary to utilize growth-promoting microorganisms. One potential source of such beneficial microorganisms is the rhizosphere community of wild-growing trees. However, the structure, dynamics, and metabolism of the rhizosphere community of wild-growing white poplar remain poorly understood. To ascertain seasonal dynamics, species diversity, and metabolic potential, we sequenced 16S rRNA genes in metagenomes derived from 165 soil samples collected in spring and autumn from the root surfaces of 102 trees situated in disparate geographical locations. The three most prevalent phyla across all samples are Proteobacteria, Actinobacteriota, and Acidobacteriota. At the order level, the most prevalent orders are Sphingomonadales and Rhizobiales. Accordingly, the families Sphingomonadaceae and Rhizobiaceae were identified as dominant. The rhizospheric microbiome exhibited substantial inter-seasonal variation. Six families, including Caulobacteraceae, Xanthomonadaceae, Chitinophagaceae, Chthoniobacteraceae, Sphingomonadaceae, and Rhizobiaceae, exhibited alterations (spring-to-autumn) across all geographical locations under study. Members of the Rhizobiaceae family, which includes nitrogen-fixing bacteria, can provide poplar with plant-available forms of nitrogen such as nitrate and ammonium. The rhizosphere microbiome may facilitate the conversion of inorganic sulfur into sulfur-containing amino acids, cysteine and methionine, that are bioavailable to plants. Furthermore, the rhizosphere microbiome is capable of synthesizing amino acids, organic acids (including Krebs cycle acids), and some lipids and sugars. Consequently, the rhizosphere community can stimulate poplar growth by providing it with readily available forms of nitrogen and sulfur, as well as building blocks for the synthesis of proteins, nucleic acids, and other macromolecules. Many of these pathways, including nitrogen fixation, were subjected to seasonal changes.
Prognostic Impact of Multiple Synchronous T1 Breast Cancer
Authors: Gwak Hongki , Jung Sung Hoo , Suh Young Jin , Nam Seok Jin , Han Jai Hong , Oh Se Jeong , Park Eun Hwa , Kim Seong Hwan
Published: December 2024

Background/Objectives: The reported incidence of multiple breast cancers varies widely, ranging from 6 to 60%, depending on the definitions used and methods of detection. With advancements in preoperative imaging techniques, such as magnetic resonance imaging, the detection of multiple breast cancers has improved. However, the clinical significance of multiple breast cancers remains controversial, with conflicting results regarding their impact on prognosis. We investigated the association between the number of synchronous ipsilateral T1 breast tumors, overall survival (OS), and breast cancer-specific survival (BCSS). Methods: We retrospectively analyzed 45,881 patients diagnosed with invasive breast cancer who underwent surgery between 2004 and 2016. The patients were categorized based on the number of tumors: one (n = 43,234), two (n = 2241), and three or more (n = 406). The OS and BCSS scores were compared across the groups. Results: There were no significant differences between the one- and two-tumor groups (p = 0.490 and p = 0.650, respectively). However, patients with three or more tumors had significantly lower OS and BCSS rates than those with one or two tumors (p < 0.001 for both comparisons). Multivariate analysis confirmed that the number of tumors (three or more) was an independent risk factor for poor OS and BCSS. Conclusions: Our findings suggest that patients with synchronous ipsilateral T1 breast cancers and three or more tumors may benefit from escalated treatment strategies due to their potentially worse prognosis.
Colorectal Neoplasia Detection Rates in Lynch Syndrome
Authors: Mirda Danielle , Dungan Michaela , Ren Yue , Li Hongzhe , Katona Bryson W.
Published: December 2024

Background: The expected and optimal adenoma detection rate (ADR) is not well characterized in Lynch syndrome (LS). The aim of this study is to determine the ADR, the overall colorectal neoplasia detection rate (CNDR), proximal serrated detection rate (PSDR), and CRC detection rate (CRCDR) in an LS cohort. Methods: A retrospective study was performed of individuals with LS who were evaluated at a single tertiary care center from May 2001 to September 2023 (n = 542). Data from procedure and pathology reports were collected along with relevant demographic, clinical history, and family history data. Fisher’s exact test and the Kruskal–Wallis test were used to assess factors associated with colorectal neoplasia. Results: Amongst 542 individuals with LS, 352 met the inclusion criteria, and their 1296 colonoscopies/sigmoidoscopies were used for analysis. The cohort was primarily female (64.5%), white (87.5%), and privately insured (76.1%), with a near even distribution across genotypes. CNDR was 27.9%, ADR was 21.4%, PSDR was 7.7%, and CRCDR was 1.5%. Advanced age, Medicare insurance, prior colonic resection, and prior history of non-CRC were significantly associated with an increased CNDR and ADR (p < 0.05). PSDR remained constant with age. There was no association with genotype, biological sex, race, smoking, BMI, aspirin use, nor family history. Conclusions: Despite frequent colonoscopies/sigmoidoscopies, individuals with LS maintain a high rate of colorectal neoplasia, primarily driven by increased detection of adenomas with advancing age. Neoplasia rates may serve as helpful “ballpark rates” for endoscopists performing colonoscopies/sigmoidoscopies in LS. However, further studies need to determine whether neoplasia rates are predictive of CRC risk and outcomes in LS.
Salvage Therapy with Second-Generation Inhibitors for FLT3 Mutated Acute Myeloid Leukemia: A Real-World Study by the CETLAM and PETHEMA Groups
Authors: Vives Susana , Quintela David , Morgades Mireia , Cano-Ferri Isabel , Serrano Alfons , Acuña-Cruz Evelyn , Cervera Marta , Díaz-Beyá Marina , Vidriales Belén , Raposo-Puglia José Ángel , Arnan Montserrat , Garrido Ana , Balerdi Amaia , Cabello Ana Isabel , Herrera-Puente Pilar , Serrano Josefina , Coll Rosa , Tormo Mar , López-Marín Javier , García-Ávila Sara , Casado María Soledad , Padilla Irene , Rodríguez-Macías Gabriela , Calbacho María , Puchol Ana , Hernández Agustín , Torres Melissa , Costilla Lissette , Colorado Maria Mercedes , Martínez-Cuadrón David , Esteve Jordi , Montesinos Pau
Published: December 2024

Background/Objectives: Patients with relapsed/refractory (R/R) AML with FLT3 mutation (FLT3mut) have a dismal prognosis. FLT3mut offers a target for therapy in these patients. Gilteritinib (gilter) and quizartinib (quizar) have demonstrated efficacy as single agents in two phase 3 clinical trials. Methods: We retrospectively analyzed the characteristics, treatments, and outcomes of 50 patients with R/R FLT3mut AML who received gilter or quizar as monotherapy in 27 Spanish centers before their commercial availability. Forty-four patients were treated with gilter and six with quizar. Results: The median age was 62.5 years, and 52% were women. Most patients presented with FLT3-ITD mutations (80%); 46% had refractory disease and 54% had relapsed disease at treatment initiation. First-line treatment was chemotherapy in 80% of patients, with 40% of these also receiving midostaurin. Twenty-five patients (50%) had previously received FLT3 inhibitor, and twenty-eight (56%) had received more than one line treatment before starting gilter/quizar. The rates of complete remission (CR), CR without hematological recovery (CRi), and partial remission were 22%, 18%, and 16%, respectively. The median overall survival (OS) and disease-free survival were 4.74 months and 2.99 months, respectively. We observed a significant improvement in OS in patients who had received only one prior line of therapy compared to those who had received two or more therapies (10.77 months vs. 4.24 months, p = 0.016). Multivariate analysis identified failure to achieve CR/CRi, receiving more than one prior line of therapy, age, and white blood cells count as independent prognostic factors for OS. The most common toxicities were febrile neutropenia, liver function abnormalities, and QT interval prolongation. Conclusions: Gilter/quizar monotherapy are effective and tolerable options for patients with R/R FLT3mut AML in a real-world setting. Response and toxicity rates are similar to those reported in the phase 3 trials, despite the more heterogeneous nature of the study population.
Role of Artificial Intelligence in Human Papillomavirus Status Prediction for Oropharyngeal Cancer: A Scoping Review
Authors: Migliorelli Andrea , Manuelli Marianna , Ciorba Andrea , Stomeo Francesco , Pelucchi Stefano , Bianchini Chiara
Published: December 2024

Human papillomavirus (HPV) infection is sexually transmitted and commonly widespread in the head and neck region; however, its role in tumor development and prognosis has only been demonstrated for oropharyngeal squamous cell carcinoma (HPV-OPSCC). The aim of this review is to analyze the results of the most recent literature that has investigated the use of artificial intelligence (AI) as a method for discerning HPV-positive from HPV-negative OPSCC tumors. A review of the literature was performed using PubMed/MEDLINE, EMBASE, and Cochrane Library databases, according to PRISMA for scoping review criteria (from 2017 to July 2024). A total of 15 articles and 4063 patients have been included. Eleven studies analyzed the role of radiomics, and four analyzed the role of AI in determining HPV histological positivity. The results of this scoping review indicate that AI has the potential to play a role in predicting HPV positivity or negativity in OPSCC. Further studies are required to confirm these results.
Regulation of Stromal Cells by Sex Steroid Hormones in the Breast Cancer Microenvironment
Authors: Yamaguchi-Tanaka Mio , Takagi Kiyoshi , Sato Ai , Yamazaki Yuto , Miyashita Minoru , Masamune Atsushi , Suzuki Takashi
Published: December 2024

Breast cancer is a prevalent hormone-dependent malignancy, and estrogens/estrogen receptor (ER) signaling are pivotal therapeutic targets in ER-positive breast cancers, where endocrine therapy has significantly improved treatment efficacy. However, the emergence of both de novo and acquired resistance to these therapies continues to pose challenges. Additionally, androgens are produced locally in breast carcinoma tissues by androgen-producing enzymes, and the androgen receptor (AR) is commonly expressed in breast cancer cells. Intratumoral androgens play a significant role in breast cancer progression and are closely linked to resistance to endocrine treatments. The tumor microenvironment, consisting of tumor cells, immune cells, fibroblasts, extracellular matrix, and blood vessels, is crucial for tumor progression. Stromal cells influence tumor progression through direct interactions with cancer cells, the secretion of soluble factors, and modulation of tumor immunity. Estrogen and androgen signaling in breast cancer cells affects the tumor microenvironment, and the expression of hormone receptors correlates with the diversity of the stromal cell profile. Notably, various stromal cells also express ER or AR, which impacts breast cancer development. This review describes how sex steroid hormones, particularly estrogens and androgens, affect stromal cells in the breast cancer microenvironment. We summarize recent findings focusing on the effects of ER/AR signaling in breast cancer cells on stromal cells, as well as the direct effects of ER/AR signaling in stromal cells.
Synthetic Boosted Resampling Using Deep Generative Adversarial Networks: A Novel Approach to Improve Cancer Prediction from Imbalanced Datasets
Authors: Gurcan Fatih , Soylu Ahmet
Published: December 2024

Background/Objectives: This study examines the effectiveness of different resampling methods and classifier models for handling imbalanced datasets, with a specific focus on critical healthcare applications such as cancer diagnosis and prognosis. Methods: To address the class imbalance issue, traditional sampling methods like SMOTE and ADASYN were replaced by Generative Adversarial Networks (GANs), which leverage deep neural network architectures to generate high-quality synthetic data. The study highlights the advantage of GANs in creating realistic, diverse, and homogeneous samples for the minority class, which plays a significant role in mitigating the diagnostic challenges posed by imbalanced data. Four types of classifiers, Boosting, Bagging, Linear, and Non-linear, were assessed to evaluate their performance using metrics such as accuracy, precision, recall, F1 score, and ROC AUC. Results: Baseline performance without resampling showed significant limitations, underscoring the need for resampling strategies. Using GAN-generated data notably improved the detection of minority instances and overall classification performance. The average ROC AUC value increased from baseline levels of approximately 0.8276 to over 0.9734, underscoring the effectiveness of GAN-based resampling in enhancing model performance and ensuring more balanced detection across classes. With GAN-based resampling, GradientBoosting classifier achieved a ROC AUC of 0.9890, the highest among all models, demonstrating the effectiveness of GAN-generated data in enhancing performance. Conclusions: The findings underscore that advanced models like Boosting and Bagging, when paired with effective resampling strategies such as GANs, are better suited for handling imbalanced datasets and improving predictive accuracy in healthcare applications.
Landscape of Biomarkers and Pathologic Response in Rectal Cancer: Where We Stand?
Authors: Ocanto Abrahams , Teja Macarena , Amorelli Francesco , Couñago Felipe , Gomez Palacios Ariel , Alcaraz Diego , Cantero Ramón
Published: December 2024

Colorectal cancer (CRC) is a neoplasm with a high prevalence worldwide, with a multimodal treatment that includes a combination of chemotherapy, radiotherapy, and surgery in locally advanced stages with acceptable pathological complete response (pCR) rates, this has improved with the introduction of total neoadjuvant therapy (TNT) reaching pCR rates up to 37% in compare with classic neoadjuvant treatment (NAT) where pCR rates of around 20–25% are achieved. However, the patient population that benefits most from this therapy has not been determined, and there is a lack of biomarkers that can predict the course of the disease. Multiple biomarkers have been studied, ranging from hematological and molecular markers by imaging technique and combinations of them, with contradictory results that prevent their use in routine clinical practice. In this review, we evaluate the most robust prognostic biomarkers to be used in clinical practice, highlighting their advantages and disadvantages and emphasizing biomarker combinations and their predictive value.
Elevated Expression of Cell Adhesion, Metabolic, and Mucus Secretion Gene Clusters Associated with Tumorigenesis, Metastasis, and Poor Survival in Pancreatic Ductal Adenocarcinoma
Authors: Balakrishnan Karthik , Xiao Yi , Chen Yuanhong , Dong Jixin
Published: December 2024

Objectives: Technological advances in identifying gene expression profiles are being applied to study an array of cancers. The goal of this study was to identify differentially expressed genes in pancreatic ductal adenocarcinoma (PDAC) and examine their potential role in tumorigenesis and metastasis. Methods: The transcriptomic profiles of PDAC and non-tumorous tissue samples were derived from the gene expression omnibus (GEO), which is a public repository. The GEO2R tool was used to further derive differentially expressed genes from those profiles. Results: In this study, a total of 68 genes were derived from upregulated PDAC genes in three or more transcriptomic profiles and were considered PDAC gene sets. The identified PDAC gene sets were examined in the molecular signatures database (MSigDB) for ontological investigation, which revealed that these genes were involved in the extracellular matrix and associated with the cell adhesion process in PDAC tumorigenesis. The gene set enrichment analysis showed greater enrichment scores for the gene sets. Moreover, the identified gene sets were examined for protein–protein interaction using the STRING database. Based on functional k-means clustering, the following three functional cluster groups were identified in this study: extracellular matrix/cell adhesion, metabolic, and mucus secretion-related protein groups. The receiver operating characteristic (ROC) curve revealed greater specificity and sensitivity for these cluster genes in predicting PDAC tumorigenesis and metastases. In addition, the expression of the cluster genes affects the overall survival rate of PDAC patients. Using the cancer genome atlas (TCGA) database, the associations between expression levels and clinicopathological features were validated. Conclusions: Overall, the genes identified in this study appear to be critical in PDAC development and can serve as potential diagnostic and prognostic targets for pancreatic cancer treatment.
Association of Lung Immune Prognostic Index (LIPI) with Disease Control Rate and Progression-Free Survival in Patients with Soft-Tissue Sarcoma Treated with Immunotherapy in Early-Phase Trials
Authors: Zoghbi Marianne , Patel Brina A. , Roulleaux Dugage Matthieu , Mezquita Laura , Bahleda Rastilav , Dufresne Armelle , Brahmi Mehdi , Ray-Coquard Isabelle , Pautier Patricia , Blay Jean-Yves , Le Cesne Axel , Massard Christophe , Besse Benjamin , Auclin Edouard , Nassif Haddad Elise F.
Published: December 2024

Background: The efficacy of immunotherapies in soft-tissue sarcomas (STSs) is limited, and biomarkers of response are lacking. The lung immune prognostic index (LIPI) is a prognostic biomarker used with immunotherapy across cancer types. This study investigates the association of LIPI with the disease control rate (DCR) and progression-free survival (PFS) in patients with STS treated with immunotherapy versus other therapies in early-phase trials. Methods: This post hoc analysis was conducted with patients with STS from Gustave Roussy and Centre Léon Bérard between January 2012 and June 2021. The LIPI was calculated based on a derived neutrophil-to-lymphocyte ratio > 3 and elevated lactate dehydrogenase. Patients were categorized based on treatment (immunotherapy or other) and LIPI (good, intermediate, or poor). DCR was defined as the sum of stable disease and complete and partial response. Results: A total of 82 patients were enrolled in immunotherapy trials and 126 in the other therapy trials. In the immunotherapy group, DCR was higher in patients with good LIPI (76%; n = 23/30) compared with the intermediate (50%; n = 13/26) and poor LIPI groups (8%; n = 1/12; p < 0.001). The other-therapy group did not show significant differences in DCR by LIPI: DCR was 70% (n = 48/69), 70% (n = 21/30), and 60% (n = 6/10) in patients with good, intermediate, and poor LIPI, respectively (p = 0.86). In multivariate analyses, LIPI was independently associated with PFS in the immunotherapy group (hazard ratio = 5.97, p = 0.0001) and not in the control group (p = 0.71). Conclusions: LIPI is a significant independent prognostic marker for DCR in patients with STS treated with immunotherapy. In early-phase trials, LIPI could be used as a screening tool for stratification at inclusion. High neutrophil levels, which correlate with a poorer LIPI score, are likely associated with immunotherapy resistance. This relationship could explain the statistical impact of poor LIPI in the immunotherapy group.
Class B Scavenger Receptor CD36 as a Potential Therapeutic Target in Inflammation Induced by Danger-Associated Molecular Patterns
Authors: Baranova Irina N. , Bocharov Alexander V. , Vishnyakova Tatyana G. , Chen Zhigang , Ke Yunbo , Birukova Anna A. , Yuen Peter S. T. , Tsuji Takayuki , Star Robert A. , Birukov Konstantin G. , Patterson Amy P. , Eggerman Thomas L.
Published: December 2024

The class B scavenger receptor CD36 is known to bind and mediate the transport of lipid-related ligands and it functions as a pattern recognition receptor (PRR) for a variety of pathogens, including bacteria and viruses. In this study, we assessed CD36’s role as a PRR mediating pro-inflammatory effects of several known Danger-Associated Molecular Patterns (DAMPs) used either as a single preparation or as a combination of DAMPs in the form of total cell/skeletal muscle tissue lysates. Our data demonstrated that multiple DAMPs, including HMGB1, HSPs, histone H3, SAA, and oxPAPC, as well as cell/tissue lysate preparations, induced substantially higher (~7–10-fold) IL-8 cytokine responses in HEK293 cells overexpressing CD36 compared to control WT cells. At the same time, DAMP-induced secretion of IL-6 in bone marrow-derived macrophages (BMDM) from CD36−/− mice was markedly (~2–3 times) reduced, as compared to macrophages from normal mice. Synthetic amphipathic helical peptides (SAHPs), known CD36 ligands, efficiently blocked CD36-dependent inflammatory responses induced by both cell and tissue lysates, HMGB1 and histone H3 in CD36+ cells. IP injection of total cellular lysate preparation induced inflammatory responses that were assessed by the expression of liver and lung pro-inflammatory markers, including IL-6, TNF-α, CD68, and CXCL1, and was reduced by ~50% in CD36-deficient mice compared to normal mice. Our findings demonstrate that CD36 is a PRR contributing to the innate immune response via mediating DAMP-induced inflammatory signaling and highlight the importance of this receptor as a potential therapeutic target in DAMP-associated inflammatory conditions.
Using Differential Scanning Calorimetry to Measure the Energetic Properties of Residual Sludge and Catalysts from the Textile, Tannery, and Galvanic Industries
Authors: Carvajal-Chávez Ghem , Cazar Josselyn , Gordillo Gilda , De-La-Rosa Andrés , Chiriboga Gonzalo , Montero-Calderón Carolina
Published: December 2024

This research delved into the energetic properties of catalysts synthesized from residual sludge from the textile, galvanic, and tannery industries. The experimental process consisted of an initial heat treatment to activate their catalytic properties and a thermal analysis employing differential scanning calorimetry (DSC). This technique permitted the investigation of the materials’ thermal behavior as a function of temperature, ranging from 142 to 550 °C, effectively controlling the heating rates and pressure conditions. The data gathered were the input for constructing specific heat models through polynomial regression employing the least squares method. These models were subsequently used to estimate variations in the enthalpy and entropy for both the sludge and catalysts through integration. Third-degree polynomials primarily characterized the specific heat models that accurately represented the samples’ thermal behavior, considering variations in their physicochemical properties that influenced it. The catalysts derived from residual sludge from the textile industry exhibited the models with the most robust statistical fit. Concurrently, the catalysts from the galvanic industry displayed noteworthy similarities with the bibliographic data across various temperature points. The mathematical models determined the specific heat (Cp) as a function of temperature, which, in turn, was used to estimate the enthalpy and entropy variations in the sludge and catalysts under study. The highest enthalpy value corresponded to the sludge and catalyst obtained from the tannery industry, with a Cp of 5.60 J/g-K at 603 K and 2.45 J/g-K at 445.6 K. Finally, the third-degree polynomials showed the best mathematical models since (1) they considered the variations in the physicochemical properties that intervened in the behavior of Cp as a function of temperature; (2) they presented a better statistical fit; and (3) they showed consistency with the existing information in the literature for the textile industry and the galvanic industries.
Chemical Inhibitors in Gas Hydrate Formation: A Review of Modelling Approaches
Authors: Zulu Njabulo Mziwandile , Hashemi Hamed , Tumba Kaniki
Published: December 2024

Gas hydrate inhibition using chemicals has been under continuous investigation, and several modelling studies have been published since its inception. Since it is not always feasible to conduct experimental research, it is especially crucial to forecast the conditions under which gas hydrates may form and dissociate in the presence of chemical inhibitors. As a result, a reliable forecasting tool is vital. This article provides an exhaustive review of various modelling methodologies in the context of gas hydrate chemical inhibition. The key aspects of empirical models, thermodynamic models, kinetic models, artificial intelligence-based models and quantum chemistry-based models are presented. Critical analysis of each modelling approach has been performed, highlighting strengths, limitations, and areas where further investigations are still crucial. Rapid progress has been made with respect to gas hydrate modelling approaches in the context of chemical inhibition; however, further research is still vital to bridge the gaps that have been identified in this review. Potential improvements to existing models have been proposed, particularly in terms of integrating experimental data and utilizing hybrid approaches, which could serve as valuable future directions for the field.
Formation Conditions of Unusual Extremely Reduced High-Temperature Mineral Assemblages in Rocks of Combustion Metamorphic Complexes
Authors: Peretyazhko Igor S. , Savina Elena A.
Published: December 2024

New data, including Raman spectroscopy, characterize unusual mineral assemblages from rocks of the Naylga and Khamaryn–Khyral–Khiid combustion metamorphic complexes in Mongolia. Several samples of melilite–nepheline paralava and other thermally altered (metamorphosed) sedimentary rocks contain troilite (FeS), metallic iron Fe0, kamacite α-(Fe,Ni) or Ni-bearing Fe0, taenite γ-(Fe,Ni) or Ni-rich Fe0, barringerite or allabogdanite Fe2P, schreibersite Fe3P, steadite Fe4P = eutectic α-Fe + Fe3P, wüstite FeO, and cohenite Fe3C. The paralava matrix includes a fragment composed of magnesiowüstite–ferropericlase (FeO–MgO solid solution), as well as of spinel (Mg,Fe)Al2O4 and forsterite. The highest-temperature mineral assemblage belongs to a xenolithic remnant, possibly Fe-rich sinter, which is molten ash left after underground combustion of coal seams. The crystallization temperatures of the observed iron phases were estimated using phase diagrams for the respective systems: Fe–S for iron sulfides and Fe–P ± C for iron phosphides. Iron monosulfides (high-temperature pyrrhotite) with inclusions of Fe0 underwent solid-state conversion into troilite at 140 °C. Iron phosphides in inclusions from the early growth zone of anorthite–bytownite in melilite–nepheline paralava crystallized from <1370 to 1165 °C (Fe2P), 1165–1048 °C (Fe3P), and <1048 °C (Fe4P). Phase relations in zoned spherules consisting of troilite +Fe0 (or kamacite + taenite) +Fe3P ± (Fe3C, Fe4P) reveal the potential presence of a homogeneous Fe–S–P–C melt at T~1350 °C, which separated into two immiscible melts in the 1350–1250 °C range; namely, a dense Fe–P–C melt in the core and a less dense Fe–S melt in the rim. The melts evolved in accordance with cooling paths in the Fe–S and Fe–P–C phase diagrams. Cohenite and schreibersite in the spherules crystallized between 988 °C and 959 °C. The crystallization temperatures of minerals were used to reconstruct redox patterns with respect to the CCO, IW, IM, and MW buffer equilibria during melting of marly limestone and subsequent crystallization and cooling of melilite–nepheline paralava melts. The origin of the studied CM rocks was explained in a model implying thermal alteration of low-permeable overburden domains in reducing conditions during wild subsurface coal fires, while heating was transferred conductively from adjacent parts of ignited coal seams. The fluid (gas) regime in the zones of combustion was controlled by the CCO buffer at excess atomic carbon. Paralava melts exposed to high-temperature extremely reducing conditions contained droplets of immiscible Fe–S–P–C, Fe–S, Fe–P, and Fe–P–C melts, which then crystallized into reduced mineral assemblages.
Redescription of Euscorpius studentium Based on Adult Specimens; Updated Classification of Cavernicolous Euscorpiidae; and Review of Cavernicolous Scorpions in the Balkans
Authors: Blasco-Aróstegui Javier , Prendini Lorenzo
Published: December 2024

Cavernicolous scorpions are difficult to collect and study due to their often inaccessible habitats. Some have evolved unique morphological adaptations, known as troglomorphies, including reduced sclerotization and pigmentation, reduction and/or loss of eyes, attenuation and elongation of the appendages, which assist them to thrive in dark, humid and low-energy input environments. Cavernicolous scorpions are classified into accidentals, trogloxenes, troglophiles, and troglobites. The Balkans, and particularly the Dinaric Karst region, host a diverse cave-adapted fauna, including scorpions. Despite an 1895 report of a blind scorpion from Bosnia and Herzegovina, the first truly troglobitic European scorpion, Euscorpius studentium Karaman, 2020, was only described a few years ago, based on two immature specimens. In the present contribution, this unique species is redescribed based on the first adult specimens; the ecological classification of all currently known cavernicolous Euscorpiidae Laurie, 1896, is updated; a key to the identification of cavernicolous scorpions occurring in the Dinaric Karst is provided; and the historical and geographical factors affecting the distribution and conservation of cavernicolous scorpions in the Balkans is reviewed.
Reconstructing Historical Changes in the Macroalgal Vegetation of a Central Mediterranean Coastal Area Based on Herbarium Collections
Authors: Rindi Fabio , Bellanti Giulia , Annibaldi Anna , Accoroni Stefano
Published: December 2024

Well-conserved herbarium specimens of marine macroalgae represent a valuable resource for multiple types of investigation. When algal herbaria host specimens collected over long time spans from a certain geographic area, they have the potential to document historical changes in the benthic vegetation of that area. In this study, historical changes in the macroalgal vegetation of a central Mediterranean coast (Conero Riviera, Adriatic Sea) were assessed based on a critical re-examination of the herbarium of Irma Pierpaoli (collection period 1925–1951) and the phycological herbarium of the Polytechnic University of Marche (ANC ALG, collections made mostly in the period 1999–2024). For both herbaria, the identifications of many specimens were revised based on the current species circumscriptions. The comparison indicates that some major changes occurred between the two collection periods: a switch in the morphological functional structure of the vegetation (increase in the number of filamentous species, decrease in leathery macrophytes, and the near disappearance of calcareous articulated algae), local extinction of some species (at least 23, possibly more), and introduction of 11 species of non-indigenous seaweeds. Anthropogenic impacts (habitat destruction, increase in sediment load, and impacts of port activities and maritime traffic) are considered the main factors responsible for these changes.
Free-Forming of Customised NFRP Profiles for Architecture Using Simplified Adaptive and Stay-In-Place Moulds
Authors: Baszyński Piotr , Dahy Hanaa
Published: December 2024

Design and production technology of natural fibre reinforced polymers not only aims to offer products with a lower environmental impact than conventional glass fibre composites but also caters for designers’ needs for the fabrication of lightweight free-formed architectural components. To combine both characteristics, the forming process itself, once scaled up, needs to be based on efficient material moulding strategies. Based on case studies of adaptive forming techniques derived from the composite industry and concrete casting, two approaches for the mass production of customised NFRP profiles are proposed. Both processes are based on foam from recycled PET, which is used as either a removable mould or a stay-in-place (SIP) core. Once the textile reinforcement is placed on a mould, either by helical winding of natural fibre prepregs or in the form of mass-produced textile preforms, its elastic properties allow for the free-forming of the composite profile before the resin is fully cured. This paper investigates the range of deformations that it is possible to achieve by each method and describes the realisation of a small structural demonstrator, in the form of a stool, through the helical winding of a flax prepreg on a SIP core.