bluuebunny/crossref_metadata_2025 huggingface dataset:
Lower estimates of myocardial perfusion are associated with greater aortic perivascular adipose tissue density in humans independent of aortic stiffness
Authors: Carlini Nicholas A. , Harber Matthew P. , Fleenor Bradley S.
Published: August 2024

Aortic perivascular adipose tissue (aPVAT) density is associated with age-related aortic stiffness in humans and therefore, may contribute to cardiovascular dysfunction. A lower subendocardial viability ratio (SEVR), an estimate of myocardial perfusion, indicates greater cardiovascular disease (CVD) risk and is associated with aortic stiffness in clinical populations. However, the influence of aortic stiffness on the relation between aPVAT density and SEVR/cardiovascular (CV) hemodynamics in apparently healthy adults are unknown. We hypothesize greater aPVAT density will be associated with lower SEVR and higher CV hemodynamics independent of aortic stiffness. Fourteen (6M/8F, mean age 55.4 ± 5.6 y, body mass index 25.5 ± 0.6 kg/m2) adults completed resting measures of myocardial perfusion (SEVR), CV hemodynamics (pulse wave analysis), aortic stiffness (carotid-femoral pulse wave velocity [cfPWV]), and a computed tomography scan to acquire aPVAT and visceral adipose tissue (VAT) density. Greater aPVAT density (i.e. higher density) was associated with lower SEVR (r=-0.78, p<0.001) and a higher systolic pressure time integral (r=0.49, p=0.03), forward pulse height (r=0.49, p=0.03), reflected pulse height (r=0.55, p=0.02), ejection duration (r=0.56, p=0.02) and augmentation pressure (r=0.69, p=0.003), but not with the diastolic pressure time integral (r=-0.22, p=0.22). VAT density was not associated with SEVR or any CV hemodynamic endpoints (all, p>0.05). Further, the relation between aPVAT density and SEVR remained after adjusting for aortic stiffness (r=-0.66, p=0.01) but not age (r=-0.24, p>0.05). These data provide initial evidence for aPVAT as a novel yet understudied local fat depot contributing to lower myocardial perfusion in apparently healthy adults with aging.
Electrical Impedance Dermography: Background, Current State, and Emerging Clinical Opportunities
Authors: Brunsgaard Elise K. , Sanchez Benjamin , Grossman Douglas
Published: August 2024

Electrical impedance dermography (EID), based on electrical impedance spectroscopy, is a specific technique for the evaluation of skin disorders that relies upon the application and measurement of painless, alternating electrical current. EID assesses pathological changes to the normal composition and architecture of the skin that influence the flow of electrical current, including changes associated with inflammation, keratinocyte and melanocyte carcinogenesis, and scarring. Assessing the electrical properties of the skin across a range of frequencies and in multiple directions of current flow can provide diagnostic information to aid in the identification of pathologic skin conditions. EID holds the promise of serving as a diagnostic biomarker and potential to be used in skin cancer detection and staging. EID may also be useful as a biomarker in monitoring effectiveness of treatment in individual patients and in therapeutic research. This review highlights ongoing efforts to improve mechanistic understanding of skin electrical changes, study of EID in a variety of clinical contexts, and further refine the technology to find greater clinical use in dermatology and dermatologic research.
Research on the Energy Dissipation Patterns and Fragment Size Distribution Characteristics of Coal Under Cyclic Impact Loading With Confining Pressure
Authors: Yongliang He , Yuping Fu , Chuantian Li , Liying Sun , Dongya Zhang
Published: August 2024

This study examines energy dissipation patterns and failure mechanisms in coal under cyclic impact, crucial for preventing dynamic disasters like rock bursts and coal and gas outbursts. Using a 75‐mm split Hopkinson pressure bar (SHPB) experimental system, the dynamic mechanical characteristics and fragment size distribution patterns of coal samples were analysed under a confining pressure of 10 MPa, axial pressure of 12 MPa, and impact pressures of 0.25, 0.30, 0.35, 0.40, and 0.45 MPa for 1, 2, and 3 cycles. The experimental data indicate that as the number of impacts increases, the energy reflected by the coal samples gradually increases, while the transmitted energy correspondingly decreases. The energy absorbed per unit volume of the coal samples under the first, second, and third dynamic loading cycles and confining pressure is 0.56, 0.61, and 0.66 J/cm3, respectively, with energy absorption rates ranging from 16.2% to 33.8%. Under different impact pressures, the fractal dimension of coal fragmentation shows a linear change, and as the impact pressure increases, the degree of fragmentation intensifies, and the mass of the fragmented coal decreases. The strength reduction in the energy dissipation patterns of coal samples under dynamic loading provides important theoretical support for the prevention of rock bursts during coal mining.
Molecular Signature of miR‐34a/NEAT‐1/p53 Axis in Mycosis Fungoides
Authors: Fares Reham , Elasmer Shimaa M. , A. Abeer Khalefa , Shaker Olfat G. , El-Tahlawi Samar M. , Sabri Ahmed , Yaseen Sara M.
Published: August 2024

Background. Mycosis fungoides (MF) is a type of cutaneous T‐cell lymphoma where red rash exists on the skin. Understanding the role of miRNAs and ncRNAs in p53‐response has become an open discussion, as they can regulate p53 or its downstream targets, and ncRNAs themselves. Objectives. To evaluate the serum levels of NEAT‐1, miR‐34a, and p53 in MF patients and its relation to healthy controls to indicate whether it has a potential role in the pathogenesis of the disease. Subjects and Methods. This prospective case‐control study was carried out on 75 subjects subdivided into two groups, 35 MF patients (stages 1 and II) and 40 matched healthy controls. Their clinical investigations and serum biomarkers (NEAT‐1, miR‐34a, and p53) were measured. Results. There were significant elevations in the expression levels of both NEAT‐1 (5.10 ± 1.16) and p53 (277.28 ± 62.02) in the serum of MF patients in comparison with controls (1.01 ± 0.031) and (194.29 ± 16.039), respectively, while the level of miR‐34a tends to decrease in MF patients (0.24 ± 0.15). There are no significant difference between MF stages and the level of miR‐34a, while in NEAT‐1 and p53, there are significant differences with p value <0.05 between the stages and the biomarkers. There is a positive correlation between the %BSA and miR‐34a and a slightly positive correlation between NEAT‐1 and P53 with (r = 0.353, p = 0.037) and (r = 0112, p = 0.05), respectively. There were also negative correlations between disease duration and NEAT‐1 with (r = −0.341, p = 0.045) and between B2 microglobulin level and p53 (r = −0.373, p = 0.027). Conclusion. The combination of miR‐34a, NEAT‐1, and p53 may be considered as potential biomarkers that play an active role in the disease process of MF for helping in its early diagnosis and stage identification as well.
An Intelligent Two‐Stage Fault Classification Model for Railway Turnout Systems Based on FastDTW
Authors: Sun Huasheng , Fu Yingguo , Zhang Sizhong , Yang Zhongqun , Guo Fangmao , Li Linfeng , Liu Jianyang
Published: August 2024

The identification and classification of railway turnout faults are essential for guaranteeing train safety. Traditional diagnostic methods for these faults face challenges due to limited accuracy, stemming from the scarcity of fault samples, and often fail to provide detailed fault classification. In response to these issues, we introduce an advanced two‐stage model for the classification of railway turnout faults, utilizing the FastDTW algorithm, known for its efficient approximation of DTW (dynamic time warping) with linear time and space complexity. In the first stage, we employ a Shapelets feature extraction algorithm, based on a greedy strategy, to efficiently identify the most representative segments from long sequence action curves. Progressing to the second stage, the model tackles the inherent singularities in the FastDTW algorithm by incorporating a novel curve segmentation technique, also rooted in a greedy strategy. This technique fine‐tunes the fault classification process, leading to more accurate outcomes. The effectiveness and precision of our proposed model were validated empirically using a dataset of 540 faulty curves from a specific high‐speed railway station, achieving an impressive classification accuracy of 97%. This substantial accuracy in fault curve classification underscores the potential of our model to significantly enhance the safety and efficiency of railway operations, marking a notable advancement in the field of railway turnout fault classification.
Influential Factors on Smoking and Drinking Behavior: Health Literacy among Adolescents from the Hill Tribe Communities, Thailand
Authors: Sopajaree Chompunut , Mitkitti Ratchanee , Tonkuriman Asawinee , Moonpanane Katemanee
Published: August 2024

Purpose. This study examines smoking and alcohol use among disadvantaged Hill tribe adolescents (12–19 years old) in northern Thailand. We use Leininger’s theory to better understand how cultural norms, health literacy, and perceived impacts influence these behaviors. Methods. The study utilized a cross‐sectional approach and involved 324 participants. Data were collected using standardized questionnaires (Thai‐AUDIT, FTND) to assess substance use and health literacy. Focus group discussions provided further insights into cultural norms and the impacts of such behaviors. Results. Over half (51.2%) of participants reported ever consuming alcohol, and 20.10% currently smoke cigarettes. Health literacy levels were adequate across all subgroups. Multiple regression analyses with a hierarchical approach identified the cultural and social factors including age at first drinking (β = −0.34, t = −2.68, p = 0.01) and factors related to the impact of past usage (impact on one’s health: β = −0.33, t = −2.48, p = 0.01, and impact on deep feelings: β = −0.33, t = −2.33, p = 0.02), which accounted for 18.2% of the variance in current alcohol consumption frequency (adjusted R2 = 0.182, F = 3.04, p = 0.01). The analysis revealed that there was no statistically significant relationship between age at first smoking and the current amount of cigarettes (β = −0.01, p = 0.15). As expected, health literacy was shown as the only predictor that significantly predicted the current amount of cigarettes (β = −0.40, p = 0.003), accounting for 14.1% of the current amount of cigarettes (adjusted R2 = 0.141, F = 4.08, p = 0.05). Conclusion. The results provide further evidence that the standard intervention is not appropriate for utilization with this specific group. Therefore, we propose a multifaceted culturally appropriate approach that integrates the insights derived from the focus group discussion while currently targeting health literacy, alcohol attitudes, and early substance use prevention through family and community awareness initiatives.
Rapid Screening of 300 Pesticide Residues in Commercially Available Vegetable‐, Fruit‐, and Cereal‐Based Baby Foods by Using Amino‐Functionalized Multiwalled Carbon Nanotubes with QuEChERS and Gas Chromatography‐Electrostatic Field Orbitrap High‐Resolution Mass Spectrometry
Authors: Meng Zhijuan , Fan Sufang , Ding Tongtong , Yuan Xiaoxuan , Zhao Limin , Li Qiang , Zhang Yan
Published: August 2024

A new method for screening 300 pesticide residues in fruit‐, vegetable‐, and cereal‐based baby foods by an improved QuEChERS purification method based on amino‐functionalized multiwalled carbon nanotubes (NH2‐MWCNTs) combined with gas chromatography‐electrostatic field orbitrap high‐resolution mass spectrometry (Orbitrap GC‐MS) was developed. The samples were extracted with acetonitrile (dry sample soaked in water first for activation), purified by dispersed solid phase extraction (d‐SPE) tube modified by NH2‐MWCNTs, and detected by Orbitrap GC‐MS. Qualitative analysis was carried out by retention time and accurate mass measurements in full scan mode, and external standard method for quantitation was performed using matrix‐matched standard calibration, which could effectively eliminate matrix interference. Method validation was performed on commercially available fruit‐, vegetable‐, and cereal‐based baby foods. Good linearity was achieved for 300 pesticides in the concentration range of 5 to 500 μg/kg with correlation coefficients greater than 0.995 0. The limits of detection (LOD) were 0.3–3.0 μg/kg, and the limits of quantification (LOQ) were 1.0–10.0 μg/kg. The average recoveries on 10, 50, and 200 μg/kg spiked levels were in the range of 72.8%–123.4% in three types of samples, with relative standard deviations (RSDs) of 2.0%–13.3%. The proposed method, with simple pretreatment, highly sensitivity, high precision, and accuracy, is suitable for simultaneous analysis of 300 pesticide residues in baby foods. This method provides a reference for accurate screening of low pesticide residues in baby food.
Point Prevalence Survey of Antimicrobial Use among Hospitalized Patients in a Referral Hospital in Northwest Ethiopia: A Hospital‐Based Cross‐Sectional Study
Authors: Gobezie Mengistie Yirsaw , Hassen Minimize , Tesfaye Nuhamin Alemayehu , Demessie Mulat Belete , Solomon Tewodros , Alemayehu Ermiyas
Published: August 2024

Background. Globally, imprudent consumption practices contribute to the widespread threat of antimicrobial resistance (AMR). Standardized monitoring of antibiotic use is essential to combat AMR, yet few studies in sub‐Saharan Africa, including Ethiopia, have utilized the World Health Organization (WHO) point‐prevalence survey (PPS) methodology to examine antimicrobial use. Our setting lacks sufficient national data on this issue. This study aimed to examine the prevalence of antimicrobial use, common antimicrobial drug types, and indications for antimicrobial use in a major public hospital. Methodology. A cross‐sectional PPS study design conducted in a hospital setting was utilized to explore the usage of antimicrobials in the adult wards of Felege Hiwot Comprehensive Specialized Hospital (FHCSH), employing the WHO‐PPS methodology. The research was carried out between December 24th and 26th, 2022. All patients present in a hospital ward at 8 : 00 am on the designated survey day were included. Data were gathered through a combination of reviewing patients′ medical records and conducting interviews with the attending physicians. Results. A total of 410 hospitalized patients were surveyed, out of which 258 (62.9%) patients were treated with at least one antimicrobial on the date of PPS. All antimicrobials were prescribed empirically. The most common indication for the therapeutic use of antimicrobials was community‐acquired infections (166, 64.3%). The top three wards with a large number of antimicrobial prescriptions were the surgical (158, 42.5%), medical (144, 38.7%), and gynecology (55, 14.8%) wards. Ceftriaxone was the most frequently used antibiotic (35%) in all the wards. The mean number of antimicrobials prescribed to the patient was 1.44. Of the prescribed 372 antimicrobials, 60.1% belonged to the WHO watch group. Conclusion. Our findings indicate that a significant number of patients received at least one antimicrobial during the point‐prevalence survey (PPS). Empirical prescriptions for community‐acquired infections were prevalent. These results underscore the need for robust antimicrobial stewardship programs in Ethiopian hospitals.
Mortality Prediction in COVID‐19 Using Time Series and Machine Learning Techniques
Authors: Akter Tanzina , Hossain Md. Farhad , Ullah Mohammad Safi , Akter Rabeya
Published: August 2024

Predicting mortality in COVID‐19 is one of the most significant and difficult tasks at hand. This study compares time series and machine learning methods, including support vector machines (SVMs) and neural networks (NNs), to forecast the mortality rate in seven countries: the United States, India, Brazil, Russia, France, China, and Bangladesh. Data were gathered between December 31, 2019, when COVID‐19 began, and March 31, 2021. The study used 457 observations with 4 variables: daily confirmed cases, daily deaths, daily mortality rate, and date. To predict the death rate in the seven countries that were chosen, the data were analyzed using time series analysis and machine learning techniques. Models were compared to obtain more accurate mortality predictions. The autoregressive integrated moving average (ARIMA) model with the lowest AIC value for each nation is found through time series analysis. By increasing the hidden layer and applying machine learning techniques, the NN model for each country is chosen, and the optimal model is determined by determining the model with the lowest error value. Additionally, SVM analyzes every country and calculates its R2 and root‐mean‐square error (RMSE). The lowest RMSE value is used to compare all of the time series and machine learning models. According to the comparison table, SVM provides a more accurate model to predict the mortality rate of the seven countries, with the lowest RMSE value. During the study period, mortality rates increased in Brazil and Russia and decreased in the United States, India, France, China, and Bangladesh, according to the comparison value of RMSE in this study. Furthermore, this paper shows that SVM outperforms all other models in terms of performance. According to the author’s analysis of the data, SVM is a machine learning technique that can be used to accurately predict mortality in a pandemic scenario.
Explication of Pharmacological Proficiency of Phytoconstituents from Adansonia digitata Bark: An In Vitro and In Silico Approaches
Authors: P. Sangavi , S. Gowtham Kumar , KT. Nachammai , Selvaraj Chandrabose , K. Langeswaran
Published: August 2024

Compared to other drug discovery sources, traditional medicine has significantly contributed to developing innovative therapeutic molecules for preventive and curative medicine. The Baobab tree, also known as Adansonia digitata L., is significant in Africa due to its multitude of benefits and various parts that serve different purposes, providing economic support to rural communities. The analysis of a plant sample using Fourier transform infrared (FT‐IR) spectroscopy detected multiple functional groups, such as carboxyl and aromatic groups. Additionally, gas chromatography‐mass spectroscopy (GC‐MS) was utilized to identify various compounds present in the sample, including tetrachloroethylene and octyl ester. The results of different assays, such as α‐diphenyl‐β‐picrylhydrazyl (DPPH), superoxide, nitric oxide scavenging assays, and total antioxidant by thiobarbituric acid method (TBA) and ferric thiocyanate (FTC) method, demonstrated a substantial scavenging of free radicals and an effective antioxidant efficacy. The bark’s antimicrobial activity was tested through agar diffusion, resulting in a range of zone of inhibition from 10.1 ± 0.36 mm to 20.85 ± 0.76 mm. The minimum inhibitory concentration (MIC) value was observed to be approximately 0.625 µg/mL. The biofilm inhibition percentage ranged from 9.89% to 57.92%, with the highest percentage being 57.92%. The GC‐MS and FT‐IR studies revealed phytocompounds, which were then analyzed for their potential therapeutic properties. Computational studies were conducted on the phytocompounds against Pseudomonas aeruginosa and C2 kinase (antioxidant). The study concluded that the Adansonia digitata bark extract and its phytocompound have potential therapeutic efficacy against the target proteins. The best docking scores were about −7.053 kcal/mol and −7.573 kcal/mol for Pseudomonas aeruginosa and C2 kinase (antioxidant), respectively. The interaction patterns with the crucial amino acid residues elucidate the inhibitory efficacy of the phytocompounds.
The Hepatoprotective Possessions of Specific Iranian Medicinal Plants
Authors: Dini Salome , Singh Shubhra , Fatemi Faezeh
Published: August 2024

With its historical roots, Iranian traditional medicine has played a significant role in addressing liver‐related disorders and providing alternative approaches to synthetic drugs. Liver‐related disorders, such as hepatitis, liver cirrhosis, and nonalcoholic fatty liver disease, pose significant health challenges worldwide. From traditional practices and indigenous knowledge, Iranian traditional medicine offers a holistic approach to liver health. It emphasizes the importance of lifestyle modifications, including dietary adjustment, physical activity, and stress reduction, to support liver function and restore balance within the body. This review collects from different databases, mainly Google Scholar, ScienceDirect, and SID. It focused on medicinal plants that are recommended in Iranian traditional medicine and scientifically proved to have liver protection properties as well as summarized our 10 years of experience in this field. This comprehensive article is an effort to study the integration of traditional knowledge with modern evidence‐based practices that can contribute to a comprehensive understanding of Iranian medicine’s potential in managing liver‐related disorders. Iranian traditional medicine incorporates many natural remedies derived from medicinal plants, minerals, and animal products. These remedies are often used in the form of herbal preparations, decoctions, and dietary supplements. Specific plants include Zataria multiflora, Satureja spp., Heracleum persicum, Carum carvi, Ferula spp., Hypericum scabrum, and Archillae spp. They are known for their hepatoprotective properties and are commonly employed in the management of liver disorders in Iranian traditional medicine. This traditional treatment provides a unique perspective by offering natural approaches to liver health. Traditional remedies aim to minimize potential side effects associated with synthetic drugs while addressing the root causes of liver disorders.
Ideal Living Skin Equivalents, From Old Technologies and Models to Advanced Ones: The Prospects for an Integrated Approach
Authors: Riabinin Andrei , Pankratova Maria , Rogovaya Olga , Vorotelyak Ekaterina , Terskikh Vasiliy , Vasiliev Andrey
Published: August 2024

The development of technologies for the generation and transplantation of living skin equivalents (LSEs) is a significant area of translational medicine. Such functional equivalents can be used to model and study the morphogenesis of the skin and its derivatives, to test drugs, and to improve the healing of chronic wounds, burns, and other skin injuries. The evolution of LSEs over the past 50 years has demonstrated the leap in technology and quality and the shift from classical full‐thickness LSEs to principled new models, including modification of classical models and skin organoids with skin derived from human‐induced pluripotent stem cells (iPSCs) (hiPSCs). Modern methods and approaches make it possible to create LSEs that successfully mimic native skin, including derivatives such as hair follicles (HFs), sebaceous and sweat glands, blood vessels, melanocytes, and nerve cells. New technologies such as 3D and 4D bioprinting, microfluidic systems, and genetic modification enable achievement of new goals, cost reductions, and the scaled‐up production of LSEs.
Table 1 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Characteristics of patients with malignant mesothelioma
Supplementary Table 6 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

The association of immune cells and cellular neighborhood proportion with overall survival in all malignant mesothelioma (MM) as well as for malignant pleural mesothelioma (MPM) and malignant peritoneal mesothelioma (MPeM) separately.
Supplementary Table 5 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Comparison of cell type distributions between malignant pleural mesothelioma (MPM) and malignant peritoneal mesothelioma (MPeM) within the same histologic subtypes.
Supplementary Table 4 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Distribution of immune cells and tumor cells across different histologies in the malignant mesothelioma (MM) cohort.
Table S1 from Development and Application of Genetic Ancestry Reconstruction Methods to Study Diversity of Patient-Derived Models in the NCI PDXNet Consortium
Authors: Lott Paul C. , Chiu Katherine , Quino Juanita Elizabeth , Vang April Pangia , Lloyd Michael W. , Srivastava Anuj , Chuang Jeffrey H. , Carvajal-Carmona Luis G.
Published: August 2024

Populations of origin for unrelated individuals from the 1000 Genomes Phase III, GenomeAsia, and INMEGEN data used as reference populations to design a new SNPweights panel.
Supplementary Table 2 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Clinical features, cell count, tumor percentage, and density associated with each core, including marker percentage, density and intensity for each core.
Supplementary Figure 1 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Example of 7-plex healthy donor lymphoid tissue as a control and for validation. All channels combined as well as Individual marker channels (pCK: pan-cytokeratin).
Figure 5 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Analysis of cell types in MPM BAP1-high and BAP1-low tumor groups. A, Correlation between mean CD8+ (cytotoxic T-cell) and CD11c+ (DC) intensities and mean BAP1 expression levels. Dots are color-coded by histologic subtypes. B, Ridge density plot illustrating tumor and CD8+ T cell contact scores among BAP1-high and BAP1-low pan-CK–enriched cores (cores with CK percent>20%). Density values >0.6 quantile and <0.4 quantile were used as thresholds to categorize cores as BAP1-high and BAP1-low, respectively. C and D, Segmented images show increased interaction between cancer cells and CD8+ T cells in BAP1-low MPM (D) compared with BAP1-high MPM (C). Top, TMA core sections stained with H&E, in which BAP1 is represented in Opal 690 (red); NF2 in Opal 780 (orange); MTAP in Opal 620 (green); and LAG3 in Opal 570 (magenta). Scale bars, 100 μm, 10× original magnification. Middle, Zoomed-in area from the boxed segment in the top, stained with DAPI for DNA (cyan); Opal 480 for CD8+ T cells (yellow); and Opal 780 for pan-CK cells (blue). Scale bars, 10 μm, 100× original magnification. Bottom, Composite images. Scale bars, 30 μm, 30× original magnification.
Figure 4 from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Association of BAP1, NF2, MTAP, and LAG3 intensities with immune cell–type intensity in MPM or MPeM. A, Heatmaps showing correlations between the mean intensity of immune cell markers and expression levels of BAP1, NF2, MTAP, and LAG3 across biologically independent tumors in MPM and MPeM. B, Correlation between mean CD56 (NK cell) intensity and mean BAP1, NF2, MTAP, and LAG3 expression. Dots are color-coded by histologic subtypes.
Data from Spatial Landscape of Malignant Pleural and Peritoneal Mesothelioma Tumor Immune Microenvironments
Authors: Ma Xiaojun , Lembersky David , Kim Elena S. , Becich Michael J. , Testa Joseph R. , Bruno Tullia C. , Osmanbeyoglu Hatice U.
Published: August 2024

Abstract
Immunotherapies have demonstrated limited clinical efficacy in malignant mesothelioma treatment. We conducted multiplex immunofluorescence analyses on tissue microarrays (n = 3) from patients with malignant pleural mesothelioma (MPM, n = 88) and malignant peritoneal mesothelioma (MPeM, n = 25). Our study aimed to elucidate spatial distributions of key immune cell populations and their association with lymphocyte activation gene 3 (LAG3), BRCA1-associated protein 1 (BAP1), neurofibromatosis type 2 (NF2), and methylthioadenosine phosphorylase (MTAP), with MTAP serving as a cyclin-dependent kinase inhibitor 2A/2B (CDKN2A/B) surrogate marker. Additionally, we examined the relationship between the spatial distribution of major immune cell types and prognosis and clinical characteristics of patients with malignant mesothelioma. We observed a higher degree of interaction between immune cells and tumor cells in MPM compared with MPeM. Notably, within MPM tumors, we detected a significantly increased interaction between tumor cells and CD8+ T cells in tumors with low BAP1 expression compared with those with high BAP1 expression. To support the broader research community, we have developed The Human Spatial Atlas of Malignant Mesothelioma, containing hematoxylin and eosin and multiplex immunofluorescence images with corresponding metadata.
Significance:
Considering the limited therapeutic options available to patients with malignant mesothelioma, there is substantial translational potential in understanding the correlation between the spatial architecture of the malignant mesothelioma tumor immune microenvironment and tumor biology. Our investigation reveals critical cell–cell interactions that may influence the immune response against malignant mesothelioma tumors, potentially contributing to the differential behaviors observed in MPM and MPeM. These findings represent a valuable resource for the malignant mesothelioma cancer research community.
Real-Time Gastric Juice Analysis to Rule Out the Presence of Autoimmune Gastritis: A Case-Control Study
Authors: Dilaghi Emanuele , Esposito Gianluca , Ligato Irene , Del Forno Alessandro , Rossi Roberta Elisa , Hassan Cesare , Annibale Bruno , Zullo Angelo
Published: August 2024

Background: Autoimmune gastritis (AIG) is an infrequent disease predisposing to both neuroendocrine tumours and cancer. This study aimed to evaluate whether pH measurement of gastric juice allows accurate exclusion of the presence of AIG in real time so that gastric mucosa sampling on normal-appearing mucosa may be avoided. Methods: This study enrolled patients diagnosed with AIG and matched controls (ratio 1:5) who underwent upper endoscopy with standard gastric mucosa sampling and real-time, gastric juice pH assessment. A threshold of pH less than 4.5 was adopted as cut-off to rule out the presence of a feature of AIG. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), overall accuracy, positive likelihood ratio (LR+), and negative likelihood ratio (LR−) were calculated. Results: Data of 40 patients (M/F: 19/21; mean age: 58 years, range: 18–89) with AIG and 212 matched controls were evaluated. Among AIG patients, the feature of atrophy/metaplasia of the oxyntic mucosa was staged as mild in 9 cases, moderate in 9, and severe in the remaining 22 patients. Gastric juice analysis showed a pH value >4.5 in 29 (72.5%) patients and 12 (5.7%) controls. Sensitivity, specificity, accuracy, PPV, NPV, LR+, and LR− were 73% (95% CI = 0.57–0.84), 94% (95% CI = 0.90–0.97), 71% (95% CI = 0.64–0.74), 95% (95% CI = 0.93–0.97), 91% (95% CI = 0.87–0.95), 12.9 (95% CI = 7.19–23.03), and 0.29 (95% CI = 0.18–0.48), respectively. The histological assessment of false-negative cases showed the presence of only mild-moderate atrophy of oxyntic mucosa in 6 (54.5%) cases, and severe in the others. Conclusions: Our data found that real-time pH evaluation of gastric juice allows ruling out AIG with a very high NPV, but further studies are needed.
The Law of International Responsibility Situated: From Halcyon Days to a Fragmented Global Order
Authors: Creutz Katja
Published: August 2024

The question of how international responsibility fares following the Russian aggression against Ukraine has become commonly discussed and explored. This article argues that the context is nevertheless more complicated as the global order is changing due to power shifts. International norms and institutions as Western states used to know them are no longer secure, but subject to great power contestation leaving it unclear if and how practices, pursuits and invocations of international responsibility change. By analysing, in turn, three institutional snapshots of responsibility from the UN General Assembly, the International Court of Justice, and the International Criminal Court respectively, the article identifies three themes prevalent in current responsibility practices: lawfare, short-term goals like prevention, and accusations of double standards. These attributes reflect the tensions of the reordering of the global order and stands far apart from the story of progress that characterised international responsibility in the Halcyon Days of the 1990s.
When foundations falter: The emergence of defensive narratives from insecure attachment dynamics
Authors: Richardson Emma , Boag Simon
Published: August 2024

The present paper introduces a theoretical model that addresses the interplay between insecure attachment, internal narratives, and defensive behaviour. Drawing from attachment theory research, we conceptualize the “internalized defensive narrative” (IDN) as a mental representation associated with attachment-insecurity. The model illustrates how the unique IDN associated with attachment-anxiety and attachment-avoidance respectively invoke hyperactivating and deactivating defenses. In clinical contexts, the model’s application may possibly contribute to the development of more effective therapeutic strategies that target the root causes of a client’s defensive behaviour. By recognizing the IDN as a key factor in the maintenance of the insecure cycle, therapists can potentially help clients gain insights into the psychological mechanisms driving their behaviour and provide them with tools for change, leading to improved therapeutic outcomes for individuals struggling with these issues. Further research is needed to validate and elaborate on the proposed model and its implications for clinical practice.
Issue Accountability in Non-Partisan Municipalities: A Case Study
Authors: McPherson Carter , Lucas Jack , McGregor R. Michael
Published: August 2024

Issue accountability – the extent to which elected representatives are rewarded or punished by voters for their legislative actions in office – is fundamental to many conceptions of healthy democratic accountability. It is not clear, however, if this form of accountability is possible in non-partisan contexts, when constituents may have considerably more difficulty acquiring information about what their elected representatives have done. In this research note, we use data from council roll calls and a large public opinion survey to provide a case study of issue accountability in a large non-partisan city in Canada, assessing how citizens’ agreement with their elected representatives’ actions on seven high-profile policy issues is related to their satisfaction with their representatives’ performance. We find that most local residents are unaware of or incorrect about their councillors’ actions in office, even on issues that they consider important. However, we also find that issue alignment is very strongly related to performance satisfaction among citizens who do know how their councillors have acted in office. Our findings thus illustrate both the possibility of issue accountability in non-partisan municipal politics as well as its constraints.
Surface analysis of iron-based self-lubricating composite under oil lubrication
Authors: Zhang Keyu , Bao Yichen , Dong Yinghui , Yao Lulu , Xu Yufu
Published: August 2024

To improve tribological performances of the tribopairs of hydraulic pump, a kind of new iron-based self-lubricating composite was made and tested on an end-face tribometers under oil lubrication conditions in this work. The results show that the worn surface has shallow furrows and slight wear at different speeds, and the wear type mainly attributes to oxidation wear. When the speed reaches 0.8 m/s, the wear volume of the lower friction pair reaches the maximum 0.289 mm3. This can be due to the fact that the wear debris destroys the lubricating film since the content of mechanical impurities in the lubricant reaches the maximum at this speed. The chemical components characterization of the lubricant shows that the functional groups in lubricating oil after sliding have not changed significantly, but the concentration of the chemicals decreases. This confirms that the lubricating oil with lubrication additives can form tribofilm through chemical reaction during boundary lubrication sliding process to achieve superior antifriction and antiwear effect. While in 1.0 m/s speed, the thicker adsorbed oil film was formed on the sliding interfaces of the iron-based self-lubricating composite, playing an excellent lubrication role.
Surgical management of extensive facial vascular malformation with skin graft: A multidisciplinary approach—Case report
Authors: Katwal Shailendra , Paudel Pratiksha , Khatiwada Bidur , Agrawal Srikant , Bidari Sahadev
Published: August 2024

Vascular malformations are rare congenital abnormalities of blood vessels that persist throughout life. Large vascular malformations affecting the facial region can be distressing and require meticulous management to achieve satisfactory outcomes and prevent recurrence. Here, we present a case of a 40-year-old man with a progressively growing tumor-like mass on the right side of his face, extending from the periorbital region to the chin. He was diagnosed with vascular malformations, which was further confirmed with contrast-enhanced magnetic resonance imaging. Eventually, he underwent surgical excision of the lesion with a split-thickness skin graft. The surgical management of this case was challenging due to the large size and complexity of the lesion, particularly because it was located in the facial region. This unique case report highlights the importance of diagnostic imaging techniques and effective surgical management in addressing large vascular malformations, especially those affecting the facial region while prioritizing desirable cosmetic outcomes.
Artificial Intelligence-Assisted MRI Diagnosis in Lumbar Degenerative Disc Disease: A Systematic Review
Authors: Liawrungrueang Wongthawat , Park Jong-Beom , Cholamjiak Watcharaporn , Sarasombath Peem , Riew K. Daniel
Published: August 2024

Study Design

Systematic review.

Objectives

Lumbar degenerative disc disease (DDD) poses a significant global health care challenge, with accurate diagnosis being difficult using conventional methods. Artificial intelligence (AI), particularly machine learning and deep learning, offers promising tools for improving diagnostic accuracy and workflow in lumbar DDD. This study aims to review AI-assisted magnetic resonance imaging (MRI) diagnosis in lumbar DDD and discuss current research for clinical use.

Methods

A systematic search of electronic databases identified studies on AI applications in MRI-based lumbar DDD diagnosis, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Search terms included combinations of “Artificial Intelligence,” “Machine Learning,” “Deep Learning,” “Low Back Pain,” “Lumbar,” “Disc,” “Degeneration,” and “MRI,” targeting studies in English from January 1, 2010, to January 1, 2024. Inclusion criteria encompassed experimental and observational studies in peer-reviewed journals. Data extraction focused on study characteristics, AI techniques, performance metrics, and diagnostic outcomes, with quality assessed using predefined criteria.

Results

Twenty studies met the inclusion criteria, employing various AI methodologies, including machine learning and deep learning, to diagnose lumbar DDD manifestations such as disc degeneration, herniation, and bulging. AI models consistently outperformed conventional methods in accuracy, sensitivity, and specificity, with performance metrics ranging from 71.5% to 99% across different diagnostic objectives.

Conclusion

The algorithm model provides a structured framework for integrating AI into routine clinical practice, enhancing diagnostic precision and patient outcomes in lumbar DDD management. Further research and validation are needed to refine AI algorithms for real-world application in lumbar DDD diagnosis.
Analysis of Determinants of Stunting and Identifications of Stunting Risk Profiles Among Under 2-Year-Old Children in Ethiopia. A Latent Class Analysis
Authors: Fikrie Anteneh , Adula Berhanu , Beka Jitu , Hailu Dejene , Kitabo Cheru Atsmegiorgis , Spigt Mark
Published: August 2024

Background

Childhood stunting has a long-term impact on cognitive development and overall well-being. Understanding varying stunting profiles is crucial for targeted interventions and effective policy-making. Therefore, our study aimed to identify the determinants and stunting risk profiles among 2-year-old children in Ethiopia.

Methods and materials

A cross-sectional study was conducted on 395 mother–child pairs attending selected public health centers for growth monitoring and promotion under 5 outpatient departments and immunization services. The data were collected by face-to-face interviews, with the anthropometric data collected using the procedure stipulated by the World Health Organization. The data were entered using Epi Data version 4.6 and exported to STATA 16 and Jamovi version 2.3.28 for analysis. Bayesian logistic regression analysis was conducted to identify potential factors of stunting. Likewise, lifecycle assessment analysis (LCA) was used to examine the heterogeneity of the magnitude of stunting.

Results

The overall prevalence of stunting in children under 24 months was 47.34% (95% confidence interval (CI): 42.44-52.29%). The LCA identified 3 distinct risk profiles. The first profile is Class 1, which is labeled as low-risk, comprised 23.8% of the children, and had the lowest prevalence of stunting (23.4%). This group characterized as having a lower risk to stunting. The second profile is Class 2, which is identified as high-risk, comprised 47.1%, and had a high prevalence of stunting (66.7%), indicating a higher susceptibility to stunting compared to Class 1. The third profile is Class 3, which is categorized as mixed-risk and had a moderate stunting prevalence of 35.7%, indicating a complex interplay of factors contributing to stunting.

Conclusion

Our study identified 3 distinct risk profiles for stunting in young children. A substantial amount (almost half) is in the high-risk category, where stunting is far more common. The identification of stunting profiles necessitates considering heterogeneity in risk factors in interventions. Healthcare practitioners should screen, provide nutrition counseling, and promote breastfeeding. Policymakers should strengthen social safety nets and support primary education.
The response of labour demand to different COVID-19 containment measures: evidence from online job postings in Austria
Authors: Leitner Sandra M. , Reiter Oliver
Published: August 2024

This paper analyses changes in the speed of labour demand for new hires in response to the lockdowns that were repeatedly put in place to contain the spread of the COVID-19 pandemic. It tests whether the uncertainty-reducing effect of similar lockdowns occurring in quick succession increased the responsiveness of the labour market, thereby allowing for more rapid adjustment, both at the beginning and at the end of subsequent lockdowns. It uses high-frequency online job-posting data and applies an event study approach to the beginning of three national lockdowns and the subsequent reopening in Austria between 2020 and 2022. In view of the importance of progress in vaccination for labour market recovery, it also looks at vaccine roll-out as an additional COVID-19 containment measure, with 2021 as the main roll-out period. The results indicate very different responses to the three lockdowns, with a decline in job-posting activity of between 47 and 50% during the first lockdown and of between 29 and 31% during the second; but an increase of 23% to 28% during the last lockdown. Moreover, responses to the first lockdown were sluggish, with a slow decline at the beginning and a very slow recovery after it was lifted; but over subsequent lockdowns the responses were more rapid and more symmetrical. Responses to the various events differed by occupation and industry: the strongest responses were to be observed in the highly skilled and more-teleworkable occupations of technicians, and managers and professionals, who were badly affected during the first lockdown; the leisure and hospitality industry, which was the hardest hit on account of the mandatory closures and the widespread travel restrictions and bans, and which recovered only very slowly; and the IT, internet and telecommunications industry, where posting activity developed in a direction opposite to that seen in the other industries. Finally, there is little robust evidence of a differentiated effect of vaccinations during lockdowns, suggesting that vaccination roll-out did not have an additional demand-generating effect, over and above the lockdowns.