bluuebunny/crossref_metadata_2025 huggingface dataset:
Correction of Local Brain Temperature after Severe Brain Injury Using Hypothermia and Medical Microwave Radiometry (MWR) as Companion Diagnostics
Authors: Shevelev Oleg A. , Petrova Marina V. , Mengistu Elias M. , Yuriev Mikhail Y. , Kostenkova Inna Z. , Vesnin Sergey G. , Kanarskii Michael M. , Zhdanova Maria A. , Goryanin Igor
Published: March 2023

The temperature of the brain can reflect the activity of its different regions, allowing us to evaluate the connections between them. A study involving 111 patients in a vegetative state or minimally conscious state used microwave radiometry to measure their cortical temperature. The patients were divided into a main group receiving a 10-day selective craniocerebral hypothermia (SCCH) procedure, and a control group receiving basic therapy and rehabilitation. The main group showed a significant improvement in consciousness level as measured by CRS-R assessment on day 14 compared to the control group. Temperature heterogeneity increased in patients who received SCCH, while remaining stable in the control group. The use of microwave radiometry to assess rehabilitation effectiveness and the inclusion of SCCH in rehabilitation programs appears to be a promising approach.
Anticoagulation for Atrial Fibrillation in Patients with Decompensated Liver Cirrhosis: Bold and Brave?
Authors: Gîrleanu Irina , Trifan Anca , Huiban Laura , Muzica Cristina Maria , Petrea Oana Cristina , Sîngeap Ana-Maria , Cojocariu Camelia , Chiriac Stefan , Cuciureanu Tudor , Stafie Remus , Zenovia Sebastian , Stratina Ermina , Rotaru Adrian , Nastasa Robert , Sfarti Catalin , Costache Irina Iuliana , Stanciu Carol
Published: March 2023

Atrial fibrillation is frequently diagnosed in patients with liver cirrhosis, especially in those with non-alcoholic steatohepatitis or alcoholic etiology. Anticoagulant treatment is recommended for thromboembolic protection in patients with atrial fibrillation. Considering the impaired coagulation balance in liver cirrhosis, predisposing patients to bleed or thrombotic events, the anticoagulant treatment is still a matter of debate. Although patients with liver cirrhosis were excluded from the pivotal studies that confirmed the efficacy and safety of the anticoagulant treatment in patients with atrial fibrillation, data from real-life cohorts demonstrated that the anticoagulant treatment in patients with liver cirrhosis could be safe. This review aimed to evaluate the recent data regarding the safety and efficacy of anticoagulant treatment in patients with decompensated liver cirrhosis. Direct oral anticoagulants are safer than warfarin in patients with compensated liver cirrhosis. In Child–Pugh class C liver cirrhosis, direct oral anticoagulants are contraindicated. New bleeding and ischemic risk scores should be developed especially for patients with liver cirrhosis, and biomarkers for bleeding complications should be implemented in clinical practice to personalize this treatment in a very difficult population represented by decompensated liver cirrhosis patients.
Enhancement of Ultrasound B-Mode Image Quality Using Nonlinear Filtered-Multiply-and-Sum Compounding for Improved Carotid Artery Segmentation
Authors: Mohamed Moubark Asraf , Nie Luzhen , Mohd Zaman Mohd Hairi , Islam Mohammad Tariqul , Zulkifley Mohd Asyraf , Baharuddin Mohd Hafiz , Alomari Zainab , Freear Steven
Published: March 2023

In ultrasound B-mode imaging, the axial resolution (AR) is commonly determined by the duration or bandwidth of an excitation signal. A shorter-duration pulse will produce better resolution compared to a longer one but with compromised penetration depth. Instead of relying on the pulse duration or bandwidth to improve the AR, an alternative method termed filtered multiply and sum (FMAS) has been introduced in our previous work. For spatial-compounding, FMAS uses the autocorrelation technique as used in filtered-delay multiply and sum (FDMAS), instead of conventional averaging. FMAS enables a higher frame rate and less computational complexity than conventional plane-wave compound imaging beamformed with delay and sum (DAS) and FDMAS. Moreover, it can provide an improved contrast ratio and AR. In previous work, no explanation was given on how FMAS was able to improve the AR. Thus, in this work, we discuss in detail the theory behind the proposed FMAS algorithm and how it is able to improve the spatial resolution mainly in the axial direction. Simulations, experimental phantom measurements and in vivo studies were conducted to benchmark the performance of the proposed method. We also demonstrate how the suggested new algorithm may be used in a practical biomedical imaging application. The balloon snake active contour segmentation technique was applied to the ultrasound B-mode image of a common carotid artery produced with FMAS. The suggested method is capable of reducing the number of iterations for the snake to settle on the region-of-interest contour, accelerating the segmentation process.
Comparison of Two Tuberculosis Infection Tests in a South American Tertiary Hospital: STANDARD F TB-Feron FIA vs. QIAreachTM QuantiFERON-TB
Authors: Saint-Pierre Gustavo , Conei Daniel , Cantillana Patricia , Raijmakers Mariella , Vera Andrea , Gutiérrez Daniela , Kennedy Cristopher , Peralta Paulina , Ramonda Paulina
Published: March 2023

Introduction: Tuberculosis (TB) is one of the most prevalent respiratory diseases in the world. In 2020 there were at least 9.9 million new infections, with 1.5 million deaths. Approximately 10% of people infected with Mycobacterium tuberculosis develop the disease during the first 2 to 5 years after infection. In South America, the diagnosis of Latent Tuberculosis Infections (LTBI) continues to be performed through the Mantoux tuberculin skin test (TST). Objective: The objective of our study was to compare the sensitivity of a new immunofluorescence IGRA test against a widely available IGRA kit on the market. Material and method: Close contact with infectious TB patients, HIV patients, or immunocompromised for another cause were recruited. Two interferon-gamma release assay (IGRA) diagnostic kits were used and compared with TST. Results: 76 patients were recruited, 93.42% were Chilean nationality, and 98.68% of the patients did not have immunosuppression. The sensitivity of the new technique was 88.89%, and the specificity was 92.50% in the study population compared to the IGRA previously used. In the subgroup older than 36 years, the sensitivity was 95.65%, and the specificity was 89.47%. Conclusion: IGRA techniques are a new resource in clinical laboratories to make an accurate diagnosis of LTBI in the region of the Americas. In our population, the greatest benefit of this new IGRA would be observed in people over 36 years of age, where the sensitivity of the technique was like that of the currently available test.
SH2 Domain-Containing Phosphatase-SHP2 Attenuates Fibrotic Responses through Negative Regulation of Mitochondrial Metabolism in Lung Fibroblasts
Authors: Karampitsakos Theodoros , Galaris Apostolos , Barbayianni Ilianna , DeIuliis Giuseppe , Ahangari Farida , Sampsonas Fotis , Sotiropoulou Vasilina , Aidinis Vassilis , Bennett Anton , Herazo-Maya Jose , Xylourgidis Nikolaos , Bakakos Petros , Bouros Demosthenes , Kaminski Naftali , Tzouvelekis Argyrios
Published: March 2023

Background: We have previously shown that SHP2 downregulation may predispose fibroblasts to differentiate into myofibroblasts and proposed a role for SHP2 downregulation in the pathogenesis of idiopathic pulmonary fibrosis (IPF). Recent data have shown that SHP2 localizes to the mitochondrial intercristae, and its overexpression enhances mitochondrial metabolism leading to oxidative stress and senescence. Objective: To determine the effect of SHP2 on fibrotic responses. Methods and Results: Primary mouse lung fibroblasts derived from mice carrying a conditional knock-in mutation (D61G/+), rendering the SHP2 catalytic domain constitutively active, had reduced proliferation (1.6-fold, p < 0.05), migration (2-fold, p < 0.05), as well as reduced responsiveness of TGFB-1 induced fibroblasts-to-myofibroblasts differentiation, compared to wild-type ones. Electron microscope analysis revealed that SHP2 D61G/+ mouse lung fibroblasts were characterized by mitochondrial abnormalities, including swollen mitochondria with disrupted electron-lucent cristae and an increased number of autophagosomes compared to wild-type ones. SHP2 D61G/+ MLFs exhibited increased protein levels of autophagy markers, including LC3B-II and p-62, evidence that was confirmed by immunofluorescence analysis. Mitochondrial function analysis revealed that stable (genotype D61G/+) overexpression of SHP2 led to impaired mitochondrial function, as assessed by decreased mitochondrial membrane potential (1.29-fold, p < 0.05), coupling efficiency (1.82 fold, p < 0.05), oxygen consumption rate (1.9-fold, p < 0.05), and increased reactive oxygen species production both at baseline (1.75-fold, p < 0.05) and following H2O2 stimulation (1.63-fold, p < 0.05) compared to wild-type ones (SHP2+/+). SHP2 D61G/+ mouse lung fibroblasts showed enhanced AMPK activity, as well as decreased activation of the mTORC1 signaling pathway, potentially leading to ineffective mitochondrial metabolism and increased autophagy. Conclusions: SHP2 attenuates fibrotic responses in fibroblast cell lines through negative regulation of mitochondrial metabolism and induction of autophagy. SHP2 activation may represent a promising therapeutic strategy for patients with fibrotic lung diseases.
Prediction of Fatty Liver Disease in a Chinese Population Using Machine-Learning Algorithms
Authors: Weng Shuwei , Hu Die , Chen Jin , Yang Yanyi , Peng Daoquan
Published: March 2023

Background: Fatty liver disease (FLD) is an important risk factor for liver cancer and cardiovascular disease and can lead to significant social and economic burden. However, there is currently no nationwide epidemiological survey for FLD in China, making early FLD screening crucial for the Chinese population. Unfortunately, liver biopsy and abdominal ultrasound, the preferred methods for FLD diagnosis, are not practical for primary medical institutions. Therefore, the aim of this study was to develop machine learning (ML) models for screening individuals at high risk of FLD, and to provide a new perspective on early FLD diagnosis. Methods: This study included a total of 30,574 individuals between the ages of 18 and 70 who completed abdominal ultrasound and the related clinical examinations. Among them, 3474 individuals were diagnosed with FLD by abdominal ultrasound. We used 11 indicators to build eight classification models to predict FLD. The model prediction ability was evaluated by the area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, and kappa value. Feature importance analysis was assessed by Shapley value or root mean square error loss after permutations. Results: Among the eight ML models, the prediction accuracy of the extreme gradient boosting (XGBoost) model was highest at 89.77%. By feature importance analysis, we found that the body mass index, triglyceride, and alanine aminotransferase play important roles in FLD prediction. Conclusion: XGBoost improves the efficiency and cost of large-scale FLD screening.
Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer
Authors: Li Chanyuan , Deng Ting , Cao Junya , Zhou Yun , Luo Xiaolin , Feng Yanling , Huang He , Liu Jihong
Published: March 2023

Epithelial ovarian cancer is by far the most lethal gynecological malignancy. The exploration of promising immunomarkers to predict prognosis in ovarian cancer patients remains challenging. In our research, we carried out an integrated bioinformatic analysis of genome expressions and their immune characteristics in the ovarian cancer microenvironment with validation in different experiments. We filtrated 332 differentially expressed genes with 10 upregulated hub genes from the Gene Expression Omnibus database. These genes were closely related to ovarian tumorigenesis. Subsequently, the survival and immune infiltration analysis demonstrated that the upregulation of five candidate genes, ITGB2, VEGFA, CLDN4, OCLN, and SPP1, were correlated with an unfavorable clinical outcome and increased immune cell infiltration in ovarian cancer. Of these genes, ITGB2 tended to be the gene most correlated with various immune cell infiltrations and had a strong correlation with significant M2 macrophages infiltration (r = 0.707, p = 4.71 × 10−39), while it had a moderate correlation with CD4+/CD8+ T cells and B cells. This characteristic explains why the high expression of ITGB2 was accompanied by immune activation but did not reverse carcinogenesis. Additionally, we confirmed that ITGB2 was over-expressed in ovarian cancer tissues and was mainly located in cytoplasm, detected by Western blotting and the immunohistochemical method. In summary, ITGB2 may serve as a prognostic immunomarker for ovarian cancer patients.
Prediction of Acid-Base and Potassium Imbalances in Intensive Care Patients Using Machine Learning Techniques
Authors: Phetrittikun Ratchakit , Suvirat Kerdkiat , Horsiritham Kanakorn , Ingviya Thammasin , Chaichulee Sitthichok
Published: March 2023

Acid–base disorders occur when the body’s normal pH is out of balance. They can be caused by problems with kidney or respiratory function or by an excess of acids or bases that the body cannot properly eliminate. Acid–base and potassium imbalances are mechanistically linked because acid–base imbalances can alter the transport of potassium. Both acid–base and potassium imbalances are common in critically ill patients. This study investigated machine learning models for predicting the occurrence of acid–base and potassium imbalances in intensive care patients. We used an institutional dataset of 1089 patients with 87 variables, including vital signs, general appearance, and laboratory results. Gradient boosting (GB) was able to predict nine clinical conditions related to acid–base and potassium imbalances: mortality (AUROC = 0.9822), hypocapnia (AUROC = 0.7524), hypercapnia (AUROC = 0.8228), hypokalemia (AUROC = 0.9191), hyperkalemia (AUROC = 0.9565), respiratory acidosis (AUROC = 0.8125), respiratory alkalosis (AUROC = 0.7685), metabolic acidosis (AUROC = 0.8682), and metabolic alkalosis (AUROC = 0.8284). Some predictions remained relatively robust even when the prediction window was increased. Additionally, the decision-making process was made more interpretable and transparent through the use of SHAP analysis. Overall, the results suggest that machine learning could be a useful tool to gain insight into the condition of intensive care patients and assist in the management of acid–base and potassium imbalances.
Initial Serum Levels of Magnesium and Calcium as Predictors of Mortality in Traumatic Brain Injury Patients: A Retrospective Study
Authors: Mekkodathil Ahammed , El-Menyar Ayman , Hakim Suhail , Al Jogol Hisham , Parchani Ashok , Peralta Ruben , Rizoli Sandro , Al-Thani Hassan
Published: March 2023

Background: We sought to evaluate the predictor role of the initial serum level of calcium and magnesium in hospitalized traumatic brain injury (TBI) patients. Materials and methods: A retrospective analysis of all TBI patients admitted to the Hamad Trauma Center (HTC), between June 2016 and May 2021 was conducted. Initial serum electrolyte levels of TBI patients were obtained. A comparative analysis of clinical variables between patients with abnormal and normal serum electrolyte level was performed. Logistic regression analysis with the variables that showed a significant difference (p < 0.05) in the bivariate analysis was performed to calculate the odds ratios (OR) for mortality. Results: There was a total of 922 patients with clinical records of serum electrolyte levels at admission. Of these, 757 (82.1%) had hypocalcemia, 158 (17.1%) had normal calcium level, and 7 (0.8%) had hypercalcemia. On the other hand, 616 (66.8%) patients had normal magnesium level, 285 (30.9%) had hypomagnesemia, and 12 (1.3%) had hypermagnesemia. The mortality rate in hypocalcemia group was 24% while in patients with normal calcium level it was 12%, p = 0.001. Proportionate mortality rates in hypomagnesemia and normal magnesium groups were 15% and 23% (p = 0.006), respectively. On the other hand, 7 out of 12 (58%) hypermagnesemia patients died during the index hospitalization. The regression model including GCS, ISS, PT, aPTT, INR, Hemoglobin, Bicarbonate, Lactate, Sodium, Potassium, Calcium, Magnesium, and Phosphate showed that hypocalcemia was not a significant predictor [OR 0.59 (CI 95%: 0.20–1.35)] of mortality after TBI. However, hypermagnesemia was a significant predictor [OR 16 (CI 95%: 2.1–111)] in addition to the GCS, ISS, aPTT, Bicarbonate, and Lactate values on admission. Conclusion: Although hypocalcemia and hypomagnesemia are common in hospitalized TBI patients, hypocalcemia was not a significant predictor of mortality, while hypermagnesemia was an independent predictor. Further studies with larger sample size and with prospective design are required to support these findings and their importance.
Prediction of Perforated and Nonperforated Acute Appendicitis Using Machine Learning-Based Explainable Artificial Intelligence
Authors: Akbulut Sami , Yagin Fatma Hilal , Cicek Ipek Balikci , Koc Cemalettin , Colak Cemil , Yilmaz Sezai
Published: March 2023

Background: The primary aim of this study was to create a machine learning (ML) model that can predict perforated and nonperforated acute appendicitis (AAp) with high accuracy and to demonstrate the clinical interpretability of the model with explainable artificial intelligence (XAI). Method: A total of 1797 patients who underwent appendectomy with a preliminary diagnosis of AAp between May 2009 and March 2022 were included in the study. Considering the histopathological examination, the patients were divided into two groups as AAp (n = 1465) and non-AAp (NA; n = 332); the non-AAp group is also referred to as negative appendectomy. Subsequently, patients confirmed to have AAp were divided into two subgroups: nonperforated (n = 1161) and perforated AAp (n = 304). The missing values in the data set were assigned using the Random Forest method. The Boruta variable selection method was used to identify the most important variables associated with AAp and perforated AAp. The class imbalance problem in the data set was resolved by the SMOTE method. The CatBoost model was used to classify AAp and non-AAp patients and perforated and nonperforated AAp patients. The performance of the model in the holdout test set was evaluated with accuracy, F1- score, sensitivity, specificity, and area under the receiver operator curve (AUC). The SHAP method, which is one of the XAI methods, was used to interpret the model results. Results: The CatBoost model could distinguish AAp patients from non-AAp individuals with an accuracy of 88.2% (85.6–90.8%), while distinguishing perforated AAp patients from nonperforated AAp individuals with an accuracy of 92% (89.6–94.5%). According to the results of the SHAP method applied to the CatBoost model, it was observed that high total bilirubin, WBC, Netrophil, WLR, NLR, CRP, and WNR values, and low PNR, PDW, and MCV values increased the prediction of AAp biochemically. On the other hand, high CRP, Age, Total Bilirubin, PLT, RDW, WBC, MCV, WLR, NLR, and Neutrophil values, and low Lymphocyte, PDW, MPV, and PNR values were observed to increase the prediction of perforated AAp. Conclusion: For the first time in the literature, a new approach combining ML and XAI methods was tried to predict AAp and perforated AAp, and both clinical conditions were predicted with high accuracy. This new approach proved successful in showing how well which demographic and biochemical parameters could explain the current clinical situation in predicting AAp and perforated AAp.
Preliminary Findings of the Role of FAPi in Prostate Cancer Theranostics
Authors: Laudicella Riccardo , Spataro Alessandro , Crocè Ludovica , Giacoppo Giulia , Romano Davide , Davì Valerio , Lopes Maria , Librando Maria , Nicocia Antonio , Rappazzo Andrea , Celesti Greta , Torre Flavia La , Pagano Benedetta , Garraffa Giuseppe , Bauckneht Matteo , Burger Irene A , Minutoli Fabio , Baldari Sergio
Published: March 2023

Prostate cancer (PCa) is the most frequently diagnosed cancer worldwide and the second most common cause of cancer-related deaths among men. Progress in molecular imaging has magnified its clinical management; however, an unmet clinical need involves the identification of new imaging biomarkers that complement the gold standard of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) in cases of clinically significant PCa that do not express PSMA. Fibroblast activation protein (FAP) is a type II transmembrane serine overexpressed in many solid cancers that can be imaged through quinoline-based PET tracers derived from an FAP inhibitor (FAPi). Preliminary results of FAPi application in PCa (in PSMA-negative lesions, and in comparison with fluorodeoxyglucose—FDG) are now available in the literature. FAP-targeting ligands for PCa are not limited to detection, but could also include therapeutic applications. In this preliminary review, we provide an overview of the clinical applications of FAPi ligands in PCa, summarising the main results and highlighting contemporary strengths and limitations.
Benefit of 3D Vena Contracta Area over 2D-Based Echocardiographic Methods in Quantification of Functional Mitral Valve Regurgitation
Authors: Jungels Vinzenz M. , Heidrich Felix M. , Pfluecke Christian , Linke Axel , Sveric Krunoslav M.
Published: March 2023

Background: The two-dimensional proximal isovelocity surface area (2D PISA) method in the quantification of an effective regurgitation orifice area (EROA) has limitations in functional mitral valve regurgitation (FMR), particularly in non-circular coaptation defects. Objective: We aimed to validate a three-dimensional vena contracta area (3D VCA) against a conventional EROA using a 2D PISA method and anatomic regurgitation orifice area (AROA) in patients with FMR. Methods: Both 2D and 3D full-volume color Doppler data were acquired during consecutive transoesophageal echocardiography (TEE) examinations. The EROA 2D PISA was calculated as recommended by current guidelines. Multiplanar reconstruction was used for offline analysis of the 3D VCA (with a color Doppler) and AROA (without a color Doppler). Receiver operating characteristic (ROC) analysis was used to calculate a cut-off value for the 3D VCA to discriminate between moderate and severe FMR as classified by the EROA 2D PISA. Results: From 2015 to 2018, 105 consecutive patients with complete and adequate imaging data were included. The 3D VCA correlated strongly with the 2D PISA EROA and AROA (r = 0.93 and 0.94). In the presence of eccentric or multiple regurgitant jets, there was no significant difference in correlations with the 3D VCA. We found a 3D VCA cut-off of 0.43 cm2 to discriminate between moderate and severe FMR (area under curve = 0.98). The 3D VCA showed a higher interobserver agreement than the EROA 2D PISA (interclass correlation coefficient: 0.94 vs. 0.81). Conclusions: The 3D VCA has excellent validity and lower variability than the conventional 2D PISA in FMR. Compared to the 2D PISA, the 3D VCA was not affected by the presence of eccentric or multiple regurgitation jets or non-circular regurgitation orifices. With a threshold of 0.43 cm2 for the 3D VCA, we demonstrated reliable discrimination between moderate and severe FMR.
Large-Scale Clinical Evaluation of Rapid Blood Culture Identification Panels for Bloodstream Infections at a Tertiary Hospital
Authors: So Min-Kyung , Kim Soo-Kyung , Chung Hae-Sun , Bae Ji-Yun , Lee Miae
Published: March 2023

The prompt implementation of optimal antibacterial therapy through the rapid identification of the causative organisms is essential for improving outcomes for critically ill patients with bloodstream infections. We evaluated the clinical performance of the FilmArray blood culture identification (BCID) panel for rapidly identifying causative pathogens in the bloodstream using large-scale clinical samples. We analyzed the results of identification using a BCID panel performed on 2005 positive blood culture bottles from September 2019 to June 2022. Pathogen detection efficiency and interval from Gram staining to identification using the BCID panel were compared to those of conventional identification systems—VITEK MS MALDI-TOF Mass Spectrometer and Vitek2—and antibiotic susceptibility testing—Vitek2. We detected 2167 isolates from 2005 positive blood culture bottles. In these isolates, the BCID panel showed 93% full agreement—both organisms and antimicrobial resistance genes were matched, and no off-target organisms were detected. Species-level discordance was found in 0.6% of tests. Sixty-five isolates (3.0%) were only detected by BCID, whereas 22 isolates (1.0%) from the on-target panel were not detected by BCID. This large-scale study demonstrated that the BCID panel was a reliable and rapid identification method for directly identifying bloodstream pathogens in a positive blood culture.
Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD
Authors: Kalra Gagan , Cetin Hasan , Whitney Jon , Yordi Sari , Cakir Yavuz , McConville Conor , Whitmore Victoria , Bonnay Michelle , Reese Jamie L. , Srivastava Sunil K. , Ehlers Justis P.
Published: March 2023

Background: The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD). Methods: Used in DL model training and testing were 341 subjects with nonexudative AMD with or without geographic atrophy (GA). An independent dataset of 120 subjects were used for testing model performance for prediction of GA progression. Accuracy, specificity, sensitivity, and intraclass correlation coefficient (ICC) for DL-based EZ At-Risk percentage area measurement was calculated. Random forest-based feature ranking of EZ At-Risk was compared to previously validated quantitative OCT-based biomarkers. Results: The model achieved a detection accuracy of 99% (sensitivity = 99%; specificity = 100%) for EZ At-Risk. Automatic EZ At-Risk measurement achieved an accuracy of 90% (sensitivity = 90%; specificity = 84%) and the ICC compared to ground truth was high (0.83). In the independent dataset, higher baseline mean EZ At-Risk correlated with higher progression to GA at year 5 (p < 0.001). EZ At-Risk was a top ranked feature in the random forest assessment for GA prediction. Conclusions: This report describes a novel high performance DL-based model for the detection and measurement of EZ At-Risk. This biomarker showed promising results in predicting progression in nonexudative AMD patients.
NGAL as Biomarker of Clinical and Subclinical Damage of Kidney Function after Coronary Angiography
Authors: Petrova Iliyana , Alexandrov Alexander , Vladimirov Georgi , Mateev Hristo , Bogov Ivaylo , Paskaleva Iva , Gotcheva Nina
Published: March 2023

Contrast-induced acute kidney injury (CI-AKI) is a serious complication after angiographic examinations in cardiology. Diagnosis may be delayed based on standard serum creatinine, and subclinical forms of kidney damage may not be detected at all. In our study, we investigate the clinical use in these directions of a “damage”-type biomarker—neutrophil gelatinase-associated lipocalin (NGAL). Among patients with a high-risk profile undergoing scheduled coronary angiography and/or angioplasty, plasma NGAL was determined at baseline and at 4th and 24th h after contrast administration. In the CI-AKI group, NGAL increased significantly at the 4th hour (Me 109.3 (IQR 92.1–148.7) ng/mL versus 97.6 (IQR 69.4–127.0) ng/mL, p = 0.006) and at the 24th hour (Me 131.0 (IQR 81.1–240.8) ng/mL, p = 0.008). In patients with subclinical CI-AKI, NGAL also increased significantly at the 4th hour (Me 94.0 (IQR 75.5–148.2) ng/mL, p = 0.002) and reached levels close to those in patients with CI-AKI. Unlike the new biomarker, however, serum creatinine did not change significantly in this group. The diagnostic power of NGAL is extremely good—AUC 0.847 (95% CI: 0.677–1.000; p = 0.001) in CI-AKI and AUC 0.731 (95% CI: 0.539–0.924; p = 0.024) in subclinical CI-AKI. NGAL may be a reliable biomarker for the early diagnosis of clinical and subclinical forms of renal injury after contrast angiographic studies.
First Results of a New Deep Learning Reconstruction Algorithm on Image Quality and Liver Metastasis Conspicuity for Abdominal Low-Dose CT
Authors: Greffier Joël , Durand Quentin , Serrand Chris , Sales Renaud , de Oliveira Fabien , Beregi Jean-Paul , Dabli Djamel , Frandon Julien
Published: March 2023

The study’s aim was to assess the impact of a deep learning image reconstruction algorithm (Precise Image; DLR) on image quality and liver metastasis conspicuity compared with an iterative reconstruction algorithm (IR). This retrospective study included all consecutive patients with at least one liver metastasis having been diagnosed between December 2021 and February 2022. Images were reconstructed using level 4 of the IR algorithm (i4) and the Standard/Smooth/Smoother levels of the DLR algorithm. Mean attenuation and standard deviation were measured by placing the ROIs in the fat, muscle, healthy liver, and liver tumor. Two radiologists assessed the image noise and image smoothing, overall image quality, and lesion conspicuity using Likert scales. The study included 30 patients (mean age 70.4 ± 9.8 years, 17 men). The mean CTDIvol was 6.3 ± 2.1 mGy, and the mean dose-length product 314.7 ± 105.7 mGy.cm. Compared with i4, the HU values were similar in the DLR algorithm at all levels for all tissues studied. For each tissue, the image noise significantly decreased with DLR compared with i4 (p < 0.01) and significantly decreased from Standard to Smooth (−26 ± 10%; p < 0.01) and from Smooth to Smoother (−37 ± 8%; p < 0.01). The subjective image assessment confirmed that the image noise significantly decreased between i4 and DLR (p < 0.01) and from the Standard to Smoother levels (p < 0.01), but the opposite occurred for the image smoothing. The highest scores for overall image quality and conspicuity were found for the Smooth and Smoother levels.
Entropy and Cities: A Bibliographic Analysis towards More Circular and Sustainable Urban Environments
Authors: Rondinel-Oviedo Daniel R. , Keena Naomi
Published: March 2023

Cities are critical to a sustainable future for our planet; still, the construction and operation of cities rely on intensive resource and energy use and transformation, leading to the generation of waste, effluents, and pollution, representing negative externalities outside and inside the city. Within every process, transformation implies the use of energy and the increase of entropy. In an urban system, the transformation of energy and materials will trigger the creation of entropic landscapes, mainly in the informal city and in unguarded natural landscapes, even hundreds of kilometers away, which generates substantial economic, social, and environmental impacts. In this sense, cities are significant contributors to the environmental crisis. Upstream, degradation of landscapes and ecosystems is frequent. Cities’ externalities and exogenous consumptions are directly linked with entropy and entropic landscapes, which are recognized as pollution (in the air, water, and land) or waste and in the degradation of natural ecosystems and communities. Through a systematic review of existing literature, this paper first outlines briefly how entropy has been applied in different disciplines and then focuses on presenting recent developments of how entropy has been defined, used, and characterized in urban studies concerning sustainability in cities and architecture, and presents a definition of the concept in relation to urban systems and key aspects to consider.
FLoCIC: A Few Lines of Code for Raster Image Compression
Authors: Žalik Borut , Strnad Damjan , Kohek Štefan , Kolingerová Ivana , Nerat Andrej , Lukač Niko , Lipuš Bogdan , Žalik Mitja , Podgorelec David
Published: March 2023

A new approach is proposed for lossless raster image compression employing interpolative coding. A new multifunction prediction scheme is presented first. Then, interpolative coding, which has not been applied frequently for image compression, is explained briefly. Its simplification is introduced in regard to the original approach. It is determined that the JPEG LS predictor reduces the information entropy slightly better than the multi-functional approach. Furthermore, the interpolative coding was moderately more efficient than the most frequently used arithmetic coding. Finally, our compression pipeline is compared against JPEG LS, JPEG 2000 in the lossless mode, and PNG using 24 standard grayscale benchmark images. JPEG LS turned out to be the most efficient, followed by JPEG 2000, while our approach using simplified interpolative coding was moderately better than PNG. The implementation of the proposed encoder is extremely simple and can be performed in less than 60 lines of programming code for the coder and 60 lines for the decoder, which is demonstrated in the given pseudocodes.
Introduction to Light Properties and Basic Principles of Spectroscopy at the High-School Level: A Pilot Study
Authors: Carpentieri Maria Antonietta , Fano Gioia , Jurinovich Sandro , Domenici Valentina
Published: March 2023

Spectroscopy is the basis of many applications in chemistry; however, the basic principles of light, light–matter interaction, and the operation of spectrophotometers are rarely present in chemistry curricula at the high-school level, or they are only briefly introduced to students before focusing on analytical chemistry applications. In this work, we report the results of a study conducted over several years, aimed to design, optimise, and put into practice a didactic sequence on light phenomena such as reflection, refraction, interference, diffraction, and light dispersion, as well as the basic principles of ultraviolet–visible spectroscopy and spectroscopic instruments. Difficult concepts of light phenomena and related topics were deeply investigated, focusing on the best ways to teach them to high-school students in the framework of the content-specific components identified in the topic-specific pedagogical content knowledge theoretical model. Inquiry-based learning and interactive STEM laboratory activities were combined with a historical epistemological teaching method. Short introductory videos were also recorded to help students during the remote lessons in the COVID-19 pandemic period. In this paper, we report and discuss the research strategy used in order to design and implement the sequence of educational activities, leading to a final optimised didactic sequence that was tested in a pilot study. The main results were obtained from the experimentation with several classes in two high-school technical institutes with a chemistry and material sciences curriculum, along with a group of undergraduate students during the first part of an introductory course on molecular spectroscopy.
Interactions of Power and Social Pedagogical Recognition: An Analysis of Narratives of Pupils Who Use Alcohol and Drugs in an Upper Secondary School Context in Sweden
Authors: Olsson Lina , Färdig Belinda , Basic Goran
Published: March 2023

The aim of this study is to contribute new knowledge about interactions of power and social pedagogical recognition in narratives of students who use alcohol and drugs in an upper secondary school context. In this context, the student narratives create and re-create a series of images of varied treatment by professional actors (e.g., teachers, student coordinators, counsellors). The reproduced power interactions in narratives describing the practices of professional actors are significant for student learning, teaching, nurturing, inclusion, change, discipline, and identity creation. The social pedagogical recognition of the “other party” in the pupil–professional actor relationship is especially important for achieving the aims of including pupils who use alcohol and drugs in a learning context and enacting positive change through the creation and re-creation of social pedagogical identities (e.g., successful pupil identity) in the upper secondary school context.
Non-Contact Measurement Method of Phase Current Based on Magnetic Field Decoupling Calculation for Three-Phase Four-Core Cable
Authors: Suo Chunguang , Cheng Kang , Wang Lifeng , Zhang Wenbin , Liu Xi , Zhu Junyu
Published: March 2023

As one of the important parameters characterizing the cable’s operation status, an accurate measurement of the current is particularly important for the cable’s reliable operation and status monitoring. Aiming at the problem that the sum of the current phasors of multiphase cables is 0 when running in a steady state, and that the traditional mutual inductance current measurement method cannot be used for the phase current measurement of such cables, or that the insulation layer needs to be damaged, this paper proposes a non-contact measurement method of three-phase cable current, based on the magnetic field decoupling calculation. When combined with the actual parameters of the three-phase cable, the analytical calculation model of the magnetic field distribution of the three-phase cable is established. The relationship between the output ratio of the sensor and the deflection angle is obtained through theoretical derivation, the magnetic field coupling coefficient matrix is determined, and the transfer relationship between the output of the magnetic sensor and the current of each phase is clarified; an array magnetic field sensor is designed, which can sense the information of the adjacent magnetic field independently and is used for the reconstruction of three-phase currents. The effectiveness of the proposed method was tested on the built three-phase four-core cable current measurement test platform. The experimental results show that under the three-phase current balance, the measurement error of phase A, phase B and phase C is less than 2.8%, and the waveform and phase angle of the three-phase current can be well restored, which verifies the three-phase current measurement method proposed in this paper.
Nutrient Film Technique-Based Hydroponic Monitoring and Controlling System Using ANFIS
Authors: Vincentdo Vito , Surantha Nico
Published: March 2023

Most people are now aware of the importance of a healthy lifestyle, including the importance of consuming vegetables. As a result, the demand for vegetables has increased, and so their production needs to be increased. Currently, most plantations use soil as a growing medium, which is time-consuming and requires a significant amount of space. To modernize cultivation, hydroponic techniques should be adopted. However, implementing hydroponics can be challenging as it requires precise pH and nutrient adjustments. The previous research has proposed the hydroponic pH and nutrient control using the Sugeno fuzzy method. However, in Sugeno fuzzy method, there is no systematic procedure in designing the fuzzy controller, thus, the design relies on hydroponic expert knowledge. To address this issue, a smart hydroponic system was developed using the adaptive neuro-fuzzy inference system (ANFIS) method, which allows for automatic adjustments based on the collected dataset and remote control through internet of things (IoT) technology. This study showed that the system could accurately adjust pH and nutrient levels, allowing plants to grow better. Furthermore, the fuzzy controller created using ANFIS is 67% more accurate than creating the fuzzy controller using the Sugeno fuzzy method. Finally, the web application dashboard of the proposed system is also presented in this paper.
Friction Feedforward Compensation Composite Control of Continuous Rotary Motor with Sliding Mode Variable Structure Based on an Improved Power Reaching Law
Authors: Wang Xiaojing , Bai Bocheng , Feng Yaming
Published: March 2023

In order to meet the accuracy requirements and tracking performance of continuous rotary electro-hydraulic servo motor system under nonlinear uncertainty and strong disturbance factors, the sliding mode variable structure composite control strategy based on an improved power reaching law is proposed. Based on the principle of valve-controlled hydraulic motor, the state space model of the motor system is established, and a continuous friction model is adopted. Then, the genetic algorithm is used for parameter identification to determine the friction feedforward compensation scheme. In addition, an improved power reaching law is designed, which can adaptively adjust the system chattering according to the system state. The simulation results show that the sliding mode variable structure composite controller with the friction feedforward compensation can achieve a system frequency of 15 Hz, and tracking accuracy and response speed meet the double-decade index requirements, which improve the performance of continuous rotary electro-hydraulic servo motor.
Web Site Fingerprint Attack Generation Technology Combined with Genetic Algorithm
Authors: Bai Hanfeng , Yi Junkai , Chen Ruidong
Published: March 2023

An anonymous network can be used to protect privacy and conceal the identities of both communication parties. A website fingerprinting attack identifies the target website for the data access by matching the pattern of the monitored data traffic, rendering the anonymous network ineffective. To defend against fingerprint attacks on anonymous networks, we propose a novel adversarial sample generation method based on genetic algorithms. We can generate effective adversarial samples with minimal cost by constructing an appropriate fitness function to select samples, allowing us to defend against several mainstream attack methods. The technique reduces the accuracy of a cutting-edge attack hardened with adversarial training from 90% to 20–30%. It also outperforms other defense methods of the same type in terms of information leakage rate.
The Circular U-Net with Attention Gate for Image Splicing Forgery Detection
Authors: Peng Jin , Li Yinghao , Liu Chengming , Gao Xiaomeng
Published: March 2023

With the advent and rapid development of image tampering technology, it has become harmful to many aspects of our society. Thus, image tampering detection has been increasingly important. Although current forgery detection methods have achieved some success, the scale of the tampered areas in each forgery image are different, and previous methods do not take this into account. In this paper, we believe that the inability of the network to accommodate tampered regions of various sizes is the main reason for the low precision. To address the mentioned problem, we propose a neural network architecture called CAU-Net, which adds residual propagation and feedback, attention gate and Atrous Spatial Pyramid Pooling with CBAM to the U-Net. The Atrous Spatial Pyramid Pooling with CBAM can capture information from multiple scales and adapt to differently sized target areas. In addition, CAU-Net can solve the vanishing gradient issue and suppress the weight of untampered regions, and CAU-Net is an end-to-end network without redundant image processing; thus, it is fast to detect suspicious images. In the end, we optimize the proposed network structure by ablation study, and the experimental results and visualization results demonstrate that our network has a better performance on CASIA and NIST16 compared with state of the art methods.
Recognition of Lane Changing Maneuvers for Vehicle Driving Safety
Authors: Wu Yuming , Zhang Lei , Lou Ren , Li Xinghua
Published: March 2023

The increasing number of vehicles has caused traffic conditions to become increasingly complicated in terms of safety. Emerging autonomous vehicles (AVs) have the potential to significantly reduce crashes. The advanced driver assistance system (ADAS) has received widespread attention. Lane keeping and lane changing are two basic driving maneuvers on highways. It is very important for ADAS technology to identify them effectively. The lane changing maneuver recognition has been used to study traffic safety for many years. Different models have been proposed. With the development of technology, machine learning has been introduced in this field with effective results. However, models which require a lot of physical data as input and unaffordable sensors lead to the high cost of AV platforms. This impedes the development of AVs. This study proposes a model of lane changing maneuver recognition based on a distinct set of physical data. The driving scenario from the natural vehicle trajectory dataset (i.e., HighD) is used for machine learning. Acceleration and velocity are extracted and labeled as physical data. The normalized features are then input into the k-nearest neighbor (KNN) classification model. The trained model was applied to another set of data and received good results. The results show that based on the acceleration features, the classification accuracy of lane keeping (LK), lane changing to the left (LCL) and lane changing to the right (LCR) is 100%, 97.89% and 96.19%.
User Experience of Multi-Mode and Multitasked Extended Reality on Different Mobile Interaction Platforms
Authors: Choi Hyeonah , Jeong Heeyoon , Kim Gerard Jounghyun
Published: March 2023

“Extended Reality (XR)” refers to a unified platform or content that supports all forms of “reality”—e.g., 2D, 3D virtual, augmented, and augmented virtual. We explore how the mobile device can support such a concept of XR. We evaluate the XR user experiences of multi-mode and multitasking among three mobile platforms—(1) bare smartphone (PhoneXR), (2) standalone mobile headset unit (ClosedXR), and (3) smartphone with clip-on lenses (LensXR). Two use cases were considered through: (a) Experiment 1: using and switching among different modes within a single XR application while multitasking with a smartphone app, and (b) Experiment 2: general multitasking among different “reality” applications (e.g., 2D app, AR, VR). Results showed users generally valued the immersive experience over usability—ClosedXR was clearly preferred over the others. Despite potentially offering a balanced level of immersion and usability with its touch-based interaction, LensXR was not generally received well. PhoneXR was not rated particularly advantageous over ClosedXR even if it needed the controller. The usability suffered for ClosedXR only when the long text had to be entered. Thus, improving the 1D/2D operations in ClosedXR for operating and multitasking would be one way to weave XR into our lives with smartphones.