bluuebunny/crossref_metadata_2025 huggingface dataset:
Blood-brain barrier disruption mediates the association between cerebral small vessel disease and clinical outcome after stroke: a secondary analysis of the Lesion Evolution in Stroke and Ischemia on Neuroimaging study
Authors: Okine Derrick N. , Kern Kyle C. , Luby Marie , Latour Lawrence L. , Gottesman Rebecca F.
Published: December 2024

Introduction

White matter hyperintensities (WMH) in patients presenting with acute ischemic stroke are associated with worse clinical outcomes, but the mechanisms underlying this association are unclear. The purpose of this study was to determine whether blood-brain barrier (BBB) disruption, detected as the hyperintense acute reperfusion marker (HARM) on post-gadolinium follow-up FLAIR MRI, is associated with WMH and mediates the association between WMH and stroke outcomes.

Methods

This is a secondary analysis of the LESION study, where patients with suspected acute ischemic stroke who were candidates for acute stroke intervention or had a baseline NIHSS ≥4 underwent serial multimodal MRI within 24 h of last-known-well time, and again at 2 or 24 h. WMH were visually graded on baseline FLAIR for presence and severity (minor or moderate-severe). HARM was evaluated on post-gadolinium FLAIR for presence and severity (minor, severe focal or severe diffuse). Using binomial and multinomial logistic regression, we tested whether WMH grade was associated with presence or severity of HARM, covarying for demographics, vascular risk factors, and stroke characteristics in sequential models. Finally, we used structural equation models to test the mediation effects of severe HARM on the association between WMH and stroke outcomes, including discharge NIHSS, hemorrhagic transformation, and 90-day modified Rankin scale.

Results

For 213 stroke patients (mean age 70 years, 54% female), higher WMH grade was associated with increased risk for severe diffuse HARM (OR: 3.37, 95% CI: 1.45–7.81), although not after adjusting for vascular risk factors or stroke characteristics. In our univariate model, severe HARM had a partial mediating effect between WMH and discharge NIHSS, explaining 23% of the association.

Discussion

These findings suggest a possible association between severe diffuse HARM and WMH severity. The relationship between WMH severity and early stroke outcome may be mediated by blood-brain barrier disruption.
Leveraging financing technology for sustainable fresh agricultural products financing in Indonesia
Authors: Karyani Tuti , Perdana Tomy , Sadeli Agriani Hermita , Utami Hesty Nurul , Renaldi Eddy
Published: December 2024

Financial technology (fintech) offers farmers the prospect of getting other sources of finance apart from financial assistance from the established official funding institutions. Farmers of fresh agricultural products (FAP) in Indonesia received financial offers from various fintech platforms. However, several platforms have failed to maintain their operations, resulting in negative consequences for the farming activities. This study’s objective is to explore how fintech contributes to the sustainability of FAP by examining five key dimensions of sustainability: economic, social, environmental, technological, and institutional. Most extant literature primarily examines the determinants that impact an individual’s interest in fintech lending. However, the existing research needs to dedicate more attention to the sustainability of the platform and the enterprises it finances, with a particular emphasis on the FAP sector. A quantitative methodology was utilized to design the study, and a proportional stratified random sampling method was employed to select 269 FAP producers as respondents. The data were analyzed using the multidimensional scaling (MDS) approach in rap-Agrifin using factors specifically designed to assess fintech sustainability in agribusiness. Fintech in the FAP supply chain is classified as quite sustainable, according to this study’s multidimensional finding. Partially, the dimensions that acquire sufficiently sustainable value are the social, economic, and environmental dimensions, but the technological and institutional dimensions are less sustainable. This research demonstrates that the MDS approach in rap-Agrifin can effectively analyze sustainable finance in agriculture, highlighting the need for focused improvement on institutional and technological factors, particularly through the application of fintech.
Assessing subsidy integration in the 40 years of agricultural planning in the Maldives
Authors: Mohamed Ilham Atho
Published: December 2024

87% of agricultural subsidies are harmful to the environment and human health while contributing little to food security. The first step to addressing harmful subsidies is to identify and trace them in policies. Small Island Developing States (SIDS), such as the Maldives, are the most vulnerable to environmental degradation caused by activities they contribute minimally. In the case of subsidies, the relative contribution to the environmental degradation by islands and the relative impacts of subsidies on islands are not studied, leaving a void in the global knowledge pool. This paper addresses the first step of this gap by identifying and assessing the historical trends of subsidy integration in Maldivian agricultural policy by analyzing their temporal distribution patterns and the quality of subsidy inclusion in national plans in the past four decades. The framework adopted for this study is a multi-criteria scoring protocol and a classification of 15 subsidy types to deliver a quantitative overview of the status and trends in subsidy in the agriculture sector of the Maldives. The results showed that although the scale of agriculture in the country is limited, subsidies have consistently been an integral part of agricultural planning since 1985, with agricultural inputs being one of the most frequently and highly subsidized over the years. Twelve different subsidy types were traced in the ten assessed national plans, and eleven subsidy types were identified in the plan from 2019 to 2023. These results serve as a baseline for the understanding of subsidies in the Maldives by providing a narrative of an island state for the global overview of subsidies and for comparative studies thereof.
IPMC-Based Purcell’s Three-Link Swimmer: Simulations and Experiments at Low-Reynolds Conditions
Authors: Nuevo-Gallardo Cristina , Tejado Inés , Hunt Andres , Vinagre Blas M.
Published: December 2024

The Purcell’s swimmer, consisting of three links with two one-degree-of-freedom joints as defined by Edward M. Purcell, has been studied by several authors since its introduction in 1977. Researchers have delved into its mathematical foundations, analysing and optimising its motion for efficient propulsion. However, despite these theoretical advances, the practical realisation and experimental characterisation of Purcell’s swimmers remains relatively unexplored. Critical aspects such as material selection, manufacturing techniques, and experimental validation under real conditions represent important knowledge gaps. This paper contributes to bridging this gap by presenting a prototype of such a swimmer using ionic polymer-metal composites (IPMC) as link actuators. A simulation model is developed based on physical modelling tools in MATLAB®/Simulink®. Both simulation and experimental results at low-Reynolds-number (Re) conditions are presented to demonstrate the performance of the swimmer.
Research and Experiments on Adaptive Root Cutting Using a Garlic Harvester Based on a Convolutional Neural Network
Authors: Yang Ke , Zhou Yunlong , Shi Hengliang , Yao Rui , Yu Zhaoyang , Zhang Yanhua , Peng Baoliang , Fan Jiali , Hu Zhichao
Published: December 2024

Aimed at the problems of a high leakage rate, a high cutting injury rate, and uneven root cutting in the existing combined garlic harvesting and root-cutting technology, we researched the key technologies used in a garlic harvester for adaptive root cutting based on machine vision. Firstly, research was carried out on the conveyor alignment and assembly of the garlic harvester to realize the adjustment of the garlic plant position and the alignment of the bulb’s upper surface before the roots were cut, to establish the parameter equations and to modify the structure of the conveyor to form the adaptive garlic root-cutting system. Then, a root-cutting test using the double-knife disk-type cutting device was carried out to examine the root-cutting ability of the cutting device. Finally, a bulb detector trained with the IRM-YOLO model was deployed on the Jetson Nano device (NVIDIA, Jetson Nano(4GB), Santa Clara, CA, USA) to conduct a harvester field trial study. The pass rate for the root cutting was 82.8%, and the cutting injury rate was 2.7%, which tested the root cutting performance of the adaptive root cutting system and its field environment adaptability, providing a reference for research into combined garlic harvesting technology.
Prediction of Anthocyanin Content in Purple-Leaf Lettuce Based on Spectral Features and Optimized Extreme Learning Machine Algorithm
Authors: Liu Chunhui , Yu Haiye , Liu Yucheng , Zhang Lei , Li Dawei , Zhang Junhe , Li Xiaokai , Sui Yuanyuan
Published: December 2024

Monitoring anthocyanins is essential for assessing nutritional value and the growth status of plants. This study aimed to utilize hyperspectral technology to non-destructively monitor anthocyanin levels. Spectral data were preprocessed using standard normal variate (SNV) and first-derivative (FD) spectral processing. Feature wavelengths were selected using uninformative variable elimination (UVE) and UVE combined with competitive adaptive reweighted sampling (UVE + CARS). The optimal two-band vegetation index (VI2) and three-band vegetation index (VI3) were then calculated. Finally, dung beetle optimization (DBO), subtraction-average-based optimization (SABO), and the whale optimization algorithm (WOA) optimized the extreme learning machine (ELM) for modeling. The results indicated the following: (1) For the feature band selection methods, the UVE-CARS-SNV-DBO-ELM model achieved an Rm2 of 0.8623, an RMSEm of 0.0098, an Rv2 of 0.8617, and an RMSEv of 0.0095, resulting in an RPD of 2.7192, further demonstrating that UVE-CARS enhances feature band extraction based on UVE and indicating a strong model performance. (2) For the vegetation index, VI3 showed a better predictive accuracy than VI2. The VI3-WOA-ELM model achieved an Rm2 of 0.8348, an RMSEm of 0.0109 mg/g, an Rv2 of 0.812, an RMSEv of 0.011 mg/g, and an RPD of 2.3323, demonstrating good performance. (3) For the optimization algorithms, the DBO, SABO, and WOA all performed well in optimizing the ELM model. The R2 of the DBO model increased by 5.8% to 27.82%, that of the SABO model by 2.92% to 26.84%, and that of the WOA model by 3.75% to 27.51%. These findings offer valuable insights for future anthocyanin monitoring using hyperspectral technology, highlighting the effectiveness of feature selection and optimization algorithms for accurate detection.
Components of High-Yielding Cotton Grown in Rain-Fed Conditions in the Brazilian Cerrado
Authors: Echer Fábio R. , Galdi Leonardo V. , Silva Gustavo R. A. , Santos Jorge W. S. , Rocha Caroline H. , Cagna Camila P. , Tormena Cássio A. , Silva Igor F. , Atarassi Ricardo
Published: December 2024

Brazil leads globally in achieving high lint yields for rain-fed cotton in large-scale fields, with about 92% of its cotton area unirrigated. This study hypothesized that cotton could achieve high yields when favorable climate conditions and management practices favor high fruit load. The objective was to analyze the impact of these factors on cotton yields by examining two commercial fields in Brazil in the same climatic zone (Aw, Koppen)—one in Sapezal (SPZ) and the other in Riachão das Neves (RN). The SPZ field (cv. TMG 47B2RF) spanned 20 hectares, while the RN field (cv. FM 974GLT) covered 90 hectares. The soils of both fields were classified as oxisols, with SPZ possessing a clayey texture and RN a sandy loam texture. The findings indicate that the high lint cotton yields—3111 kg·ha⁻1 in SPZ and 3239 kg·ha⁻1 in RN—were achieved through a combination of ideal weather conditions, high-quality soil, and effective management practices, which favored boll retention, and an optimal plant architecture with short stature (<1.1 m), 19–22 nodes, and ~165 bolls m−2. Boll weights averaged 1.85–1.91 g of lint, and fruit retention rates were 61.6% in SPZ and 66.2% in RN. The study reveals a significant yield gap compared to Brazil’s average lint cotton yield (~1900 kg·ha⁻1) and other high-yield commercial fields (~3500–3900 kg·ha⁻1 of lint). The results underscore that bridging this gap—ranging from 1200 to 2000 kg·ha⁻1—could enhance the sustainability of cotton farming in Brazil by maximizing existing cultivated areas. Ultimately, the insights from this study highlight the role of combining climate suitability, management practices, and soil quality improvement to achieve higher cotton productivity and reduce environmental pressures from agricultural expansion.
Acute Fatal Gastric Dilatation and Volvulus in a Captive Adult Linnaeus’s Two-Toed Sloth (Choloepus didactylus) in Amazon Biome
Authors: Oliveira Hanna Gabriela da Silva , Lopes Cinthia Távora de Albuquerque , Correa Letícia Yasmin Silva , Thiesen Roberta Martins Crivelaro , Silva Rodrigo Otavio Silveira , Uzal Francisco Alejandro , Domingues Sheyla Farhayldes Souza , Salvarani Felipe Masiero
Published: December 2024

This study aims to report the dietary and daily management, clinical signs, complementary exams, and pathological findings related to an acute and fatal case of gastric dilatation and volvulus (GDV) in a captive Linnaeus’s two-toed sloth (Choloepus didactylus) in the Amazon Biome. An adult female sloth, rescued after being electrocuted, was housed at the Wildlife Section of the Veterinary Hospital (WSVH) of the Institute of Veterinary Medicine (IVM) at the Universidade Federal do Pará (UFPA). It was fed a diverse diet that included animal protein, fruits, vegetables, and greens, with vitamin and mineral supplementation. After five years, the sloth was found in its enclosure hyporesponsive, dehydrated, hypothermic, and hyperventilating, with an abdominal dilation of firm consistency. During emergency care, the animal died. Fecal samples collected two days before death were positive only for Clostridium perfringens type A. Necropsy findings included dilatation of the squamous gastric compartment due to gas accumulation, with necrotic and hemorrhagic mucosa, a 180–270° volvulus obstructing the gastroesophageal region, and intestinal mucosal hyperemia. Histopathology revealed marked congestion with hemorrhage and gastric mucosal necrosis, along with tertiary lymphoid follicles in the submucosa. To the authors’ knowledge, this is the first report of GDV in a sloth in Brazil. Further research is needed to develop appropriate approaches to GDV in captive sloths.
Salmonella and Salmonellosis in Wild Birds
Authors: Wigley Paul
Published: December 2024

Salmonella enterica is an important bacterial pathogen in humans and warm-blooded animals. Wild bird species represent both a potential reservoir for zoonotic infection and as a susceptible host to infection by host-adapted variants. Historically, wild birds were considered to be a major source of Salmonella infection in livestock, but in recent years, it has been more apparent that birds are more likely to act as a reservoir for recycling infection on farms rather than as the primary source of infection. Birds may also transmit infection to humans directly from feces or indirectly through fecal contamination of foods, including peanut butter. While many bird species can be infected with Salmonella, the rates of infection are variable, and most cases lead to intestinal carriage rather than disease. In this case, fecal shedding of Salmonella bacteria from birds can represent a risk for transmission to humans. As such, care is needed when in contact with fecal material such as that found on bird tables or feeders. In recent years, there have been emergences of Salmonella Typhimurium genotypes associated with high mortality in songbirds or passerine birds, resulting in ‘die offs’ in Europe, Israel, New Zealand and the US. Additionally, S. typhimurium DT2 and other variant Copenhagen genotypes are associated with high mortality disease in pigeons. These genotypes show evidence of evolution towards adaptation to specific hosts, with pseudogenes leading to loss of functional metabolic pathways and specific virulence factors. These ‘signatures of adaptation’ are common in host-adapted Salmonella serovars and suggest these S. typhimurium isolates are evolving to adapt to specific avian hosts.
Synthesis and Antibacterial Activity of New 6″-Modified Tobramycin Derivatives
Authors: Shapovalova Kseniya S. , Zatonsky Georgy V. , Razumova Elizaveta A. , Ipatova Daria A. , Lukianov Dmitrii A. , Sergiev Petr V. , Grammatikova Natalia E. , Tikhomirov Alexander S. , Shchekotikhin Andrey E.
Published: December 2024

Objectives: Aminoglycosides are one of the first classes of natural antibiotics which have not lost relevance due to their broad spectrum of action against Gram-positive, Gram-negative bacteria and mycobacteria. The high growth rate of antimicrobial resistance (AMR) together with the severe side effects of aminoglycosides increase the importance of developing improved semisynthetic derivatives. Methods: In this work, we proposed a synthetic route to new tobramycin derivatives modified at the 6″-position with aminoalkylamine or guanidinoalkylamine residues. Results: The antibacterial activity of the new compounds against reference strains of microorganisms was comparable to the parental tobramycin. In striking contrast to tobramycin (resistance index, >256), its 6″-modified derivatives were significantly more potent against resistant clinical isolates of P. aeruginosa strains (resistance index = 4–16) and they demonstrated a promising AMR circumvention in E. coli strains associated with mutations in the fusA gene encoding elongation factor G. All the obtained tobramycin derivatives exhibited reduced cytotoxicity for the eukaryotic HEK293T cells compared to the tobramycin and thereby they potentially may have improved therapeutic index. The proposed modification of the 6″-position of tobramycin does not change the mechanism of aminoglycoside’s antibacterial activity: new compounds induced translation errors which resulted in the inhibition of protein synthesis in bacterial cells. Conclusions: Taken together, we can suggest that further modifications of the 6″-position of tobramycin may be beneficial for circumvention of AMR to aminoglycosides or used for conjugation with other molecules of interest.
Role of Redox Homeostasis in the Communication Between Brain and Liver Through Extracellular Vesicles
Authors: Huete-Acevedo Javier , Mas-Bargues Cristina , Arnal-Forné Marta , Atencia-Rabadán Sandra , Sanz-Ros Jorge , Borrás Consuelo
Published: December 2024

Extracellular vesicles (EVs) are small, membrane-bound particles secreted by cells into the extracellular environment, playing an increasingly recognized role in inter-organ communication and the regulation of various physiological processes. Regarding the redox homeostasis context, EVs play a pivotal role in propagating and mitigating oxidative stress signals across different organs. Cells under oxidative stress release EVs containing signaling molecules that can influence the redox status of distant cells and tissues. EVs are starting to be recognized as contributors to brain-liver communication. Therefore, in this review, we show how redox imbalance can affect the release of EVs in the brain and liver. We propose EVs as mediators of redox homeostasis in the brain-liver axis.
Simplified Scan-vs-BIM Frameworks for Automated Structural Inspection of Steel Structures
Authors: Kim Bohee , Jo Inho , Ham Namhyuk , Kim Jae-jun
Published: December 2024

This paper presents a deep learning-based Scan-vs-BIM methodology for evaluating structural integrity through the extraction of features from As-Built scan and As-Planned Building Information Modeling (BIM) comparison data. Traditional Scan-vs-BIM frameworks often rely on Scan-to-BIM processes to generate point cloud-based mesh models for comparison, which significantly impairs computational efficiency. In contrast, the proposed streamlined Scan-vs-BIM framework incorporates a deep neural network (DNN) model consisting of two neural networks: one for structural integrity assessment and another for error type analysis. The model evaluates the structural integrity of individual components in a sequential manner, repeating the process across all elements to comprehensively assess the entire structure. Rather than converting point cloud data into mesh models for comparison, this approach directly measures the spatial discrepancies between the As-Built point cloud and As-Planned BIM, analyzing the distribution tendencies of these distance values. Experimental validation on actual steel structures demonstrated that the proposed method effectively predicts structural integrity, providing significant improvements in both accuracy and computational performance.
Prediction and Optimization of Surface Roughness and Cutting Forces in Turning Process Using ANN, SHAP Analysis, and Hybrid MCDM Method
Authors: Pasic Mirza , Marinkovic Dejan , Lukic Dejan , Begic-Hajdarevic Derzija , Zivkovic Aleksandar , Milosevic Mijodrag , Muhamedagic Kenan
Published: December 2024

As manufacturing technologies advance, the integration of artificial neural networks in machining high-hardness materials and optimization of multi-objective parameters is becoming increasingly prevalent. By employing modeling and optimization strategies during the machining of such materials, manufacturers can improve surface roughness and tool life while minimizing cutting time, tool vibrations, and cutting forces. In this paper, the aim was to analyze the impact of input parameters (cutting speed, feed rate, depth of cut, and insert radius) on surface roughness and cutting forces during the machining of 90MnCrV7 using feed-forward neural network models and SHAP analysis. Afterward, multi-criteria optimization was applied to determine the optimal parameter levels to achieve minimum surface roughness and cutting forces using the modified PSI-TOPSIS method. According to the SHAP analysis, the insert radius has the most significant impact on the surface roughness and passive force, while in the multi-criteria analysis, according to ANOVA results, the insert radius has the most significant impact on all considered outputs. The results show that an insert radius of 0.8 mm, a cutting speed of 260 m/min, a feed rate of 0.08 mm, and a depth of cut of 0.5 mm are the optimal combination of input parameters.
Comparison of the Degree of Proteolytic Modification in Wheat Malts Obtained from Wheat Grain Produced at Different Nitrogen Fertilization Rates
Authors: Belcar Justyna , Gorzelany Józef
Published: December 2024

The degree of proteolytic modification in wheat malts significantly affects their quality, determining their suitability for use in brewing. Nitrogen fertilization at doses of 60 and 80 kg N·ha−1 applied during 3-year field experiments had a positive effect on the content of protein compounds in the analyzed wheat malts. The total protein content of the malts obtained averaged 9.9–10.1% d. m., depending on the cultivar, and from 9.1 to 10.8% dry matter, depending on nitrogen fertilization. The soluble protein content and Kolbach index value were at similar levels (4.60% dry matter and 46.07%, respectively, on average) except for malt obtained from the Elixer cultivar, for which significantly lower values were obtained (by 7.39% and 6.66%, respectively). In contrast, the highest free amino nitrogen value was obtained for malts derived from the Elixer and Gimantis cultivars. The least variation in the quality of malts derived from grains obtained in the three growing seasons during the field experiments was in the cultivar Gimantis. In 2-year commodity field experiments (in commodity farms), under 60 kg N·ha−1 nitrogen fertilization, the cultivar Lawina was characterized by the best indices of the degree of proteolytic modification.
Improving Vulnerability Management Through Process Mining
Authors: Meyer Christina , Heininger Richard , Stary Christian
Published: December 2024

With the number of cyber-attacks growing rapidly and the opportunities to attack companies widening, vulnerability management is gaining increased importance. It needs to reduce the variety of possibilities by remediating vulnerabilities found in IT infrastructures. Process mining is an established method used to discover, analyze, and manage data on (implemented) business processes. This paper proposes utilizing process mining for business-critical processes, including IT processes. This work explores how vulnerability management processes can be improved through process monitoring, targeting the operation time of processes, remediation, and the continuous management of the vulnerability process design. Thereby, process mining is applied for monitoring following the CRISP data mining approach. Process analysis includes process discovery, conformance checking, and process enhancement. Improving the vulnerability management process is based on the discovered vulnerability process, which is enhanced with throughput time data as well as priority, source, and assignment group data. Improvements concern changing the configuration of a source and better training for certain assignment groups. Process discovery can also be used to identify the cause for improper remediation of vulnerabilities. In this case, unwanted activity flows, which indicate that a major part of the vulnerability management process is being skipped, need to be identified. Finally, the continuous use of process mining allows for the monitoring of process modifications, including the impact of implemented improvements.
Lithium-Ion Battery Life Prediction Using Deep Transfer Learning
Authors: Zhang Wen , Pranav R. S. B. , Wang Rui , Lee Cheonghwan , Zeng Jie , Cho Migyung , Shim Jaesool
Published: December 2024

Lithium-ion batteries are critical components of various advanced devices, including electric vehicles, drones, and medical equipment. However, their performance degrades over time, and unexpected failures or discharges can lead to abrupt operational interruptions. Therefore, accurate prediction of the remaining useful life is essential to ensure device safety and reliability. Conventional RUL prediction methods typically rely on regression analysis, signal processing, and machine learning techniques to assess battery conditions such as charge/discharge cycles, voltage, temperature, and durability. Although effective, these approaches are constrained by their dependence on large amounts of labeled data and the necessity for complex feature engineering to capture battery physical characteristics. In this study, we propose an approach that employs deep transfer learning to address these limitations. By leveraging pretrained model weights, the proposed method significantly improves the efficiency and accuracy of RUL prediction even under limited training data conditions. Furthermore, we investigate the impact of external environmental factors and physical battery characteristics on RUL prediction precision, thereby contributing to a more robust and reliable prediction framework.
eFC-Evolving Fuzzy Classifier with Incremental Clustering Algorithm Based on Samples Mean Value
Authors: Tavares Emmanuel , Moita Gray Farias , Silva Alisson Marques
Published: December 2024

This paper introduces a new multiclass classifier called the evolving Fuzzy Classifier (eFC). Starting its knowledge base from scratch, the eFC structure evolves based on a clustering algorithm that can add, merge, delete, or update clusters (= rules) simultaneously while providing class predictions. The procedure to add clusters uses the procrastination idea to prevent outliers from affecting the quality of learning. Two pruning mechanisms are used to maintain a concise and compact structure. In the first, redundant clusters are merged based on a similarity measure, and in the second, obsolete and unrepresentative clusters are excluded based on an inactivity strategy. The center of the clusters is adjusted based on the mean value of the attributes. The eFC model was evaluated and compared with state-of-the-art evolving fuzzy systems on 8 randomly selected data streams from the UCI and Kaggle repositories. The experimental results indicate that the eFC outperforms or is at least comparable to alternative state-of-the-art models. Specifically, the eFC achieved an average accuracy of 7% to 37% higher than the competing classifiers. The results and comparisons demonstrate that the eFC is a promising alternative for classification tasks in non-stationary environments, offering good accuracy, a compact structure, low computational cost, and efficient processing time.
Spatial Transcriptomics, Proteomics, and Epigenomics as Tools in Tissue Engineering and Regenerative Medicine
Authors: Lammi Mikko J. , Qu Chengjuan
Published: December 2024

Spatial transcriptomics, proteomics, and epigenomics are innovative technologies which offer an unparalleled resolution and wealth of data in understanding and the interpretation of cellular functions and interactions. These techniques allow researchers to investigate gene and protein expressions at an individual cell level, revealing cellular heterogeneity within, for instance, bioengineered tissues and classifying novel and rare cell populations that could be essential for the function of the tissues and in disease processes. It is possible to analyze thousands of cells simultaneously, which gives thorough insights into the transcriptomic view of complex tissues. Spatial transcriptomics combines gene expressions with spatial information, conserving tissue architecture and making the mapping of gene activity across different tissue regions possible. Despite recent advancements in these technologies, they face certain limitations. Single-cell transcriptomics can suffer from technical noise and dropout events, leading to incomplete data. Its applicability has been limited by the complexity of data integration and interpretation, although better resolution and tools for the interpretation of data are developing fast. Spatial proteomics and spatial epigenomics provide data on the distribution of proteins and the gene regulatory aspects in tissues, respectively. The disadvantages of these approaches include rather costly and time-consuming analyses. Nevertheless, combining these techniques promises a more comprehensive understanding of cell function and tissue organization, which can be predicted to be useful in achieving better knowledge of cell guidance in tissue-engineered constructs and a higher quality of tissue technology products.
Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomography Images
Authors: Pennati Diletta , Bocchi Leonardo
Published: December 2024

Image registration is a crucial post-processing technique in biomedical imaging, enabling the alignment and integration of images from various sources to facilitate accurate diagnosis, treatment planning, and longitudinal studies. This paper explores the application of Scale Invariant Feature Transform (SIFT), a robust feature-based method for the alignment of biomedical images. SIFT is particularly advantageous due to its invariance to scale, rotation, and affine transformations, making it well-suited for handling the diverse and complex nature of biomedical images. However, SIFT was not initially developed specifically for medical imaging applications, so it is necessary to adapt the algorithm to those kinds of images. In particular, this work was focused on images obtained with Cone-Beam Computed Tomography (CBCT) technology. Besides fine-tuning SIFT parameters on a case-by-case basis, the novelty of this work consists of finding the optimal SIFT parameters on the basis of the keypoints stability. A statistical analysis throughout a dataset of images obtained with CBCT technology was performed to find the best SIFT parameters setting, in terms of computational cost and result quality, compared to default presets.
Intelligibility Sound Therapy Enhances the Ability of Speech-in-Noise Perception and Pre-Perceptual Neurophysiological Response
Authors: Ishino Takashi , Nakagawa Kei , Higashikawa Fumiko , Hirokane Sakura , Fujita Rikuto , Ishikawa Chie , Kawasumi Tomohiro , Takemoto Kota , Oda Takashi , Nishida Manabu , Horibe Yuichiro , Chikuie Nobuyuki , Taruya Takayuki , Hamamoto Takao , Ueda Tsutomu , Yuge Louis , Takeno Sachio
Published: December 2024

Aural rehabilitation with hearing aids can decrease the attentional requirements of cognitive resources by amplifying deteriorated-frequency sound in hearing loss patients and improving auditory discrimination ability like speech-in-noise perception. As aural rehabilitation with an intelligible-hearing sound also can be hopeful, the aim of this study was to evaluate the effectiveness of aural rehabilitation with intelligible-hearing sound for hearing loss patients. Adult native Japanese speakers (17 males and 23 females, 68.43 ± 9.23 years) with hearing thresholds exceeding 30 dB at any of the following frequencies: 125, 250, 500, 1000, 2000, 3000, 4000, 8000, 10,000, and 12,000 Hz in either ear, were recruited. on any side were recruited and underwent the Mini-Mental State Examination Japanese. We conducted a self-evaluation questionnaire for hearing problems of voice, a gap detection test, a fast speech test, a speech-in-noise test, a pure tone audiogram, and a speech perception test using a Japanese 67-S, cortical auditory-evoked fields, and magnetic mismatch negativity before and after the non-intelligible-hearing (N = 20) and intelligible-hearing (N = 20) sound therapy, which involved listening to music for one hour a day for 35 days. The better hearing ear was defined using a four-frequency pure-tone average at the thresholds of 500, 1000, 2000, and 4000 Hz. After the sound therapy, the speech-in-noise test with a signal-to-noise ratio +10 in the better hearing ear showed significant improvement (p < 0.05), and N1m-P2m amplitudes showed a significant increase in the Lt superior temporal gyrus in response to the stimulus from the better hearing ear (p < 0.05). A significant enhancement of the magnetic mismatch negativity amplitude at the Lt superior temporal gyrus was exhibited after the sound therapy (p < 0.01). Intelligible-hearing sound therapy can improve the ability of speech-in-noise perception in the better hearing ear and enhancement of central cortex response, which reflects the ability of working memory, was proved by cortical auditory-evoked fields and magnetic mismatch negativity. Intelligible-hearing sound therapy can be a valuable aural rehabilitation method for sensory neural hearing loss, the same as hearing aids.
Microbiota and Cytokine Modulation: Innovations in Enhancing Anticancer Immunity and Personalized Cancer Therapies
Authors: Farhadi Rad Hamidreza , Tahmasebi Hamed , Javani Samaneh , Hemati Maral , Zakerhamidi Darya , Hosseini Masoomeh , Alibabaei Farnaz , Banihashemian Seyedeh Zahra , Oksenych Valentyn , Eslami Majid
Published: December 2024

The gut microbiota plays a crucial role in modulating anticancer immunity, significantly impacting the effectiveness of various cancer therapies, including immunotherapy, chemotherapy, and radiotherapy. Its impact on the development of cancer is complex; certain bacteria, like Fusobacterium nucleatum and Bacteroides fragilis, can stimulate the growth of tumors by causing immunological evasion and inflammation, while advantageous strains, like Faecalibaculum rodentium, have the ability to suppress tumors by modifying immune responses. Cytokine activity and immune system regulation are intimately related. Cytokines including TGF-β, IL-6, and IL-10 promote tumor development by inhibiting efficient immune surveillance. The gut microbiome exhibits a delicate balance between pro- and anti-tumorigenic factors, as evidenced by the enhancement of anti-tumor immunity by cytokines such as IL-12 and IFN-γ. Improved immunotherapy responses are linked to a diverse microbiota, which is correlated with higher tumor infiltration and cytotoxic T-cell activation. Because microbial metabolites, especially short-chain fatty acids, affect cytokine expression and immune cell activation inside the tumor microenvironment, this link highlights the need to maintain microbial balance for optimal treatment effects. Additionally, through stimulating T-cell activation, bacteria like Lactobacillus rhamnosus and Bifidobacterium bifidum increase cytokine production and improve the efficacy of immune checkpoint inhibitors (ICIs). An option for overcoming ICI resistance is fecal microbiota transplantation (FMT), since research suggests that it improves melanoma outcomes by increasing CD8+ T-cell activation. This complex interaction provides an opportunity for novel cancer therapies by highlighting the possibility of microbiome modification as a therapeutic approach in personalized oncology approaches.
Gut Microbiota, Bacterial Translocation, and Stroke: Current Knowledge and Future Directions
Authors: Granados-Martinez Cristina , Alfageme-Lopez Nuria , Navarro-Oviedo Manuel , Nieto-Vaquero Carmen , Cuartero Maria Isabel , Diaz-Benito Blanca , Moro Maria Angeles , Lizasoain Ignacio , Hernandez-Jimenez Macarena , Pradillo Jesus Miguel
Published: December 2024

Stroke is one of the most devastating pathologies in terms of mortality, cause of dementia, major adult disability, and socioeconomic burden worldwide. Despite its severity, treatment options remain limited, with no pharmacological therapies available for hemorrhagic stroke (HS) and only fibrinolytic therapy or mechanical thrombectomy for ischemic stroke (IS). In the pathophysiology of stroke, after the acute phase, many patients develop systemic immunosuppression, which, combined with neurological dysfunction and hospital management, leads to the onset of stroke-associated infections (SAIs). These infections worsen prognosis and increase mortality. Recent evidence, particularly from experimental studies, has highlighted alterations in the microbiota–gut–brain axis (MGBA) following stroke, which ultimately disrupts the gut flora and increases intestinal permeability. These changes can result in bacterial translocation (BT) from the gut to sterile organs, further contributing to the development of SAIs. Given the novelty and significance of these processes, especially the role of BT in the development of SAIs, this review summarizes the latest advances in understanding these phenomena and discusses potential therapeutic strategies to mitigate them, ultimately reducing post-stroke complications and improving treatment outcomes.
The Influence of Key Dimensions of the Swivel Hinge on the Mechanical Performance of Bridge Rotary Structure
Authors: Wu Hantao , Yang Zheng , Lu Chunting , Li Zhongming , Guo Chen , Sha Guohua
Published: December 2024

To assess the influence of the spherical and supporting radius of swivel hinges on the anti-overturning capability of T-structures and the safety of lower turntables, this study focuses on large-tonnage rotary bridges spanning the South-to-North Water Diversion Project along the Jiaozuo to Tanghe Expressway. The research involved theoretical analysis and numerical simulations to evaluate the stability of the rotary structures and the load-bearing capacity of rotary platforms with varying spherical and supporting radii, and we generated 15 numerical models. The results indicate that the critical eccentricity for T-structure anti-overturning increases with larger supporting and spherical radii, with diminishing returns as the supporting radius decreases. The critical eccentricity for spherical hinges is consistently lower than that seen for flat hinges. The lower turntable’s failure characteristics divide it into four zones, as follows: main compressive stress failure at the bottom under the hinge, main tensile stress failure at the top around the hinge, and two other regions less prone to failure. The supporting radius significantly influences compressive and tensile stress failures, while the spherical radius mainly affects the tensile stress area. These results offer insights for the design and construction of large-tonnage rotational bridges.
Exploring Raw Red Clay as a Supplementary Cementitious Material: Composition, Thermo-Mechanical Performance, Cost, and Environmental Impact
Authors: Drissi Mohammed , Horma Othmane , Mezrhab Ahmed , Karkri Mustapha
Published: December 2024

This study explored the potential of natural red clay as a supplementary cementitious material (SCM) to reduce greenhouse gas emissions and costs associated with the cement industry. Given that cement production is one of the largest contributors to global greenhouse gas emissions, developing sustainable alternatives is of paramount importance. Recognizing the environmental impact of cement production, this research investigates the substitution of conventional cement with raw red clay, aiming to balance mechanical performance with enhanced thermal properties and a lower environmental footprint. Through chemical characterization using X-ray Fluorescence (XRF), along with comprehensive mechanical and thermal performance testing, this study identifies the dual role of raw clay in mortar. It was found that incorporating up to 5% by weight of raw clay slightly impacted compressive strength while significantly improving thermal conductivity and diffusivity, cost-efficiency, and environmental sustainability, making it an appealing option for structural applications requiring high mechanical resistance. Conversely, a higher proportion of clay (beyond 5%) compromises compressive strength, but further enhances thermal properties and environmental benefits, suggesting its suitability for applications where low mechanical resistance is acceptable. This investigation highlights the viability of raw clay as a promising SCM, offering a pathway to more sustainable construction materials without the need for energy-intensive processing, thereby contributing to the reduction in the construction sector’s carbon footprint and energy demand.
Emerging Non-Breast Implant-Associated Lymphomas: A Systematic Review
Authors: Di Napoli Arianna , Fruscione Santo , Mazzola Sergio , Amodio Rosalba , Graziano Giorgio , Mannino Rita , Zarcone Maurizio , Bertolazzi Giorgio , Bonaccorso Nicole , Sciortino Martina , De Bella Daniele Domenico , Savatteri Alessandra , Belluzzo Miriam , Norrito Chiara Alba , Sparacino Rosario , Contiero Paolo , Tagliabue Giovanna , Costantino Claudio , Mazzucco Walter
Published: December 2024

Background: Medical devices used for functional or esthetic purposes improve health and quality of life; however, they are not risk-free. Anaplastic large-cell lymphoma (ALCL), associated with breast implants, is a well-known and recognized distinct lymphoma entity. More recently, additional lymphomas have been reported in relation to prosthesis other than breast implants, as these allow the pericyte to develop into a clone that undergoes a maturation process, progressing toward full malignancy. Methods: We performed a systematic review with a descriptive analysis of data extracted from primary studies following PRISMA guidelines, including the search string “(IMPLANT* OR PROSTHES*) AND LYMPHOM*” in the PubMed, Scopus, Embase, and Google-Scholar databases. Data such as patient sex, age, implant site, prosthesis material, and lymphoma type were analyzed. Statistical methods, including Student’s t-test and Fisher’s exact test, were employed to compare lymphoma characteristics, with significance set at a p-value < 0.05. Results: From a total of 5992 studies, we obtained 43 case reports and series on a total of 52 patients diagnosed with prosthesis-associated lymphomas. The majority of implant-related lymphoma cases (85%) were of the B-cell type, mostly fibrin-associated large B-cell lymphoma (LBCL). This lymphoma type was more associated with biological (non-human-derived biological tissue), metallic, and synthetic implants (synthesized from non-organic components) (p-value = 0.007). Patients with ALCL had equal frequencies of metal and silicone prostheses (37.5%, 3 cases each), followed by synthetic prostheses (25%, 2 cases). ALCL cases were most common at skeletal (50%) and muscular-cutaneous sites (25%), whereas B-cell lymphomas were predominantly found in cardiovascular implants (50%), followed by skeletal (27%) and muscular-cutaneous (21%) sites. Death attributed to lymphoma took place in 67% of the cases, mostly LBCL occurring in cardiovascular sites. Conclusions: Because the included studies were limited to case reports and series, a potential non-causal link might have been documented between different implant materials, implant sites and lymphoma types. This underscores the importance of further comprehensive research and monitoring of non-breast implants.
Spino-Plastic Surgery: Addressing Spinal Tumors with New Techniques
Authors: Martinez Casey , Abdulwadood Isra , Winocour Sebastian , Ropper Alexander E. , Innocenti Marco , Bohl Michael , Kalani Maziyar , Reece Edward M.
Published: December 2024

Background/Objectives: Spino-plastic surgery describes a specialized, multidisciplinary approach to addressing various spinal pathologies. The field is the innovative product of a multidisciplinary collaboration between plastic and reconstructive, orthopedic, and neurosurgery. Over the last few decades, this collaboration has borne promising surgical techniques and treatment plans geared toward restoring form, function, and aesthetics in patients with a variety of spinal conditions, including failed fusions, pseudoarthrosis, and the need for oncologic reconstruction. This paper explores the application of spino-plastic surgery in the context of post-sarcoma resection reconstructions, focusing on the efficacy in addressing the unique challenges posed by extensive tissue loss and structural deformities. Methods: Our study reviews a series of cases wherein spino-plastic techniques were utilized in patients with sarcomas of the spine and adjacent structures. We also discuss the technical considerations, including preoperative planning, intraoperative challenges, and overall patient care, that are crucial for the success of spino-plastic procedures. Results: The outcomes demonstrate significant improvements in patient mobility, pain reduction, and overall quality of life. Most notably, spino-plastic surgical techniques help facilitate the restoration of functional anatomy by leveraging vascularized bone grafts and muscle flaps, thereby enhancing long-term stability and reducing the risk of complications such as nonunion or infection. Conclusions: Spino-plastic collaboration represents a pivotal advancement in oncologic treatment, spinal care, and reconstructive surgery, offering new hope for patients undergoing post-sarcoma reconstruction. Further research and refinement of the techniques will only expand their application and improve outcomes for a broader range of patients in the future.