bluuebunny/crossref_metadata_2025 huggingface dataset:
The Metabolomic Footprint of Liver Fibrosis
Authors: Beyoğlu Diren , Popov Yury V. , Idle Jeffrey R.
Published: August 2024

Both experimental and clinical liver fibrosis leave a metabolic footprint that can be uncovered and defined using metabolomic approaches. Metabolomics combines pattern recognition algorithms with analytical chemistry, in particular, 1H and 13C nuclear magnetic resonance spectroscopy (NMR), gas chromatography–mass spectrometry (GC–MS) and various liquid chromatography–mass spectrometry (LC–MS) platforms. The analysis of liver fibrosis by each of these methodologies is reviewed separately. Surprisingly, there was little general agreement between studies within each of these three groups and also between groups. The metabolomic footprint determined by NMR (two or more hits between studies) comprised elevated lactate, acetate, choline, 3-hydroxybutyrate, glucose, histidine, methionine, glutamine, phenylalanine, tyrosine and citrate. For GC–MS, succinate, fumarate, malate, ascorbate, glutamate, glycine, serine and, in agreement with NMR, glutamine, phenylalanine, tyrosine and citrate were delineated. For LC–MS, only β-muricholic acid, tryptophan, acylcarnitine, p-cresol, valine and, in agreement with NMR, phosphocholine were identified. The metabolomic footprint of liver fibrosis was upregulated as regards glutamine, phenylalanine, tyrosine, citrate and phosphocholine. Several investigators employed traditional Chinese medicine (TCM) treatments to reverse experimental liver fibrosis, and a commentary is given on the chemical constituents that may possess fibrolytic activity. It is proposed that molecular docking procedures using these TCM constituents may lead to novel therapies for liver fibrosis affecting at least one-in-twenty persons globally, for which there is currently no pharmaceutical cure. This in-depth review summarizes the relevant literature on metabolomics and its implications in addressing the clinical problem of liver fibrosis, cirrhosis and its sequelae.
Cancer-Associated-Fibroblast-Mediated Paracrine and Autocrine SDF-1/CXCR4 Signaling Promotes Stemness and Aggressiveness of Colorectal Cancers
Authors: Chen Chao-Yang , Yang Shih-Hsien , Chang Ping-Ying , Chen Su-Feng , Nieh Shin , Huang Wen-Yen , Lin Yu-Chun , Lee Oscar Kuang-Sheng
Published: August 2024

Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide, and cancer-associated fibroblasts (CAFs) play a major role in the tumor microenvironment (TME), which facilitates the progression of CRC. It is critical to understand how CAFs promote the progression of CRC for the development of novel therapeutic approaches. The purpose of this study was to understand how CAF-derived stromal-derived factor-1 (SDF-1) and its interactions with the corresponding C-X-C motif chemokine receptor 4 (CXCR4) promote CRC progression. Our study focused on their roles in promoting tumor cell migration and invasion and their effects on the characteristics of cancer stem cells (CSCs), which ultimately impact patient outcomes. Here, using in vivo approaches and clinical histological samples, we analyzed the influence of secreted SDF-1 on CRC progression, especially in terms of tumor cell behavior and stemness. We demonstrated that CAF-secreted SDF-1 significantly enhanced CRC cell migration and invasion through paracrine signaling. In addition, the overexpression of SDF-1 in CRC cell lines HT29 and HCT-116 triggered these cells to generate autocrine SDF-1 signaling, which further enhanced their CSC characteristics, including those of migration, invasion, and spheroid formation. An immunohistochemical study showed a close relationship between SDF-1 and CXCR4 expression in CRC tissue, and this significantly affected patient outcomes. The administration of AMD3100, an inhibitor of CXCR4, reversed the entire phenomenon. Our results strongly suggest that targeting this signaling axis in CRC is a feasible approach to attenuating tumor progression, and it may, therefore, serve as an alternative treatment method to improve the prognosis of patients with CRC, especially those with advanced, recurrent, or metastatic CRC following standard therapy.
Extracellular Vesicle Transplantation Is Beneficial for Acute Kidney Injury
Authors: Salybekov Amankeldi A. , Okamura Shigeaki , Ohtake Takayasu , Hidaka Sumi , Asahara Takayuki , Kobayashi Shuzo
Published: August 2024

Under vasculogenic conditioning, certain pro-inflammatory subsets within peripheral blood mononuclear cells (PBMCs) undergo phenotypic transformation into pro-regenerative types, such as vasculogenic endothelial progenitor cells, M2 macrophages, and regulatory T cells. These transformed cells are collectively termed regeneration-associated cells (RACs). In this study, we aimed to investigate the therapeutic efficacy of RAC-derived extracellular vesicles (RACev) compared with a vehicle-treated group in the context of renal ischemia-reperfusion injury (R-IRI). Human PBMCs were cultured with defined growth factor cocktails for seven days to harvest RACs. EV quantity and size were characterized by nanoparticle tracking analysis. Notably, the systemic injection of RACev significantly decreased serum creatinine and blood urine nitrogen at day three compared to the control group. Histologically, the treatment group showed less fibrosis in the cortex and medullary areas (p < 0.04 and p < 0.01) compared to the control group. The CD31 staining confirmed enhanced capillary densities in the treatment group compared to the control group (p < 0.003). These beneficial effects were accompanied by angiogenesis, anti-fibrosis, anti-inflammation, and anti-apoptosis RACev miR delivery to ischemic injury to control inflammatory, endothelial mesenchymal transition, and hypoxia pathways. In vivo bioluminescence analysis demonstrated a preferential accumulation of RACev in the IR-injured kidney. The systemic transplantation of RACev beneficially restored kidney function by protecting from tissue fibrosis and through anti-inflammation, angiogenesis, and anti-apoptosis miR delivery to the ischemic tissue.
The Effect of Loading W&V:TiO2 Nanoparticles with Noble Metals for CH4 Detection
Authors: Scarisoreanu Monica , Constantinoiu Izabela , Goncearenco Evghenii , Morjan Iuliana P. , Teodorescu Valentin Serban , Viespe Cristian
Published: August 2024

TiO2 nanoparticles (NPs) doped with W (W:TiO2), double-doped with W and V (W&V:TiO2), and loaded with noble metals (W:TiO2 @Pt/Pd/Ag and W&V:TiO2@Pt/Pd/Ag) were synthesized by laser pyrolysis followed by chemical impregnation and reduction. Due to its exceptional properties, TiO2 is considered a key material being used in a wide range of applications. To improve its detection activity, the increase in the specific surface of the material, and the presence of defects in its structure play a decisive role. Doped and double-doped TiO2 nanoparticles with dimensions in the range of 25–30 nm presented a mixture of phases corresponding to titania, with the anatase phase accounting for the majority (95%). By loading these nanoparticles with small particles of noble metals, a significant increase in the specific surface area by three or even five times the original values was achieved. Sensitive thin films for surface acoustic wave (SAW) sensors were made with the NPs, embedded in polyethyleneimine (PEI) polymer and deposited by spin-coating. Each sensor was tested at CH4 concentrations between 0.4 and 2%, at room temperature, and the best results were obtained by the sensor with NPs doped with V and decorated with Pd, with a limit of detection (LOD) of 17 ppm, due to the strong catalytic effect of Pd.
Advanced Forecasting of Drought Zones in Canada Using Deep Learning and CMIP6 Projections
Authors: Soltani Keyvan , Amiri Afshin , Ebtehaj Isa , Cheshmehghasabani Hanieh , Fazeli Sina , Gumiere Silvio José , Bonakdari Hossein
Published: August 2024

This study addresses the critical issue of drought zoning in Canada using advanced deep learning techniques. Drought, exacerbated by climate change, significantly affects ecosystems, agriculture, and water resources. Canadian Drought Monitor (CDM) data provided by the Canadian government and ERA5-Land daily data were utilized to generate a comprehensive time series of mean monthly precipitation and air temperature for 199 sample locations in Canada from 1979 to 2023. These data were processed in the Google Earth Engine (GEE) environment and used to develop a Convolutional Neural Network (CNN) model to estimate CDM values, thereby filling gaps in historical drought data. The CanESM5 climate model, as assessed in the IPCC Sixth Assessment Report, was employed under four climate change scenarios to predict future drought conditions. Our CNN model forecasts CDM values up to 2100, enabling accurate drought zoning. The results reveal significant trends in temperature changes, indicating areas most vulnerable to future droughts, while precipitation shows a slow increasing trend. Our analysis indicates that under extreme climate scenarios, certain regions may experience a significant increase in the frequency and severity of droughts, necessitating proactive planning and mitigation strategies. These findings are critical for policymakers and stakeholders in designing effective drought management and adaptation programs.
Effect of Trace Elements on the Thermal Stability and Electrical Conductivity of Pure Copper
Authors: Liu Haitao , Dong Jincan , Liang Shijun , Li Weiqiang , Liu Yong
Published: August 2024

The impact of introducing trace transition elements on the thermal stability and conductivity of pure copper was examined through metallographic microscopy (OM), transmission electron microscopy (TEM), and electrical conductivity measurements; the interaction between trace transition element and trace impurity element S in the matrix was analyzed. The results show that the addition of trace Ti and trace Cr, Ni, and Ag elements significantly enhances the thermal stability of the pure copper grain size. After high-temperature treatment at 900 °C/30 min, the grain sizes of Cu, Cu-Ti-S, and Cu-Cr-Ni-Ag-S were measured and found to be 200.24 μm, 83.83 μm, and 31.08 μm, respectively, thus establishing a thermal stability ranking of Cu-Cr-Ni-Ag-S > Cu-Ti-S > Cu. Furthermore, the conductivities of pure copper remain high even after the addition of trace transition elements, with recorded values for Cu, Cu-Ti-S, and Cu-Cr-Ni-Ag-S of 100.7% IACS, 100.2% IACS, and 98.5% IACS, respectively. The enhancement of thermal stability is primarily attributed to the pinning effect of the TiS and CrS phases, as well as the solid solution dragging of Ni and Ag elements. Trace Ti and Cr elements can react with S impurities to form a hexagonal-structure TiS phase and monoclinic-structure CrS phase, which are non-coherent with the matrix. Notably, the CrS phase is smaller than the TiS phase. In addition, the precipitation of these compounds also reduces the scattering of free electrons by solute atoms, thereby minimizing their impact on the alloy’s conductivity.
Analysis of Decorative Paintings in the Dragon and Tiger Hall of Yuzhen Palace: Culture, Materials, and Technology
Authors: Zhu Yuhua , Qi Guodong , Guo Yingmei , Wang Dongmin
Published: August 2024

Yuzhen Palace in Wudang Mountain, established in the 10th year of the Yongle reign of the Ming dynasty (1412 AD), is a significant heritage site within the ancient architectural complex of Wudang Mountain, recognized as a UNESCO World Heritage Site. Despite being entirely relocated, the original paintings on the wooden beams of the Dragon and Tiger Hall exhibit clear characteristics of early Ming dynasty style, potentially being the only surviving wooden painted structures from the Ming dynasty in Wudang Mountain. To protect these valuable cultural relics and provide accurate information regarding the construction period of the paintings, this study sampled the paintings from the central and western sections of the front eaves in the Dragon and Tiger Hall. Using optical microscopy, scanning electron microscopy (SEM), Raman spectroscopy, and infrared spectroscopy, the study analyzed the stylistic features, material composition, and craftsmanship of the paintings. The results indicate that the paintings are typical official Xuanzi paintings from the early Ming dynasty, consistent with the style of the Golden Roof in Taihe Palace, Wudang Mountain. The pigments used are all natural minerals: azurite (2CuCO3·Cu(OH)2) for blue, malachite (CuCO3·Cu(OH)2) for green, and vermilion (HgS) and hematite (Fe2O3) for red, reflecting typical early Ming dynasty characteristics. The craftsmanship shows that the paintings were applied directly onto the wooden components without a ground layer, using ink lines to outline the images, and a thin ground layer made of tung oil mixed with lime was applied under the oil coating. This study provides scientific material analysis and data support for the subsequent protection and restoration of the Yuzhen Palace architectural complex, ensuring the preservation of these historically and artistically significant relics for future generations.
Effect of Sulfuric Acid Immersion on Electrical Insulation and Surface Composition of Amorphous Carbon Films
Authors: Kanasugi Kazuya , Ichijo Eito , Hiratsuka Masanori , Hirakuri Kenji
Published: August 2024

Sulfuric acid is a concern for contacts within electronic devices, and the application of amorphous carbon films as thin electrical insulating coatings for small coils requires full investigation of its effects. Five types of amorphous carbon films were fabricated on Si substrates under different deposition conditions using vacuum coating systems. Based on their optical constants (ISO 23216:2021(E)), the films were classified into three types: hydrogenated amorphous carbon (a-C:H), polymer-like carbon (PLC), and graphite-like carbon (GLC). The structure, surface composition, and electrical insulation properties of the films were evaluated before and after immersion in sulfuric acid. Although the PLC and a-C:H showed progression of surface oxidation due to sulfuric acid immersion, none showed obvious changes in their structure or DC dielectric breakdown field strength due to sulfuric acid immersion, proving their stability. Furthermore, the PLC and a-C:H, which had a relatively low extinction coefficient, exhibited excellent insulation properties. Our results suggest that amorphous carbon films can be useful as thin insulating films for small coils that may come in contact with sulfuric acid. Our study offers a valuable tool for general users in the industry to facilitate selection of electrical insulating amorphous carbon films based on optical constants, such as extinction coefficients.
Defect Control of Donor Doping on Dielectric Ceramics to Improve the Colossal Permittivity and Temperature Stability
Authors: Wang Wei , Fan Tingting , Hu Songxiang , Zhang Jinli , Zou Xuefeng , Yang Ying , Dou Zhanming , Zhou Lin , Hu Jun , Wang Jing , Jiang Shenglin
Published: August 2024

As the demand for miniaturization of electronic devices increases, ceramics with an ABO3 structure require further improvement of the dielectric constant with high permittivity. In the present work, Ba1−1.5xBixTiO3 (BB100xT, x = 0.0025, 0.005, 0.0075, 0.01) ceramics were prepared via a solid-state reaction process. The effect of Bi doping on dielectric properties of lead-free relaxor ferroelectric BaTiO3-based ceramics was studied. The results showed that both colossal permittivity (37,174) and a temperature stability of TCC ≤ ±15% (−27–141 °C) were achieved in BB100xT ceramics at x = 0.5%. The A-site donor doping produces A-site vacancies, a larger space for Ti4+, and fluctuation of the component, which is partially responsible for the high permittivity and responsible for the temperature stability. Meanwhile, the contribution of defect dipoles, and IBLC and SBLC effects to polarization leads to the colossal permittivity. The formation of a liquid phase during sintering promotes mass transfer when the doping content is higher than 0.5%. This work benefits the exploration of novel multilayer ceramic capacitors with colossal permittivity and temperature stability via defect engineering.
Hypoxia-Regulated Proteins: Expression in Endometrial Cancer and Their Association with Clinicopathologic Features
Authors: Song Dae Hyun , Jo Jae Yoon , Kim Cho Hee , Kim Min Hye , Cho In Ae , Shin Jeong Kyu , Choi Won Jun , Baek Jong Chul
Published: August 2024

Background: Hypoxia-regulated proteins (HIF-1α and GLUT-1) have been identified as prognostic markers in various cancers; however, their role in endometrial cancer remains unclear. This study aimed to evaluate HIF-1α and GLUT-1 expression in endometrial cancer and correlate their expression with clinicopathological features. Materials and Methods: A tissue microarray (TMA) was constructed using specimens from a retrospective cohort of 51 endometrial cancer patients who underwent hysterectomy at the Gyeongsang National University Hospital between 2002 and 2009. Clinicopathologic data were collected from electronic medical records, and HIF-1α and GLUT-1 expressions were assessed in the tumor tissue. Results: GLUT-1 expression in endometrial cancer was categorized as mosaic, central, or diffuse. Most patients (56.0%) exhibited a central pattern, followed by diffuse (32.0%) and mosaic (12.0%) patterns. GLUT-1 expression was not significantly associated with histologic grade (p = 0.365). HIF-1α expression in immune cells, but not tumor cells, was significantly associated with a higher histologic grade. A higher proportion of HIF-1α-positive immune cells, using both thresholds (≤1% vs. >1% and ≤5% vs. >5%), was significantly associated with higher histologic grade (p = 0.032 and p = 0.048, respectively). In addition, a higher proportion of HIF-1α-positive immune cells was significantly associated with a diffuse GLUT-1 expression pattern using >5% as a threshold. There were no significant differences in the proportion of HIF-1α-positive immune cells between groups stratified by age, tumor size, or invasion depth, regardless of whether the 1% or 5% threshold for HIF-1α positivity was used. Conclusions: A higher proportion of HIF-1α-positive immune cells is associated with endometrial cancers with higher histologic grade and diffuse GLUT1 expression patterns. These findings suggest a potential role for HIF-1α as a prognostic marker and highlight the need for further studies into the role of HIF-1α in the tumor microenvironment.
Predicting Complete Cytoreduction with Preoperative [18F]FDG PET/CT in Patients with Ovarian Cancer: A Systematic Review and Meta-Analysis
Authors: Csikos Csaba , Czina Péter , Molnár Szabolcs , Kovács Anna Rebeka , Garai Ildikó , Krasznai Zoárd Tibor
Published: August 2024

The cornerstone of ovarian cancer treatment is complete surgical cytoreduction. The gold-standard option in the absence of extra-abdominal metastases and intra-abdominal inoperable circumstances is primary cytoreductive surgery (CRS). However, achieving complete cytoreduction is challenging, and only possible in a selected patient population. Preoperative imaging modalities such as [18F]FDG PET/CT could be useful in patient selection for cytoreductive surgery. In our systematic review and meta-analysis, we aimed to evaluate the role of preoperative [18F]FDG PET/CT in predicting complete cytoreduction in primary and secondary debulking surgeries. Publications were pooled from two databases (PubMed, Mendeley) with predefined keywords “(ovarian cancer) AND (FDG OR PET) AND (cytoreductive surgery)”. The quality of the included studies was assessed with the Prediction model Risk Of Bias Assessment Tool (PROBAST). During statistical analysis, MetaDiSc 1.4 software and the DerSimonian–Laird method (random effects models) were used. Primary and secondary cytoreductive surgeries were evaluated. Pooled sensitivities, specificities, positive predictive values (PPVs), and negative predictive values (NPVs) were calculated and statistically analyzed. Results were presented in forest plot diagrams and summary receiver operating characteristic (SROC) curves. Overall, eight publications were included in our meta-analysis. Four publications presented results of primary, three presented results of secondary cytoreductions, and two presented data related to both primary and secondary surgery. Pooled sensitivities, specificities, and positive and negative predictive values were the following: in the case of primary surgeries: 0.65 (95% CI 0.60–0.71), 0.73 (95% CI 0.66–0.80), 0.82 (95% CI 0.77–0.87), 0.52 (95% CI 0.46–0.59); and in the case of secondary surgeries: 0.91 (95% CI 0.84–0.95), 0.48 (95% CI 0.30–0.67), 0.88 (95% CI 0.81–0.93), 0.56 (95% CI 0.35–0.75), respectively. The PPVs of [18F]FDG PET/CT proved to be higher in cases of secondary debulking surgeries; therefore, it can be a valuable predictor of complete successful secondary cytoreduction.
A Comparison of Interpretable Machine Learning Approaches to Identify Outpatient Clinical Phenotypes Predictive of First Acute Myocardial Infarction
Authors: Hodgman Matthew , Minoccheri Cristian , Mathis Michael , Wittrup Emily , Najarian Kayvan
Published: August 2024

Background: Acute myocardial infarctions are deadly to patients and burdensome to healthcare systems. Most recorded infarctions are patients’ first, occur out of the hospital, and often are not accompanied by cardiac comorbidities. The clinical manifestations of the underlying pathophysiology leading to an infarction are not fully understood and little effort exists to use explainable machine learning to learn predictive clinical phenotypes before hospitalization is needed. Methods: We extracted outpatient electronic health record data for 2641 case and 5287 matched-control patients, all without pre-existing cardiac diagnoses, from the Michigan Medicine Health System. We compare six different interpretable, feature extraction approaches, including temporal computational phenotyping, and train seven interpretable machine learning models to predict the onset of first acute myocardial infarction within six months. Results: Using temporal computational phenotypes significantly improved the model performance compared to alternative approaches. The mean cross-validation test set performance exhibited area under the receiver operating characteristic curve values as high as 0.674. The most consistently predictive phenotypes of a future infarction include back pain, cardiometabolic syndrome, family history of cardiovascular diseases, and high blood pressure. Conclusions: Computational phenotyping of longitudinal health records can improve classifier performance and identify predictive clinical concepts. State-of-the-art interpretable machine learning approaches can augment acute myocardial infarction risk assessment and prioritize potential risk factors for further investigation and validation.
The Impact of Histologic Portal T-Cell Density on the Clinical Outcomes in Hepatic Graft-versus-Host Disease and Autoimmune Liver Diseases
Authors: Lee Soon Kyu , Park Sung-Soo , Park Silvia , Lee Sung-Eun , Cho Byung-Sik , Eom Ki-Seong , Kim Yoo-Jin , Kim Hee-Je , Min Chang-Ki , Cho Seok-Goo , Lee Jong Wook , Lee Seok , Kim Younghoon , Han Ji Won , Yang Hyun , Bae Si Hyun , Jang Jeong Won , Choi Jong Young , Yoon Seung Kew , Lee Dong Yeup , Lee Sung Hak , Yoon Jae-Ho , Sung Pil Soo
Published: August 2024

Hepatic graft-versus-host disease (GVHD) significantly impacts morbidity and mortality among allogeneic hematopoietic stem cell transplant recipients. However, the relationship between clinical and immunopathological phenotypes and their influence on clinical outcomes in hepatic GVHD is not well understood. In this study, we aimed to study the implications of portal T-cell infiltration on the clinical outcomes in hepatic GHVD and its similarities to autoimmune liver disease. We analyzed 78 patients with biopsy-confirmed hepatic GVHD (n = 38) or autoimmune liver disease (n = 40) between 2016 and 2021. The cholestatic variant was defined by an R-value < 2.0, based on the ratio of alanine aminotransferase to alkaline phosphatase. The primary outcome was the biochemical response at 4 (early) and 8–12 (late) weeks after corticosteroid treatment. In hepatic GVHD patients, the hepatitic variant (n = 19) showed greater CD3+ T-cell infiltration than the cholestatic variant (n = 19; p < 0.001). No significant differences were observed in the infiltration of CD20+, CD38+, or CD68+ cells. The hepatitic variant had significantly better early and late responses and higher liver-related event-free survival than the cholestatic variants (p < 0.05). Concerning autoimmune liver diseases, the autoimmune hepatitis (AIH) group had significantly more portal T-cell infiltration and better treatment responses than the primary biliary cholangitis (PBC) group. In conclusion, higher portal T-cell infiltration may be associated with better clinical outcomes in patients with hepatic GVHD. Additionally, this study highlights similarities in portal T-cell infiltration and treatment response patterns between AIH and the hepatitic variant, as well as PBC and the cholestatic variant.
Gastric Cancer Detection with Ensemble Learning on Digital Pathology: Use Case of Gastric Cancer on GasHisSDB Dataset
Authors: Mudavadkar Govind Rajesh , Deng Mo , Al-Heejawi Salah Mohammed Awad , Arora Isha Hemant , Breggia Anne , Ahmad Bilal , Christman Robert , Ryan Stephen T. , Amal Saeed
Published: August 2024

Gastric cancer has become a serious worldwide health concern, emphasizing the crucial importance of early diagnosis measures to improve patient outcomes. While traditional histological image analysis is regarded as the clinical gold standard, it is labour intensive and manual. In recognition of this problem, there has been a rise in interest in the use of computer-aided diagnostic tools to help pathologists with their diagnostic efforts. In particular, deep learning (DL) has emerged as a promising solution in this sector. However, current DL models are still restricted in their ability to extract extensive visual characteristics for correct categorization. To address this limitation, this study proposes the use of ensemble models, which incorporate the capabilities of several deep-learning architectures and use aggregate knowledge of many models to improve classification performance, allowing for more accurate and efficient gastric cancer detection. To determine how well these proposed models performed, this study compared them with other works, all of which were based on the Gastric Histopathology Sub-Size Images Database, a publicly available dataset for gastric cancer. This research demonstrates that the ensemble models achieved a high detection accuracy across all sub-databases, with an average accuracy exceeding 99%. Specifically, ResNet50, VGGNet, and ResNet34 performed better than EfficientNet and VitNet. For the 80 × 80-pixel sub-database, ResNet34 exhibited an accuracy of approximately 93%, VGGNet achieved 94%, and the ensemble model excelled with 99%. In the 120 × 120-pixel sub-database, the ensemble model showed 99% accuracy, VGGNet 97%, and ResNet50 approximately 97%. For the 160 × 160-pixel sub-database, the ensemble model again achieved 99% accuracy, VGGNet 98%, ResNet50 98%, and EfficientNet 92%, highlighting the ensemble model’s superior performance across all resolutions. Overall, the ensemble model consistently provided an accuracy of 99% across the three sub-pixel categories. These findings show that ensemble models may successfully detect critical characteristics from smaller patches and achieve high performance. The findings will help pathologists diagnose gastric cancer using histopathological images, leading to earlier identification and higher patient survival rates.
Benefit of Optical Coherence Tomography–Angiography in Patients Undergoing Transsphenoidal Pituitary Adenoma Surgery: A Prospective Controlled Study
Authors: Toumi Elsa , Almairac Fabien , Mondot Lydiane , Themelin Albert , Decoux-Poullot Anne-Gaëlle , Paquis Philippe , Chevalier Nicolas , Baillif Stéphanie , Nahon-Esteve Sacha , Martel Arnaud
Published: August 2024

Background: Although visual field (VF) defects are common in compressive pituitary adenoma (CPA), their pathophysiology has not been fully elucidated. The mechanical theory (i.e., direct compression of the optic chiasm by the CPA) and the vascular theory (i.e., compression of the vessels supplying the visual path by the CPA) or their association could explain the visual impairment. The aim of this study was to determine whether the vascular density (VD) improved after surgical decompression of the optic chiasm in CPA patients and whether OCT-A could help to identify predictive factors for postoperative visual recovery. Methods: A prospective controlled study was conducted in patients who underwent transsphenoidal pituitary adenoma surgery. Patients were divided into two groups: with CPA and without CPA (NCPA). All patients underwent a neuro-ophthalmological examination, VF testing, macular and optic disc structural OCT [retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) thicknesses] and OCT-A before and then 1 and 6 months after surgery. Results: Twenty-four eyes and fourteen eyes were included, respectively, in the CPA and NCPA groups. None of the VD parameters assessed by OCT-A were significantly improved after surgery in the CPA group. In the CPA group, the mean macular superficial VD was significantly decreased at 6 months. The multivariate analysis failed to identify any preoperative parameters predictive of postoperative VF improvement. Conclusions: Our preliminary findings suggest that the visual impairment observed in CPA patients could not be explained by the vascular theory. None of the preoperative OCT-A parameters allowed a postoperative VF recovery assessment. Trial registration number NCT04074642, ID-RCB 2019-A01186-51 date of registration 30 July 2019.
Cross-Modality Medical Image Segmentation via Enhanced Feature Alignment and Cross Pseudo Supervision Learning
Authors: Yang Mingjing , Wu Zhicheng , Zheng Hanyu , Huang Liqin , Ding Wangbin , Pan Lin , Yin Lei
Published: August 2024

Given the diversity of medical images, traditional image segmentation models face the issue of domain shift. Unsupervised domain adaptation (UDA) methods have emerged as a pivotal strategy for cross modality analysis. These methods typically utilize generative adversarial networks (GANs) for both image-level and feature-level domain adaptation through the transformation and reconstruction of images, assuming the features between domains are well-aligned. However, this assumption falters with significant gaps between different medical image modalities, such as MRI and CT. These gaps hinder the effective training of segmentation networks with cross-modality images and can lead to misleading training guidance and instability. To address these challenges, this paper introduces a novel approach comprising a cross-modality feature alignment sub-network and a cross pseudo supervised dual-stream segmentation sub-network. These components work together to bridge domain discrepancies more effectively and ensure a stable training environment. The feature alignment sub-network is designed for the bidirectional alignment of features between the source and target domains, incorporating a self-attention module to aid in learning structurally consistent and relevant information. The segmentation sub-network leverages an enhanced cross-pseudo-supervised loss to harmonize the output of the two segmentation networks, assessing pseudo-distances between domains to improve the pseudo-label quality and thus enhancing the overall learning efficiency of the framework. This method’s success is demonstrated by notable advancements in segmentation precision across target domains for abdomen and brain tasks.
The Risk Factors for Myopia Undercorrection in Second-Generation (Visumax 800) Keratorefractive Lenticule Extraction Surgery: A Retrospective Case–Control Study
Authors: Lee Chia-Yi , Yang Shun-Fa , Chen Hung-Chi , Lian Ie-Bin , Huang Chin-Te , Huang Jing-Yang , Chang Chao-Kai
Published: August 2024

In this study, we aim to evaluate the risk factors of myopia undercorrection in recipients of second-generation keratorefractive lenticule extraction (KLEx) surgery. A retrospective case–control study was performed, and patients who received second-generation KLEx surgery were enrolled. The cases with myopia undercorrection were matched to non-myopia undercorrection cases with a 1:4 ratio according to age, and a total of 22 and 88 eyes were categorized into the undercorrection and control groups, respectively. Demographic, refractive, topographic, and surgical data were collected preoperatively. A generalized linear model was operated to evaluate the potential risk factors for myopia undercorrection. The uncorrected distance visual acuity (UDVA) at three months postoperation was significantly better in the control group (p = 0.006), and residual myopia and SE were significantly higher in the undercorrection group during the whole follow-up period (all p < 0.001). The UDVA value showed a trend of improvement in the control group (p < 0.001), and the changes to SE and residual myopia were significantly lower in the control group (both p < 0.001). Regarding the risk factors for myopia undercorrection in the whole population and the high-myopia population, a higher manifest sphere power, higher steep keratometry (K), higher topographic cylinder, lower central corneal thickness (CCT) at apex, higher CCT difference and lower residual stromal thickness (RST) correlated to myopia undercorrection (all p < 0.05). In the low-myopia population, only higher myopia and lower RST correlated to myopia undercorrection (both p < 0.05). In conclusion, a high-sphere power and irregular topographic pattern correlated to myopia undercorrection after the second KLEx surgery, especially for individuals with high myopia.
Prognostic Value of Optic Nerve Sheath Diameters after Acute Ischemic Stroke According to Slice Thickness on Computed Tomography
Authors: Lee Han-Bin , Oh Sang Hoon , Jang Jinhee , Koo Jaseong , Bang Hyo Jin , Lee Min Hwan
Published: August 2024

The optic nerve sheath diameter (ONSD) can predict intracranial pressure and outcomes in neurological disease, but it remains unclear whether a small ONSD can be accurately measured on routine CT images with a slice thickness of approximately 4–5 mm. We measured the ONSD and ONSD/eyeball transverse diameter (ETD) ratio on routine-slice (4 mm) and thin-slice (0.6–0.75 mm) brain CT images from initial scans of acute ischemic stroke (AIS) patients. ONSD-related variables, National Institutes of Health Stroke Scale (NIHSS) scores, and age were compared between good (modified Rankin Scale [mRS] ≤ 2) and poor (mRS > 2) outcomes at discharge. Among 155 patients, 38 had poor outcomes. The thin-slice ONSD was different between outcome groups (p = 0.047), while the routine-slice ONSD showed no difference. The area under the curve (AUC) values for the ONSD and ONSD/ETD were 0.58 (95% CI, 0.49–0.66) and 0.58 (95% CI, 0.50–0.66) on the routine-slice CT, and 0.60 (95% CI, 0.52–0.68) and 0.62 (95% CI, 0.54–0.69) on the thin-slice CT. The thin-slice ONSD/ETD ratio correlated with initial NIHSS scores (r = 0.225, p = 0.005). After adjusting for NIHSS scores and age, ONSD-related variables were not associated with outcomes, and adding them to a model with NIHSS scores and age did not improve performance (all p-values > 0.05). Although ONSD measurements were not an independent outcome predictor, they correlated with stroke severity, and the thin-slice ONSD provided a slightly better prognostic performance than the routine-slice ONSD.
A Two-Step Controller for Vision-Based Autonomous Landing of a Multirotor with a Gimbal Camera
Authors: Yoo Sangbaek , Park Jae-Hyeon , Chang Dong Eui
Published: August 2024

This article presents a novel vision-based autonomous landing method utilizing a multirotor and a gimbal camera, which is designed to be applicable from any initial position within a broad space by addressing the problems of a field of view and singularity to ensure stable performance. The proposed method employs a two-step controller based on integrated dynamics for the multirotor and the gimbal camera, where the multirotor approaches the landing site horizontally in the first step and descends vertically in the second step. The multirotor and the camera converge simultaneously to the desired configuration because we design the stabilizing controller for the integrated dynamics of the multirotor and the gimbal camera. The controller requires only one feature point and decreases unnecessary camera rolling. The effectiveness of the proposed method is demonstrated through simulation and real environment experiments.
The Impact of the COVID-19 Pandemic and Related Measures on the Sports Industry in Slovakia
Authors: Varmus Michal , Mičiak Martin , Toman Dominika , Boško Pavol , Greguška Ivan , Elkhwesky Zakaria
Published: August 2024

Stopping competitions and the training process was a shock that sports organizations had to deal with. Financial problems forced them to rethink the situation. In Slovakia, this became critical. This is why we started to research this issue to provide an answer to the research question: What are the actual consequences of government measures on the sports industry? A survey was conducted including two questionnaires made available between the pandemic waves. The first questionnaire was designed for athletes and sports professionals (N = 1040). The second addressed sports organizations (N = 626). Questionnaires were accessible via sports organizations’ portals. The ban on organizing mass sports events affected this industry. More than 80% of respondents had an experience of having to cancel a competition or training activity. This had an impact on their income as well as their future activities. We cooperate with government institutions and sports associations in Slovakia, so the results were provided to government officials. However, due to political changes accompanied by changes in the ministries responsible for the sports industry in Slovakia, it is relevant to summarize the research results in their present form. In this way they can serve as background for future sports policies.
A Novel Rational Medicine Use System Based on Domain Knowledge Graph
Authors: Qin Chaoping , Wang Zhanxiang , Zhao Jingran , Liu Luyi , Xiao Feng , Han Yi
Published: August 2024

Medication errors, which could often be detected in advance, are a significant cause of patient deaths each year, highlighting the critical importance of medication safety. The rapid advancement of data analysis technologies has made intelligent medication assistance applications possible, and these applications rely heavily on medical knowledge graphs. However, current knowledge graph construction techniques are predominantly focused on general domains, leaving a gap in specialized fields, particularly in the medical domain for medication assistance. The specialized nature of medical knowledge and the distinct distribution of vocabulary between general and biomedical texts pose challenges. Applying general natural language processing techniques directly to the medical domain often results in lower accuracy due to the inadequate utilization of contextual semantics and entity information. To address these issues and enhance knowledge graph production, this paper proposes an optimized model for named entity recognition and relationship extraction in the Chinese medical domain. Key innovations include utilizing Medical Bidirectional Encoder Representations from Transformers (MCBERT) for character-level embeddings pre-trained on Chinese biomedical corpora, employing Bi-directional Gated Recurrent Unit (BiGRU) networks for extracting enriched contextual features, integrating a Conditional Random Field (CRF) layer for optimal label sequence output, using the Piecewise Convolutional Neural Network (PCNN) to capture comprehensive semantic information and fusing it with entity features for better classification accuracy, and implementing a microservices architecture for the medication assistance review system. These enhancements significantly improve the accuracy of entity relationship classification in Chinese medical texts. The model achieved good performance in recognizing most entity types, with an accuracy of 88.3%, a recall rate of 85.8%, and an F1 score of 87.0%. In the relationship extraction stage, the accuracy reached 85.7%, the recall rate 82.5%, and the F1 score 84.0%.
Formation of Vibration Fields for a Mechatronic Platform Driven by Dual Asynchronous Motors
Authors: Fradkov Alexander L. , Andrievsky Boris , Tomchina Olga P. , Zaitceva Iuliia
Published: August 2024

This paper investigates the formation of vibration fields in a mechatronic setup driven by dual induction motors, relying on the controlled synchronization of unbalanced rotors. The proposed algorithm enables precise control over rotor speeds and phase shifts. Experimental results from a multi-resonance vibration laboratory setup demonstrate this approach’s ability to form the vibration fields. The ability to control these fields is crucial for applications such as vibratory transportation and the mixing of bulk materials. The results obtained can ensure a diverse picture of the complex trajectories of motion for various points of the platform, primarily in the screens, making various useful effects for vibration technologies. Additionally, the practical value of this research is that in the case of double synchronous mode the ordinate of the lower point of the trajectory is lower than in the case of single synchronous mode, which improves the efficiency of unloading and prevents congestion formation. The experimental data highlight the practical advantages and potential improvements in efficiency and reliability offered by this method.
Grover on Scrypt
Authors: Song Gyeongju , Seo Hwajeong
Published: August 2024

This paper presents an optimized quantum circuit for the scrypt cryptographic algorithm. We applied various optimization techniques to reduce the DW cost, which is the product of the time and space complexity of quantum circuits. In our proposed method, the number of ancilla qubits was significantly reduced through the use of optimized inverse operations, while the depth was minimized by implementing parallel structures. For the SHA-256, we devised a structure that achieves a substantial reduction in the number of ancilla qubits with only a slight increase in quantum circuit depth. By cleaning the dirty ancilla qubits used in the previous round through inverse operations, we enabled their reuse in each subsequent round. Specifically, we reduced the number of 8128 ancilla qubits, achieving this with an increase of only 6 in the full depth of the quantum circuit. Additionally, within Salsa20/8 in SMix, we reused qubits through inverse operations and performed some operations in parallel to reduce both the number of qubits and the overall quantum circuit depth. Finally, our quantum circuit for scrypt demonstrates a significant reduction in the width (the number of qubits) with only a minimal increase in the full quantum circuit depth.
Fire Segmentation with an Optimized Weighted Image Fusion Method
Authors: Tlig Mohamed , Bouchouicha Moez , Sayadi Mounir , Moreau Eric
Published: August 2024

In recent decades, earlier fire detection has become a research priority. Since visible and infrared images cannot produce clear and complete information, we propose in this work to combine two images with an appropriate fusion technique to improve the quality of fire detection, segmentation, and localization. The visible image is at first weighted before being used in the fusion process. The value of the optimal weight is estimated from the mean of the visible image with a second-order polynomial model. The parameters of this model are optimized with the least squares method from the curve of optimal weights according to the mean of visible images. Finally, a major voting method based on deep learning models is used. Experiments include an assessment of the framework’s performance not only with respect to its visual appearance but also across a spectrum of predefined evaluation criteria. The experiments show that the proposed model, which includes an optimized weighted image fusion stage before segmentation, has a high Intersection over Union (IoU) score of more than 94%.
VN-MADDPG: A Variable-Noise-Based Multi-Agent Reinforcement Learning Algorithm for Autonomous Vehicles at Unsignalized Intersections
Authors: Zhang Hao , Du Yu , Zhao Shixin , Yuan Ying , Gao Qiuqi
Published: August 2024

The decision-making performance of autonomous vehicles tends to be unstable at unsignalized intersections, making it difficult for them to make optimal decisions. We propose a decision-making model based on the Variable-Noise Multi-Agent Deep Deterministic Policy Gradient (VN-MADDPG) algorithm to address these issues. The variable-noise mechanism reduces noise dynamically, enabling the agent to utilize the learned policy more effectively to complete tasks. This significantly improves the stability of the decision-making model in making optimal decisions. The importance sampling module addresses the inconsistency between outdated experience in the replay buffer and current environmental features. This enhances the model’s learning efficiency and improves the robustness of the decision-making model. Experimental results on the CARLA simulation platform show that the success rate of decision making at unsignalized intersections by autonomous vehicles has significantly increased, and the pass time has been reduced. The decision-making model based on the VN-MADDPG algorithm demonstrates stable and excellent decision-making performance.
Ohmic Contact Formation to β-Ga2O3 Nanosheet Transistors with Ar-Containing Plasma Treatment
Authors: Chen Jin-Xin , Liu Bing-Yan , Gu Yang , Li Bin
Published: August 2024

Effective Ohmic contact between metals and their conductive channels is a crucial step in developing high-performance Ga2O3-based transistors. Distinct from bulk materials, excess thermal energy of the annealing process can destroy the low-dimensional material itself. Given the thermal budget concern, a feasible and moderate solution (i.e., Ar-containing plasma treatment) is proposed to achieve effective Ohmic junctions with (100) β-Ga2O3 nanosheets. The impact of four kinds of plasma treatments (i.e., gas mixtures SF6/Ar, SF6/O2/Ar, SF6/O2, and Ar) on (100) β-Ga2O3 crystals is comparatively studied by X-ray photoemission spectroscopy for the first time. With the optimal plasma pre-treatment (i.e., Ar plasma, 100 W, 60 s), the resulting β-Ga2O3 nanosheet field-effect transistors (FETs) show effective Ohmic contact (i.e., contact resistance RC of 104 Ω·mm) without any post-annealing, which leads to competitive device performance such as a high current on/off ratio (>107), a low subthreshold swing (SS, 249 mV/dec), and acceptable field-effect mobility (μeff, ~21.73 cm2 V−1 s−1). By using heavily doped β-Ga2O3 crystals (Ne, ~1020 cm−3) for Ar plasma treatments, the contact resistance RC can be further decreased to 5.2 Ω·mm. This work opens up new opportunities to enhance the Ohmic contact performance of low-dimensional Ga2O3-based transistors and can further benefit other oxide-based nanodevices.