bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a deep learning pipeline to measure pericardial effusion in echocardiography
Authors: Cheng Chi-Yung , Wu Cheng-Ching , Chen Huang-Chung , Hung Chun-Hui , Chen Tien-Yu , Lin Chun-Hung Richard , Chiu I-Min 
Published: August 2023

ObjectivesThe aim of this study was to develop a deep-learning pipeline for the measurement of pericardial effusion (PE) based on raw echocardiography clips, as current methods for PE measurement can be operator-dependent and present challenges in certain situations.MethodsThe proposed pipeline consisted of three distinct steps: moving window view selection (MWVS), automated segmentation, and width calculation from a segmented mask. The MWVS model utilized the ResNet architecture to classify each frame of the extracted raw echocardiography files into selected view types. The automated segmentation step then generated a mask for the PE area from the extracted echocardiography clip, and a computer vision technique was used to calculate the largest width of the PE from the segmented mask. The pipeline was applied to a total of 995 echocardiographic examinations.ResultsThe proposed deep-learning pipeline exhibited high performance, as evidenced by intraclass correlation coefficient (ICC) values of 0.867 for internal validation and 0.801 for external validation. The pipeline demonstrated a high level of accuracy in detecting PE, with an area under the receiving operating characteristic curve (AUC) of 0.926 (95% CI: 0.902–0.951) for internal validation and 0.842 (95% CI: 0.794–0.889) for external validation.ConclusionThe machine-learning pipeline developed in this study can automatically calculate the width of PE from raw ultrasound clips. The novel concepts of moving window view selection for image quality control and computer vision techniques for maximal PE width calculation seem useful in the field of ultrasound. This pipeline could potentially provide a standardized and objective approach to the measurement of PE, reducing operator-dependency and improving accuracy.
Determination method of rock characteristic stresses based on the energy growth rate
Authors: Liu Xiaohui , Gui Xin , Qiu Xue , Wang You , Xue Yang , Zheng Yu 
Published: August 2023

Introduction: Precisely determining the characteristic stress value of a rock progressive failure process has important theoretical and practical significance for reasonably defining the rock deformation and failure stage, mechanical mechanism, and design parameters.Methods: Based on the energy characteristics in the process of rock deformation and failure, this paper proposes a new method of rock characteristic stress (EGR) around the index of elastic energy storage capacity, elastic energy growth rate, and dissipative energy growth rate. First, the rationality of the new method is verified by the indoor uniaxial and triaxial loading test data of coal and marble. Second, five different determination methods, namely, lateral strain method, lateral strain difference method, crack strain method, energy dissipation rate method, and volumetric strain method, are compared to further verify the scientific nature of the new method. Finally, the method is applied to the conventional triaxial unloading confining pressure test and true triaxial loading and unloading test of marble, and the new method is fully extended to verify its universality.Results: The results show that the theoretical basis of the EGR characteristic stress determination method is rigorous and sufficient, and the value process is objective and reasonable. Compared with different methods, the EGR method can accurately define the process of rock asymptotic failure, and its corresponding characteristic stress level is well-consistent and in a reasonable range.Discussion: The EGR method is applicable to the conventional triaxial unloading confining pressure test and true triaxial loading and unloading test and has good universality.
Glymphatic transport is reduced in rats with spontaneous pituitary tumor
Authors: Li Lian , Ding Guangliang , Zhang Li , Luo Hao , Davoodi-Bojd Esmaeil , Li Qingjiang , Chopp Michael , Zhang Zheng Gang , Jiang Quan 
Published: August 2023

Background and objectivePituitary tumor in patients induces adverse alterations in the brain, accompanied by cognitive deficits. Dysfunction of glymphatic waste clearance results in accumulation of neurotoxic products within the brain, leading to cognitive impairment. However, the status of glymphatic function in the brain with pituitary tumor is unknown. Using magnetic resonance imaging (MRI) and an advanced mathematical modeling, we investigated the changes of glymphatic transport in the rats carrying spontaneous pituitary tumor.MethodsRats (22–24 months, female, Wistar) with and without pituitary tumor (n = 7/per group) underwent the identical experimental protocol. MRI measurements, including T2-weighted imaging and dynamic 3D T1-weighted imaging with intracisternal administration of contrast agent, were performed on each animal. The contrast-induced enhancement in the circle of Willis and in the glymphatic influx nodes were observed on the dynamic images and verified with time-signal-curves (TSCs). Model-derived parameters of infusion rate and clearance rate that characterize the kinetics of glymphatic tracer transport were evaluated in multiple representative brain regions.ResultsOur imaging data demonstrated a higher incidence of partially enhanced circle of Willis (86 vs. 14%; p &lt; 0.033) and a lower incidence of enhancement in glymphatic influx nodes of pituitary (71 vs. 100%) and pineal (57 vs. 86%) recesses in the rats with pituitary tumor than in the rats with normal appearance of pituitary gland, indicating an intensification of impaired peri-vascular pathway and impeded glymphatic transport due to the presence of pituitary tumor. Consistently, our kinetic modeling and regional cerebral tissue quantification revealed significantly lower infusion and clearance rates in all examined regions in rats with spontaneous pituitary tumor than in non-tumor rats, representing a suppressed glymphatic transport in the brain with pituitary tumor.ConclusionOur study demonstrates the compromised glymphatic transport in the rat brain with spontaneous pituitary tumor. The reduced efficiency in cerebral waste clearance increases the risk for neurodegeneration in the brain that may underlie the cognitive impairment commonly seen in patients with pituitary tumors.
Molecular epidemiology and antibiotic resistance of staphylococci other than Staphylococcus aureus in children in Cape Town, South Africa
Authors: Ocloo Remous , Newton-Foot Mae , Ziebuhr Wilma , Whitelaw Andrew Christopher 
Published: August 2023

IntroductionStaphylococci other than Staphylococcus aureus (SOSA) have emerged as significant pathogens in healthcare settings, particularly among patients with indwelling devices and immunocompromised individuals. Staphylococcus epidermidis, Staphylococcus haemolyticus and Staphylococcus hominis are the most common commensal SOSA species and are implicated in infections such as endocarditis and bacteremia. SOSA infections in neonates and children have been reported globally. Recent increases in antibiotic resistance and virulence among SOSA strains in clinical settings have highlighted the need to describe the reservoirs of SOSA to enable monitoring of these emerging pathogens.MethodsStool samples were collected from 150 healthy children from Cape Town communities between 2017 and 2020. Staphylococci were isolated, identified using mass-spectrometry, and antimicrobial susceptibility testing and Illumina whole genome sequencing were performed.ResultsAmong the participants, 50 (33.3%) were colonized by SOSA, with S. haemolyticus (n = 38; 25.3%) being the most common, followed by S. hominis (n = 5; 3.3%) and Mammalicoccus sciuri (n = 5; 3.3%). Out of the 77 initially isolated S. haemolyticus strains, 23 were identified as Staphylococcus borealis through whole genome sequencing. All S. haemolyticus isolates (n = 49) were methicillin resistant, with 65.3% (n = 32) harbouring mecA. In S. haemolyticus, SCCmec type VIII(4A) was detected in 42.0% of ST9 isolates while non-mecA methicillin resistant S. haemolyticus isolates were mostly ST49 (41.1%). Additionally, 16 (50.0%) S. haemolyticus strains contained non-typeable SCCmec elements.DiscussionHigh rates of methicillin resistance were identified among colonizing SOSA in Cape Town, increasing the risk of transmission to clinical settings. This study also identified a new species, S. borealis, for the first time in Africa.
Semantic intrusion errors are associated with plasma Ptau-181 among persons with amnestic mild cognitive impairment who are amyloid positive
Authors: Curiel Cid Rosie E. , Ortega Alexandra , Crocco Elizabeth A. , Hincapie Diana , McFarland Karen N. , Duara Ranjan , Vaillancourt David , DeKosky Steven T. , Smith Glenn , Sfakianaki Efrosyni , Rosselli Monica , Barker Warren W. , Adjouadi Malek , Barreto Yarlenis , Feito Yuleidys , Loewenstein David A. 
Published: August 2023

IntroductionSemantic intrusion errors (SI) have distinguished between those with amnestic Mild Cognitive Impairment (aMCI) who are amyloid positive (A+) versus negative (A−) on positron emission tomography (PET).MethodThis study examines the association between SI and plasma – based biomarkers. One hundred and twenty-eight participants received SiMoA derived measures of plasma pTau-181, ratio of two amyloid-β peptide fragments (Aβ42/Aβ40), Neurofilament Light protein (NfL), Glial Fibrillary Acidic Protein (GFAP), ApoE genotyping, and amyloid PET imaging.ResultsThe aMCI A+ (n = 42) group had a higher percentage of ApoE ɛ4 carriers, and greater levels of pTau-181 and SI, than Cognitively Unimpaired (CU) A− participants (n = 25). CU controls did not differ from aMCI A− (n = 61) on plasma biomarkers or ApoE genotype. Logistic regression indicated that ApoE ɛ4 positivity, pTau-181, and SI were independent differentiating predictors (Correct classification = 82.0%; Sensitivity = 71.4%; Specificity = 90.2%) in identifying A+ from A− aMCI cases.DiscussionA combination of plasma biomarkers, ApoE positivity and SI had high specificity in identifying A+ from A− aMCI cases.
The influence of a maternal vegan diet on carnitine and vitamin B2 concentrations in human milk
Authors: Juncker Hannah G. , van den Akker Chris H. P. , Meerdink Pauline L. , Korosi Aniko , Vaz Frédéric M. , van Goudoever Johannes B. , van Keulen Britt J. 
Published: August 2023

BackgroundThe maternal diet greatly influences the nutritional composition of human milk. With the rise of vegan diets by lactating mothers, there are concerns about the nutritional adequacy of their milk. Two important nutrients, vitamin B2 and carnitine, are mostly ingested via animal products.ObjectiveWe investigated the influence of a vegan diet on the vitamin B2 and carnitine concentrations in milk and serum of lactating women.MethodsIn this case–control study, 25 lactating mothers following an exclusive vegan diet were comparted to 25 healthy lactating mothers with an omnivorous diet without use of supplements. High-performance liquid chromatography and liquid chromatography–tandem mass spectrometry were used to measure vitamin B2 and carnitine concentrations, respectively. A linear regression model was used to determine differences in human milk and serum concentrations between study groups.ResultsVitamin B2 concentrations in human milk and serum did not differ between study groups. While the human milk free carnitine (C0) and acetyl carnitine (C2) concentrations did not differ between study groups, serum carnitine concentrations were lower in participants following a vegan diet than in omnivorous women (p &lt; 0.0001).ConclusionA maternal vegan diet did not affect human milk concentration of vitamin B2 and carnitine. Breastfed infants of mothers following an exclusive vegan diet therefore are likely not at increased risk of developing a vitamin B2 or carnitine deficiency.
Machine learning models-based on integration of next-generation sequencing testing and tumor cell sizes improve subtype classification of mature B-cell neoplasms
Authors: Mu Yafei , Chen Yuxin , Meng Yuhuan , Chen Tao , Fan Xijie , Yuan Jiecheng , Lin Junwei , Pan Jianhua , Li Guibin , Feng Jinghua , Diao Kaiyuan , Li Yinghua , Yu Shihui , Liu Lingling 
Published: August 2023

BackgroundNext-generation sequencing (NGS) panels for mature B-cell neoplasms (MBNs) are widely applied clinically but have yet to be routinely used in a manner that is suitable for subtype differential diagnosis. This study retrospectively investigated newly diagnosed cases of MBNs from our laboratory to investigate mutation landscapes in Chinese patients with MBNs and to combine mutational information and machine learning (ML) into clinical applications for MBNs, especially for subtype classification.MethodsSamples from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database were collected for ML model construction and cases from our laboratory were used for ML model validation. Five repeats of 10-fold cross-validation Random Forest algorithm was used for ML model construction. Mutation detection was performed by NGS and tumor cell size was confirmed by cell morphology and/or flow cytometry in our laboratory.ResultsTotally 849 newly diagnosed MBN cases from our laboratory were retrospectively identified and included in mutational landscape analyses. Patterns of gene mutations in a variety of MBN subtypes were found, important to investigate tumorigenesis in MBNs. A long list of novel mutations was revealed, valuable to both functional studies and clinical applications. By combining gene mutation information revealed by NGS and ML, we established ML models that provide valuable information for MBN subtype classification. In total, 8895 cases of 8 subtypes of MBNs in the COSMIC database were collected and utilized for ML model construction, and the models were validated on the 849 MBN cases from our laboratory. A series of ML models was constructed in this study, and the most efficient model, with an accuracy of 0.87, was based on integration of NGS testing and tumor cell sizes.ConclusionsThe ML models were of great significance in the differential diagnosis of all cases and different MBN subtypes. Additionally, using NGS results to assist in subtype classification of MBNs by method of ML has positive clinical potential.
Efficacy of lung cancer screening at the American University of Beirut Medical Center
Authors: Harb Tarek , Alhafi Anas , Tfayli Arafat H. 
Published: August 2023

IntroductionIn Lebanon, a dedicated screening program for lung cancer is absent. Screening is largely based on the recommendation of an informed physician or the initiative of a patient. To better understand the situation, it is important to look at the available data on patients currently being screened for lung cancer in this country. Our aim in this study is to review the data and compare it with that in the literature as well as to assess the efficacy of the screening process followed.MethodsOur study accessed the electronic medical records of patients at the American University of Beirut Medical Center (AUBMC), a tertiary care center in Lebanon. We collected information on patients who underwent screening low-dose computed tomography (LDCT) scan between June 2019 and June 2021 inclusive. Records of all patients who underwent a non-contrast computed tomography (CT) scan at AUBMC during this period were collected and analyzed.ResultsOn average, our population had a 52.6 pack-year smoking history. Moreover, 47% of our population had an accurate pack-year reported, while 12% did not have enough information to even estimate their pack-year history. When looking at the accurate and estimated data, 5% of our population did not even meet the ≥20 pack-year smoking history. Eight patients had positive findings on the screening LDCT, which we defined as suspicious findings that require further workup (e.g., PET/CT or biopsy) or other significant incidental findings.ConclusionA well-organized program for lung cancer screening in Lebanon is absent. Screening largely depends on the initiative of the physician or the patient. We were able to uncover multiple flaws in the screening method used, including poor documentation and follow-up. Although the screening method adopted retained some benefits in terms of detecting early malignancy, it lacked proper organization and was not ideal. A better, systematized screening program is needed to have optimal outcomes.
Multimodal imaging features of primary pericardial synovial sarcoma: a case report
Authors: Jin Hongrui , Zhang Yong , Zhang Wenbo , Wang Keyan 
Published: August 2023

BackgroundPrimary pericardial synovial sarcoma is an extremely rare malignant tumor, and affected patients have a poor prognosis. Only a few cases have been reported in the literature.Case summaryA 34-year-old man was admitted to our hospital with chest tightness and a cough. An echocardiogram revealed a heterogeneous mass with a large pericardial effusion. Further computed tomography (CT) of the chest and cardiac magnetic resonance imaging (CMRI) demonstrated an irregular pericardial mass abutting the left atrium and left ventricle and invading the mediastinal structures. Pathology results showed that the tumor was a monophasic synovial sarcoma. The patient underwent chemotherapy and survived for 17 months.DiscussionMany cardiac tumors are clinically asymptomatic or nonspecific, and they are frequently detected or diagnosed at an advanced stage of the disease. Multimodal cardiac imaging facilitates the detection and assessment of cardiac tumors. In particular, CMRI is considered as a superior imaging tool, because it provides high tissue contrast and can detect invasion of the myocardium. We describe the clinical details and multimodal imaging features of a rare primary pericardial synovial sarcoma, hoping to provide guidance for the diagnosis of similar cases in the future.
Quantitative analysis of chest MRI images for benign malignant diagnosis of pulmonary solid nodules
Authors: Yang Bin , Gao Yeqi , Lu Jie , Wang Yefu , Wu Ren , Shen Jie , Ren Jialiang , Wu Feiyun , Xu Hai 
Published: August 2023

BackgroundIn this study, we developed and validated machine learning (ML) models by combining radiomic features extracted from magnetic resonance imaging (MRI) with clinicopathological factors to assess pulmonary nodule classification for benign malignant diagnosis.MethodsA total of 333 consecutive patients with pulmonary nodules (233 in the training cohort and 100 in the validation cohort) were enrolled. A total of 2,824 radiomic features were extracted from the MRI images (CE T1w and T2w). Logistic regression (LR), Naïve Bayes (NB), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) classifiers were used to build the predictive models, and a radiomics score (Rad-score) was obtained for each patient after applying the best prediction model. Clinical factors and Rad-scores were used jointly to build a nomogram model based on multivariate logistic regression analysis, and the diagnostic performance of the five prediction models was evaluated using the area under the receiver operating characteristic curve (AUC).ResultsA total of 161 women (48.35%) and 172 men (51.65%) with pulmonary nodules were enrolled. Six important features were selected from the 2,145 radiomic features extracted from CE T1w and T2w images. The XGBoost classifier model achieved the highest discrimination performance with AUCs of 0.901, 0.906, and 0.851 in the training, validation, and test cohorts, respectively. The nomogram model improved the performance with AUC values of 0.918, 0.912, and 0.877 in the training, validation, and test cohorts, respectively.ConclusionMRI radiomic ML models demonstrated good nodule classification performance with XGBoost, which was superior to that of the other four models. The nomogram model achieved higher performance with the addition of clinical information.
Identifying clinicopathological risk factors for regional lymph node metastasis in Chinese patients with T1 breast cancer: a population-based study
Authors: Liu Gang , Xing Zeyu , Guo Changyuan , Dai Qichen , Cheng Han , Wang Xiang , Tang Yu , Wang Yipeng 
Published: August 2023

ObjectivesTo analyze clinicopathological risk factors and regular pattern of regional lymph node metastasis (LNM) in Chinese patients with T1 breast cancer and the effect on overall survival (OS) and disease-free survival (DFS).Materials and methodsBetween 1999 and 2020, breast cancer patients meeting inclusion criteria of unilateral, no distant metastatic site, and T1 invasive ductal carcinoma were reviewed. Clinical pathology characteristics were retrieved from medical records. Survival analysis was performed using Kaplan−Meier methods and an adjusted Cox proportional hazards model.ResultsWe enrolled 11,407 eligible patients as a discovery cohort to explore risk factors for LNM and 3484 patients with stage T1N0 as a survival analysis cohort to identify the effect of those risk factors on OS and DFS. Compared with patients with N- status, patients with N+ status had a younger age, larger tumor size, higher Ki67 level, higher grade, higher HR+ and HER2+ percentages, and higher luminal B and HER2-positive subtype percentages. Logistic regression indicated that age was a protective factor and tumor size/higher grade/HR+ and HER2+ risk factors for LNM. Compared with limited LNM (N1) patients, extensive LNM (N2/3) patients had larger tumor sizes, higher Ki67 levels, higher grades, higher HR- and HER2+ percentages, and lower luminal A subtype percentages. Logistic regression indicated that HR+ was a protective factor and tumor size/higher grade/HER2+ risk factors for extensive LNM. Kaplan−Meier analysis indicated that grade was a predictor of both OS and DFS; HR was a predictor of OS but not DFS. Multivariate survival analysis using the Cox regression model demonstrated age and Ki67 level to be predictors of OS and grade and HER2 status of DFS in stage T1N0 patients.ConclusionIn T1 breast cancer patients, there were several differences between N- and N+ patients, limited LNM and extensive LNM patients. Besides, HR+ plays a dual role in regional LNM. In patients without LNM, age and Ki67 level are predictors of OS, and grade and HER2 are predictors of DFS.
Comprehensive studies on the electrical transport of some chalcogenide semiconductors: frequency- and temperature-dependent AC conductivity
Authors: Ojha Swarupa , Chamuah Anil , Roy Madhab , Bhattacharya Sanjib 
Published: August 2023

The AC conductivity of chalcogenide semiconductors doped with Ag2S was extensively studied, not only for applications in devices but also for academic interests. X-ray diffraction studies reveal the presence of GeS, Ag2S, Se5.1S1.9, Se2.57S5.43, Ag2Se, S3Se5, Se4.7S3.3, and Ag8S nanocrystallites. The characteristic vibration that appeared in the range 500–600 cm−1 is due to the Ag–S bond, and the vibrations at 3,700 and 1600 cm−1 can be assigned as the bending and stretching vibrations of the O–H bond, which may be formed due to the adsorption of H2O molecules on the Ag2S surface. DC electrical conductivity can be increased by optical phonon frequency, which may be involved in the enhancement of structural vibrations. At low temperatures, the “density of states” increases from 3.337 × 1019 to 2.396 × 1021 eV−1 cm−3, and at high temperatures, it enhances from 3.417 × 1028 to 1.1356 × 1031 eV– 1 cm−3. The correlated barrier hopping model explores the maximum barrier height for composition, x = 0.1 as 0.0292 eV. The modified non-overlapping small polaron tunnelling model reveals the polaron transfer activation energy for x = 0.2 as 0.09110 eV. The independence of the electrical relaxation process of the system on temperature and its dependence on composition were exhibited by the scaling of the conductivity spectra.