bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report
Authors: Compagnone Christian , Borrini Giulia , Calabrese Alberto , Taddei Mario , Bellini Valentina , Bignami Elena 
Published: August 2022

Abstract
Background
Neuraxial anesthesia in obese parturients can be challenging due to anatomical and physiological modifications secondary to pregnancy; this led to growing popularity of spine ultrasound in this population for easing landmark identification and procedure execution.
Integration of Artificial Intelligence with ultrasound (AI-US) for image enhancement and analysis has increased clinicians' ability to localize vertebral structures in patients with challenging anatomical conformation.

Case presentation
We present the case of a parturient with extremely severe obesity, with a Body Mass Index (BMI) = 64.5 kg/m2, in which the AI-Enabled Image Recognition allowed a successful placing of an epidural catheter.

Conclusions
Benefits gained from AI-US implementation are multiple: immediate recognition of anatomical structures leads to increased first-attempt success rate, making easier the process of spinal anesthesia execution compared to traditional palpation methods, reducing needle placement time for spinal anesthesia and predicting best needle direction and target structure depth in peridural anesthesia.
The relationship between external and internal load parameters in 3 × 3 basketball tournaments
Authors: Willberg C. , Wieland B. , Rettenmaier L. , Behringer M. , Zentgraf K. 
Published: August 2022

Abstract
Purpose
3 × 3 basketball games are characterized by high-intensity accelerations and decelerations, and a high number of changes of direction and jumps. It is played in tournament form with multiple games per day. Therefore, optimal regeneration is crucial for maintaining a high performance level over the course of the tournament. To elucidate how load of a match affects the athletes' bodies (i.e., internal load), muscular responses to the load of 3 × 3 games were analyzed. We aimed to investigate changes in contractility of the m. rectus femoris (RF) and m. gastrocnemius medialis (GC) in response to the load of single 3 × 3 games and a 3 × 3 tournament.

Methods
Inertial movement analysis was conducted to capture game load in 3 × 3. Changes in contractility were measured using tensiomyography (TMG). During a two-day tournament, TMG measurements were conducted in the morning and after each game. Additionally, off-game performance analysis consisting of jump and change-of-direction (COD) tests was conducted the day before the tournament.

Results
Significant changes of the muscle contractility were found for GC with TMG values being higher in the baseline than in the post-game measurements. In contrast to athletes of the GC group, athletes of the RF group responded with either decreased or increased muscle contractility after a single 3 × 3 game. A significant correlation between external and internal load parameters could not be shown. Concerning off-game performance, significant correlations can be reported for COD test duration, CMJ height and ∆Vc as well as COD test duration and ∆Dm. No systematic changes in muscle contractility were found over the course of the tournament in RF and GC.

Conclusion
The athletes' external 3 × 3 game load and their performance level did not seem to affect muscular contractility after a single 3 × 3 game or a complete 3 × 3 tournament within this investigation. This might indicate that elite athletes can resist external load without relevant local muscular fatigue. With respect to the course of the tournament, it can therefore be concluded that the breaks between games seem to be sufficient to return to the initial level of muscle contractility.
Early diagnosis of Alzheimer’s disease using machine learning: a multi-diagnostic, generalizable approach
Authors: Diogo Vasco Sá , Ferreira Hugo Alexandre , Prata Diana ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: August 2022

Abstract
Background
Early and accurate diagnosis of Alzheimer’s disease (AD) is essential for disease management and therapeutic choices that can delay disease progression. Machine learning (ML) approaches have been extensively used in attempts to develop algorithms for reliable early diagnosis of AD, although clinical usefulness, interpretability, and generalizability of the classifiers across datasets and MRI protocols remain limited.

Methods
We report a multi-diagnostic and generalizable approach for mild cognitive impairment (MCI) and AD diagnosis using structural MRI and ML. Classifiers were trained and tested using subjects from the AD Neuroimaging Initiative (ADNI) database (n = 570) and the Open Access Series of Imaging Studies (OASIS) project database (n = 531). Several classifiers are compared and combined using voting for a decision. Additionally, we report tests of generalizability across datasets and protocols (IR-SPGR and MPRAGE), the impact of using graph theory measures on diagnostic classification performance, the relative importance of different brain regions on classification for better interpretability, and an evaluation of the potential for clinical applicability of the classifier.

Results
Our “healthy controls (HC) vs. AD” classifier trained and tested on the combination of ADNI and OASIS datasets obtained a balanced accuracy (BAC) of 90.6% and a Matthew’s correlation coefficient (MCC) of 0.811. Our “HC vs. MCI vs. AD” classifier trained and tested on the ADNI dataset obtained a 62.1% BAC (33.3% being the by-chance cut-off) and 0.438 MCC. Hippocampal features were the strongest contributors to the classification decisions (approx. 25–45%), followed by temporal (approx. 13%), cingulate, and frontal regions (approx. 8–13% each), which is consistent with our current understanding of AD and its progression. Classifiers generalized well across both datasets and protocols. Finally, using graph theory measures did not improve classification performance.

Conclusions
In sum, we present a diagnostic tool for MCI and AD trained using baseline scans and a follow-up diagnosis regardless of progression, which is multi-diagnostic, generalizable across independent data sources and acquisition protocols, and with transparently reported performance. Rated as potentially clinically applicable, our tool may be clinically useful to inform diagnostic decisions in dementia, if successful in real-world prospective clinical trials.
Harmonization issues in unit costing of service use for multi-country, multi-sectoral health economic evaluations: a scoping review
Authors: Fischer Claudia , Mayer Susanne , Perić Nataša , Simon Judit 
Published: August 2022

Abstract
Background
Valuation is a critical part of the costing process in health economic evaluations. However, an overview of specific issues relevant to the European context on harmonizing methodological requirements for the valuation of costs to be used in health economic evaluation is lacking. We aimed to inform the development of an international, harmonized and multi-sectoral costing framework, as sought in the European PECUNIA (ProgrammE in Costing, resource use measurement and outcome valuation for Use in multi-sectoral National and International health economic evaluAtions) project.

Methods
We conducted a scoping review (information extraction 2008–2021) to a) to demonstrate the degree of heterogeneity that currently exists in the literature regarding central terminology, b) to generate an overview of the most relevant areas for harmonization in multi-sectoral and multi-national costing processes for health economic evaluations, and c) to provide insights into country level variation regarding economic evaluation guidance. A complex search strategy was applied covering key publications on costing methods, glossaries, and international costing recommendations augmented by a targeted author and reference search as well as snowballing. Six European countries served as case studies to describe country-specific harmonization issues. Identified information was qualitatively synthesized and cross-checked using a newly developed, pilot-tested data extraction form.

Results
Costing methods for services were found to be heterogeneous between sectors and country guidelines and may, in practice, be often driven by data availability and reimbursement systems in place. The lack of detailed guidance regarding specific costing methods, recommended data sources, double-counting of costs between sectors, adjustment of unit costs for inflation, transparent handling of overhead costs as well as the unavailability of standardized unit costing estimates in most countries were identified as main drivers of country specific differences in costing methods with a major impact on valuation and cost-effectiveness evidence.

Conclusion
This review provides a basic summary of existing costing practices for evaluative purposes across sectors and countries and highlights several common methodological factors influencing divergence in cost valuation methods that would need to be systematically incorporated and addressed in future costing practices to achieve more comparable, harmonized health economic evaluation evidence.
An electrochemical sensor based on [Ru(bpy)2dpp]2+/SMWCNTs/Au modified glassy carbon electrode for the detection of 5ʹ-GMP
Authors: Yu Ying , Huan Siqi , Wang Xiaodan , Yang Cong , Liu Dengyong 
Published: August 2022

AbstractA sensitive electrochemical sensor for the selective detection of 5ʹ-guanylic acid (5ʹ-GMP) was prepared by combining sulfonated-multiwalled carbon nanotubes (SMWCNTs) and [Ru(bpy)2dpp]Cl2, which were dripped on the surface of a glass carbon electrode (GCE) immobilized with gold nanoparticles. The 5ʹ-GMP electrochemical biosensor was fabricated using [Ru(bpy)2dpp]2+/SMWCNTs/Au/GCE as working, Ag/AgCl as reference and Pt as auxiliary electrode connected by an electrochemical workstation. The modified electrode was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The results showed the sensor’s response current had the best peak shape and maximum peak when the pH of electrolyte was 3, scan speed of CV was in the range of 100 to 180 mV/s, and the enrichment time was in the range of 200 to 300 s. Under the optimum conditions, a linear analytical curve was obtained for 5ʹ-GMP concentrations in the range of 0.01 to 0.5 mmol L−1, with a detection limit of 0.0014 mmol L−1. The analytical results of the 5ʹ-GMP sensor were exhibited good consistent with the data from liquid chromatography. The sensor has good reproducibility, long-term stability and strong immunity to interference, and may be a powerful device for 5ʹ-GMP detection, with great advantages such as simple preparation and operation, low equipment cost.
Differences between bipolar disorder types 1 and 2 support the DSM two-syndrome concept
Authors: Tondo Leonardo , Miola Alessandro , Pinna Marco , Contu Martina , Baldessarini Ross J. 
Published: August 2022

Abstract
Objective
To compare characteristics of bipolar disorder patients diagnosed as DSM-5 types I (BD-1) vs. II (BD-2).

Methods
We compared descriptive, psychopathological, and treatment characteristics in a sample of 1377 consenting, closely and repeatedly evaluated adult BD patient-subjects from a specialty clinic, using bivariate methods and logistic multivariable modeling.

Results
Factors found more among BD-2 > BD-1 cases included: [a] descriptors (more familial affective disorder, older at onset, diagnosis and first-treatment, more education, employment and higher socioeconomic status, more marriage and children, and less obesity); [b] morbidity (more general medical diagnoses, less drug abuse and smoking, more initial depression and less [hypo]mania or psychosis, longer episodes, higher intake depression and anxiety ratings, less mood-switching with antidepressants, less seasonal mood-change, greater %-time depressed and less [hypo]manic, fewer hospitalizations, more depression-predominant polarity, DMI > MDI course-pattern, and less violent suicidal behavior); [c] specific item-scores with initial HDRS21 (higher scores for depression, guilt, suicidality, insomnia, anxiety, agitation, gastrointestinal symptoms, hypochondriasis and weight-loss, with less psychomotor retardation, depersonalization, or paranoia); and [d] treatment (less use of lithium or antipsychotics, more antidepressant and benzodiazepine treatment).

Conclusions
BD-2 was characterized by more prominent and longer depressions with some hypomania and mixed-features but not mania and rarely psychosis. BD-2 subjects had higher socioeconomic and functional status but also high levels of long-term morbidity and suicidal risk. Accordingly, BD-2 is dissimilar to, but not necessarily less severe than BD-1, consistent with being distinct syndromes.
Do immigrants experience labor market mismatch? New evidence from the US PIAAC
Authors: Pivovarova Margarita , Powers Jeanne M. 
Published: August 2022

AbstractBackgroundOne way of evaluating immigrants’ labor market outcomes is to assess the extent to which immigrants are able to enter into jobs that are commensurate with their education and experience. An imperfect alignment between workers’ educational qualifications and these required for their current job, or education-job mismatch, has implications for both the broader economy and individual workers. In this study, we investigate the factors associated with education-job mismatches among US workers by immigrant generation.MethodsWe analyzed the data from the US sample of the Program for the International Assessment of Adult Competencies (PIAAC) 2012/2014. Our analytic sample included 4022 employed (full and part-time) individuals between the ages of 20–65 years. We documented the distribution of education-job mismatches across selected independent variables and estimated the relationship between the individual characteristics of workers such as race, gender, presence of children, location, time in the country and knowledge of English for first-generation immigrant workers, and education-job mismatch using multinomial logistic regressions for the full sample and for the sample of first- and second-generation workers.ResultsWe found that on average, immigrant workers in the US labor market were more likely to hold jobs which required less education that they had (being overmatched for the job), with first-generation workers being overmatched more frequently than second-generation workers. The probability of being overmatched for immigrant workers declines with the length of stay, and workers who are proficient in English are less likely to be overmatched. Our results also suggest that there may be labor market disadvantages to immigrant status that persist beyond the first-generation.ConclusionsPrevious research demonstrated that over-education depresses wages and lowers workers’ standards of living and their abilities to accumulate wealth. Our findings confirm that this dynamic may be particularly acute for first- and second-generation workers who are finding it difficult to become fully integrated into US labor markets, even though the factors behind the mismatch differs between the two immigrant generations.
Investigation of heavy metalloid pollutants in the south of Tehran using kriging method and HYDRUS model
Authors: Mirzaei Farhad , Abbasi Yasser , Sohrabi Teymour , Mirhashemi Seyed Hassan 
Published: August 2022

AbstractDue to the high cost of the large-scale measurement of heavy metals, the use of statistical land models and techniques is one of the proper ways to study their distribution and level of pollution. The study area, is agricultural lands of south Tehran in Iran. Municipal wastewater is often used for irrigation agricultural lands under surface irrigation method. To study the distribution of heavy metals including copper, nickel, and lead, the ordinary kriging method in the GIS environment was used. In addition, one-dimensional HYDRUS modeling of water flow and heavy metals in the soil environment was simulated up to a depth of 50 cm for 210 days and the concentration of heavy metals in the depth was simulated. Distribution of lead element in soil surface with spherical model showed that its variation was in the range of 20–70 mg/kg. These values were 50–60 mg/kg for copper and 30 mg/kg for nickel. Investigation of heavy metal concentrations in soil profiles using the HYDRUS-1D model showed that the major accumulation of heavy metals occurred in the surface layer of soil at a depth of 0–15 cm that was higher than the permissible level.
An eye for an ‘I:’ a critical assessment of artificial intelligence tools in migration and asylum management
Authors: Nalbandian Lucia 
Published: August 2022

AbstractThe promise of artificial intelligence has been originally to put technology at the service of people utilizing powerful information processors and ‘smart’ algorithms to quickly perform time-consuming data analysis. It soon though became apparent that the capacity of artificial intelligence to scrape and analyze big data would be particularly useful in surveillance policies. In the wider areas of migration and asylum management, increasingly sophisticated artificial intelligence tools have been used to register and manage vulnerable populations without much concern about the potential misuses of the data collected and the overall ethical and legal underpinnings of these operations. This article examines three cases in point. The first case investigates the United Nations High Commissioner for Refugees’ decision to deploy a biometric matching engine engaging artificial intelligence to make accessing identification documents easier for both refugees and asylum seekers and the states and organizations they interact with. The second case focuses on the New Zealand government’s introduction of artificial intelligence to improve border security and streamline immigration. The third case looks at data scraping and biometric recognition tools implemented by the United States government to track (and eventually deport) undocumented migrants. The article first shows how states and international organizations are increasingly turning to artificial intelligence tools to support the implementation of their immigration policies and programs. Subsequently, the article also outlines how even despite well-intentioned efforts, the decision to use artificial intelligence tools to increase efficiency and support the implementation of migration or asylum management policies and programs often involves jeopardizing or altogether sacrificing individuals’ human rights, including privacy and security, and raises concerns about vulnerability and transparency.
ABC/2 formula for “bedside” postoperative pneumocephalus volume measurement
Authors: Chan David Yuen Chung , Cheung Eric Yuk Hong , Hui Ka Ho , Leung Cecelia Mei Sze , Ng Stephanie Chi Ping , Mak Wai Kit , Wong George Kwok Chu , Chan Tat Ming Danny , Poon Wai Sang 
Published: August 2022

Abstract
Background
Postoperative pneumocephalus is associated with a higher risk of recurrence of chronic subdural hematoma (cSDH). However, there is no verified simple way to measure the pneumocephalus volume at the bedside for daily clinical use. The ABC/2 method was shown to be a simple and reliable technique to estimate volumes of intracranial lesions, such as intracranial hematomas. This study aims to evaluate the accuracy of the ABC/2 formula in estimating volumes of pneumocephalus, as compared to the gold standard with computer-assisted volumetric analysis.

Methods
A total of 141 postoperative computed tomographic (CT) brain scans of cSDH patients with burr-hole drainage were analysed. Pneumocephalus volume was measured independently by both the ABC/2 formula and the computer-assisted volumetric measurement. For the computer-assisted measurement, the volume of the air was semiautomatically segmented and calculated by computer software. Linear regression was used to determine the correlation between the ABC/2 method and computer-assisted measurement.

Results
The postoperative pneumocephalus volume after bilateral burr-hole drainage was significantly larger than that of unilateral burr-hole drainage (29.34 ml versus 12.21 ml, p < 0.001). The estimated volumes by the formula ABC/2 significantly correlated to the volumes as measured by the computer-assisted volumetric technique, with r = 0.992 (p < 0.001). The Pearson correlation coefficient is very close to 1, which signifies a very strong positive correlation, and it is statistically significant.

Conclusions
An excellent correlation is observed between the ABC/2 method and the computer-assisted measurement. This study verified that the ABC/2 method is an accurate and simple “bedside” technique to estimate pneumocephalus volume.
A phase I/II study of adoptive immunotherapy using donor liver graft-derived natural killer cells to prevent bloodstream infection after liver transplantation: a study protocol
Authors: Ohira Masahiro , Imaoka Yuki , Sato Koki , Imaoka Koki , Nakano Ryosuke , Tanimine Naoki , Tahara Hiroyuki , Ide Kentaro , Kobayashi Tsuyoshi , Tanaka Yuka , Ohdan Hideki 
Published: August 2022

Abstract
Background
Bloodstream infections (BSIs) are among the most lethal complications of liver transplantation (LT). Natural killer (NK) cells are an important component of innate immunity and play an essential role in infection and cancer. Adoptive transfer of activated NK cells has the potential to decrease post-LT infections, including BSIs.

Methods
In this prospective, single-center, interventional, single-arm, historical control, phase I/II study, 37 LT recipients will enroll. The patient will receive a single infusion of donor liver-derived NK cells 3−5 days after LT.

Discussion
The primary endpoint is the incidence of BSIs during the first month after LT. Secondary endpoints include overall survival, adverse events, immunological responses, hepatocellular or de novo malignancy, and incidence of infectious disease.

Trial registration
This study was prospectively registered with UMIN000019183 (https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000022074) on November 1, 2015 and jRCTa060190036 on February 27, 2020.