bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of lower airway parameters in an adult Asian population related to endotracheal tube design: a cadaveric study
Authors: Turbpaiboon Chairat , Kasemassawachanont Adisak , Wankijcharoen Jirawat , Thusneyapan Kittipott , Khamman Pramuk , Patharateeranart Karnkawin , Amornsitthiwat Ramida , Numwong Terasut , Chaikittisilpa Nophanan , Kiatchai Taniga 
Published: March 2024

AbstractThe risk of endotracheal tube (ETT) placement includes endobronchial intubation and subglottic injury. This study aimed to describe the lengths of lower airway parameters related to cuff location and vocal cord markings in different adult-sized ETTs. Eighty cadavers were examined for the lengths of the lower airway, including their correlations and linear regressions with height. Thirty adult-sized ETTs from seven different brands were examined for Mark-Cuff and Mark-Tip distances. The depth of ETT placement was simulated for each brand using vocal cord marking. The mean (standard deviation) lengths from the subglottis, trachea, vocal cord to mid- trachea, and vocal cord to carina were 24.2 (3.5), 97.9 (8.6), 73.2 (5.3), and 122.1 (9.0) mm, respectively. Airway lengths were estimated as: (1) subglottis (mm) = 0.173 * (height in cm) − 3.547; (2) vocal cord to mid-trachea (mm) = 0.28 * (height in cm) + 28.391. There were variations in the Mark-Cuff and Mark-Tip distances among different ETTs. In the simulation, endobronchial intubation ranged between 2.5 and 5% and the cuff in the subglottis ranged between 2.5 and 97.5%. In summary, the lower airway parameters were height-related. ETT placement using vocal cord marking puts the patient at a high risk of cuff placement in the subglottis.
Status of selected biochemical and coagulation profiles and platelet count in malaria and malaria-Schistosoma mansoni co-infection among patients attending at Dembiya selected Health Institutions, Northwest Ethiopia
Authors: Abebe Wagaw , Asmare Zelalem , Wondmagegn Addis , Awoke Mulat , Adgo Aderajew , Derso Adane , Lemma Wossenseged 
Published: March 2024

AbstractMalaria and schistosomiasis are infectious diseases that cause coagulation disorders, biochemical abnormalities, and thrombocytopenia. Malaria and Schistosoma mansoni co-infection cause exacerbations of health consequences and co-morbidities.This study aimed to compare the effect of malaria and Schistosoma mansoni co-infection and malaria infection on selected biochemical and coagulation profiles, and platelet count. An institutional-based comparative cross-sectional study was conducted from March 30 to August 10, 2022. A total of 70 individuals were enrolled in the study using a convenient sampling technique. Wet mount and Kato Katz techniques were conducted to detect Schistosoma mansoni in a stool sample. Blood films were prepared for the detection of plasmodium. The data was coded and entered into EpiData version 3.1 before being analyzed with SPSS version 25. An independent t test was used during data analysis. A P-value of less than 0.05 was considered statistically significant. The mean [SD] of alanine aminotransferase, aspartate aminotransferase, creatinine, total bilirubin, and direct bilirubin in the co-infected was higher than in malaria infected participants. However, the mean of total protein and glucose in co-infected was lower than in the malaria infected participants. The mean of prothrombin time, international normalization ratio, and activated partial thromboplastin time in co-infected was significantly higher, while the platelet count was lower compared to malaria infected participants. Biochemical and coagulation profiles, and platelet count status in co-infection were changed compared to malaria infected participants. Therefore, biochemical and coagulation profiles and platelet count tests should be used to monitor and manage co-infection related complications and to reduce co-infection associated morbidity and mortality.
Numerical study on the axial collapse of thin-walled columns
Authors: Wang Di , Fang Houcheng , Xue Ruilei , Li Shen 
Published: March 2024

AbstractIn order to investigate the damage characteristics of structural components under axial compression, thin-walled columns are chosen as a more straightforward construct due to the complex structural properties of composite materials, diverse fiber laying angles, and varied geometries associated with thin-walled columns. Despite the limitations imposed by labor-intensive testing procedures, high costs, and the poor repeatability inherent in experimental research methods, there remains an insufficient exploration of axial compressive damage in columns composed of aluminum and fiber-reinforced polymers. This article utilizes the finite element technique to quantitatively analyze the crushing processes of four materials: aluminum, carbon fiber-reinforced aluminum, carbon fiber-reinforced polymer, and glass fiber-reinforced polymer. It examines the effects of varying fibers and matrix materials on their mechanical attributes. The study also evaluates the impact of different cross-sectional designs on the mechanical behavior of the columns.
Prediction and detection of side effects severity following COVID-19 and influenza vaccinations: utilizing smartwatches and smartphones
Authors: Levi Yosi , Brandeau Margaret L. , Shmueli Erez , Yamin Dan 
Published: March 2024

AbstractVaccines stand out as one of the most effective tools in our arsenal for reducing morbidity and mortality. Nonetheless, public hesitancy towards vaccination often stems from concerns about potential side effects, which can vary from person to person. As of now, there are no automated systems available to proactively warn against potential side effects or gauge their severity following vaccination. We have developed machine learning (ML) models designed to predict and detect the severity of post-vaccination side effects. Our study involved 2111 participants who had received at least one dose of either a COVID-19 or influenza vaccine. Each participant was equipped with a Garmin Vivosmart 4 smartwatch and was required to complete a daily self-reported questionnaire regarding local and systemic reactions through a dedicated mobile application. Our XGBoost models yielded an area under the receiver operating characteristic curve (AUROC) of 0.69 and 0.74 in predicting and detecting moderate to severe side effects, respectively. These predictions were primarily based on variables such as vaccine type (influenza vs. COVID-19), the individual's history of side effects from previous vaccines, and specific data collected from the smartwatches prior to vaccine administration, including resting heart rate, heart rate, and heart rate variability. In conclusion, our findings suggest that wearable devices can provide an objective and continuous method for predicting and monitoring moderate to severe vaccine side effects. This technology has the potential to improve clinical trials by automating the classification of vaccine severity.
Improved estimation of the relationship between fetal growth and late stillbirth in the United States, 2014–15
Authors: Tanner Darren , Lavista Ferres Juan M. , Mitchell Edwin A. 
Published: March 2024

AbstractIn the United States the rate of stillbirth after 28 weeks’ gestation (late stillbirth) is 2.7/1000 births. Fetuses that are small for gestational age (SGA) or large for gestational age (LGA) are at increased risk of stillbirth. SGA and LGA are often categorized as growth or birthweight ≤ 10th and ≥ 90th centile, respectively; however, these cut-offs are arbitrary. We sought to characterize the relationship between birthweight and stillbirth risk in greater detail. Data on singleton births between 28- and 44-weeks’ gestation from 2014 to 2015 were extracted from the US Centers for Disease Control and Prevention live birth and fetal death files. Growth was assessed using customized birthweight centiles (Gestation Related Optimal Weight; GROW). The analyses included logistic regression using SGA/LGA categories and a generalized additive model (GAM) using birthweight centile as a continuous exposure. Although the SGA and LGA categories identified infants at risk of stillbirth, categorical models provided poor fits to the data within the high-risk bins, and in particular markedly underestimated the risk for the extreme centiles. For example, for fetuses in the lowest GROW centile, the observed rate was 39.8/1000 births compared with a predicted rate of 11.7/1000 from the category-based analysis. In contrast, the model-predicted risk from the GAM tracked closely with the observed risk, with the GAM providing an accurate characterization of stillbirth risk across the entire birthweight continuum. This study provides stillbirth risk estimates for each GROW centile, which clinicians can use in conjunction with other clinical details to guide obstetric management.
Single shot detection of alterations across multiple ionic currents from assimilation of cell membrane dynamics
Authors: Morris Paul G. , Taylor Joseph D. , Paton Julian F. R. , Nogaret Alain 
Published: March 2024

AbstractThe dysfunction of ion channels is a causative factor in a variety of neurological diseases, thereby defining the implicated channels as key drug targets. The detection of functional changes in multiple specific ionic currents currently presents a challenge, particularly when the neurological causes are either a priori unknown, or are unexpected. Traditional patch clamp electrophysiology is a powerful tool in this regard but is low throughput. Here, we introduce a single-shot method for detecting alterations amongst a range of ion channel types from subtle changes in membrane voltage in response to a short chaotically driven current clamp protocol. We used data assimilation to estimate the parameters of individual ion channels and from these we reconstructed ionic currents which exhibit significantly lower error than the parameter estimates. Such reconstructed currents thereby become sensitive predictors of functional alterations in biological ion channels. The technique correctly predicted which ionic current was altered, and by approximately how much, following pharmacological blockade of BK, SK, A-type K+ and HCN channels in hippocampal CA1 neurons. We anticipate this assay technique could aid in the detection of functional changes in specific ionic currents during drug screening, as well as in research targeting ion channel dysfunction.
Comparing risk assessment methods for work-related musculoskeletal disorders with in vivo joint loads during manual materials handling
Authors: Brandl Christopher , Bender Alwina , Schmachtenberg Tim , Dymke Jörn , Damm Philipp 
Published: March 2024

AbstractThe validity of observational methods in ergonomics is still challenging research. Criterion validity in terms of concurrent validity is the most commonly studied. However, studies comparing observational methods with biomechanical values are rare. Thus, the aim of this study is to compare the Ovako Working Posture Analysing System (OWAS) and the Rapid Entire Body Assessment (REBA) with in vivo load measurements at hip, spine, and knee during stoop and squat lifting of 14 participants. The results reveal that OWAS and REBA action levels (AL) can distinguish between different in vivo load measurements during manual lifting. However, the results also reveal that the same OWAS- and REBA-AL do not necessarily provide equal mean values of in vivo load measurements. For example, resultant contact force in the vertebral body replacement for squat lifting ranged from 57% body weight (%BW) in OWAS-AL1 to 138%BW in OWAS-AL3 compared to 46%BW in REBA-AL0 and 173%BW in REBA-AL3. Furthermore, the results suggest that the performed squat lifting techniques had a higher risk for work-related musculoskeletal disorders than the performed stoop lifting techniques.
Application of back propagation neural network in complex diagnostics and forecasting loss of life of cellulose paper insulation in oil-immersed transformers
Authors: Ngwenyama M. K. , Gitau M. N. 
Published: March 2024

AbstractOil-immersed transformers are expensive equipment in the electrical system, and their failure would lead to widespread blackouts and catastrophic economic losses. In this work, an elaborate diagnostic approach is proposed to evaluate twenty-six different transformers in-service to determine their operative status as per the IEC 60599:2022 standard and CIGRE brochure. The approach integrates dissolved gas analysis (DGA), transformer oil integrity analysis, visual inspections, and two Back Propagation Neural Network (BPNN) algorithms to predict the loss of life (LOL) of the transformers through condition monitoring of the cellulose paper. The first BPNN algorithm proposed is based on forecasting the degree of polymerization (DP) using 2-Furaldehyde (2FAL) concentration measured from oil samples using DGA, and the second BPNN algorithm proposed is based on forecasting transformer LOL using the 2FAL and DP data obtained from the first BPNN algorithm. The first algorithm produced a correlation coefficient of 0.970 when the DP was predicted using the 2FAL measured in oil and the second algorithm produced a correlation coefficient of 0.999 when the LOL was predicted using the 2FAL and DP output data obtained from the first algorithm. The results show that the BPNN can be utilized to forecast the DP and LOL of transformers in-service. Lastly, the results are used for hazard analysis and lifespan prediction based on the health index (HI) for each transformer to predict the expected years of service.
Impact of rumen microbiome on cattle carcass traits
Authors: Sato Yoshiaki , Sato Ruki , Fukui Emiko , Yoshizawa Fumiaki 
Published: March 2024

AbstractRumen microbes are crucial in the anaerobic fermentation of plant polysaccharides to produce volatile fatty acids. However, limited information exists about the specific microbial species and strains in the rumen that affect carcass traits, and it is unclear whether there is a relationship between rumen metabolic functions and these traits. This study investigated the relationship between the rumen microbiome and carcass traits in beef cattle using 16S rRNA amplicon and shotgun sequencing. Metagenomic sequencing was used to compare the rumen microbiome between high-carcass weight (HW) and low-carcass weight (LW) cattle, and high-marbling (HM) and low-marbling (LM) cattle. Prokaryotic communities in the rumen of HW vs. LW and HM vs. LM were separated using 16S rRNA amplicon sequencing. Notably, shotgun metagenomic sequencing revealed that HW cattle had more methane-producing bacteria and ciliate protozoa, suggesting higher methane emissions. Additionally, variations were observed in the abundances of certain glycoside hydrolases and polysaccharide lyases involved in the ruminal degradation of plant polysaccharides between HW and LW. From our metagenome dataset, 807 non-redundant metagenome-assembled genomes (MAGs) of medium to high quality were obtained. Among these, 309 and 113 MAGs were associated with carcass weight and marbling, respectively.
Identification and interpretation of gait analysis features and foot conditions by explainable AI
Authors: Özateş Mustafa Erkam , Yaman Alper , Salami Firooz , Campos Sarah , Wolf Sebastian I. , Schneider Urs 
Published: March 2024

AbstractClinical gait analysis is a crucial step for identifying foot disorders and planning surgery. Automating this process is essential for efficiently assessing the substantial amount of gait data. In this study, we explored the potential of state-of-the-art machine learning (ML) and explainable artificial intelligence (XAI) algorithms to automate all various steps involved in gait analysis for six specific foot conditions. To address the complexity of gait data, we manually created new features, followed by recursive feature elimination using Support Vector Machines (SVM) and Random Forests (RF) to eliminate low-variance features. SVM, RF, K-nearest Neighbor (KNN), and Logistic Regression (LREGR) were compared for classification, with a Majority Voting (MV) model combining trained models. KNN and MV achieved mean balanced accuracy, recall, precision, and F1 score of 0.87. All models were interpreted using Local Interpretable Model-agnostic Explanation (LIME) method and the five most relevant features were identified for each foot condition. High success scores indicate a strong relationship between selected features and foot conditions, potentially indicating clinical relevance. The proposed ML pipeline, adaptable for other foot conditions, showcases its potential in aiding experts in foot condition identification and planning surgeries.
Prioritized experience replay based on dynamics priority
Authors: Li Hu , Qian Xuezhong , Song Wei 
Published: March 2024

AbstractExperience replay has been instrumental in achieving significant advancements in reinforcement learning by increasing the utilization of data. To further improve the sampling efficiency, prioritized experience replay (PER) was proposed. This algorithm prioritizes experiences based on the temporal difference error (TD error), enabling the agent to learn from more valuable experiences stored in the experience pool. While various prioritized algorithms have been proposed, they ignored the dynamic changes of experience value during the training process, merely combining different priority criteria in a fixed or linear manner. In this paper, we present a novel prioritized experience replay algorithm called PERDP, which employs a dynamic priority adjustment framework. PERDP adaptively adjusts the weights of each criterion based on average priority level of the experience pool and evaluates experiences’ value according to current network. We apply this algorithm to the SAC model and conduct experiments in the OpenAI Gym experimental environment. The experiment results demonstrate that the PERDP exhibits superior convergence speed when compared to the PER.
Interferon-γ in the tumor microenvironment promotes the expression of B7H4 in colorectal cancer cells, thereby inhibiting cytotoxic T cells
Authors: Jing Zhi-liang , Liu Guang-long , Zhou Na , Xu Dong-yan , Feng Na , Lei Yan , Ma Li-li , Tang Min-shan , Tong Gui-hui , Tang Na , Deng Yong-jian 
Published: March 2024

AbstractThe bioactivity of interferon-γ (IFN-γ) in cancer cells in the tumor microenvironment (TME) is not well understood in the current immunotherapy era. We found that IFN-γ has an immunosuppressive effect on colorectal cancer (CRC) cells. The tumor volume in immunocompetent mice was significantly increased after subcutaneous implantation of murine CRC cells followed by IFN-γ stimulation, and RNA sequencing showed high expression of B7 homologous protein 4 (B7H4) in these tumors. B7H4 promotes CRC cell growth by inhibiting the release of granzyme B (GzmB) from CD8+ T cells and accelerating apoptosis in CD8+ T cells. Furthermore, interferon regulatory factor 1 (IRF1), which binds to the B7H4 promoter, is positively associated with IFN-γ stimulation-induced expression of B7H4. The clinical outcome of patients with CRC was negatively related to the high expression of B7H4 in cancer cells or low expression of CD8 in the microenvironment. Therefore, B7H4 is a biomarker of poor prognosis in CRC patients, and interference with the IFN-γ/IRF1/B7H4 axis might be a novel immunotherapeutic method to restore the cytotoxic killing of CRC cells.
Predicting conversational satisfaction of face-to-face conversation through interpersonal similarity in resting-state functional connectivity
Authors: Ikeda Shigeyuki , Jeong Hyeonjeong , Sasaki Yukako , Sakaki Kohei , Yamazaki Shohei , Nozawa Takayuki , Kawashima Ryuta 
Published: March 2024

AbstractWhen conversing with an unacquainted person, if it goes well, we can obtain much satisfaction (referred to as conversational satisfaction). Can we predict how satisfied dyads will be with face-to-face conversation? To this end, we employed interpersonal similarity in whole-brain resting-state functional connectivity (RSFC), measured using functional magnetic resonance imaging before dyadic conversation. We investigated whether conversational satisfaction could be predicted from interpersonal similarity in RSFC using multivariate pattern analysis. Consequently, prediction was successful, suggesting that interpersonal similarity in RSFC is an effective neural biomarker predicting how much face-to-face conversation goes well. Furthermore, regression coefficients from predictive models suggest that both interpersonal similarity and dissimilarity contribute to good interpersonal relationships in terms of brain activity. The present study provides the potential of an interpersonal similarity approach using RSFC for understanding the foundations of human relationships and new neuroscientific insight into whether success in human interactions is predetermined.
A retrospective cohort study of autogenous iliac strut bone grafting in large bone defects of the lower extremity
Authors: Kook Incheol , You Jooyoung , Kim Dong Hong , Park Ki-Chul , Hwang Kyu Tae 
Published: March 2024

AbstractAutogenous iliac bone graft (AIBG) is the treatment of choice for managing bone defects, and favorable results have been reported for bone defects < 5 cm in length. In large bone defects ≥ 5 cm, it is difficult to obtain good results with simple bone grafting, and other management options have drawbacks, such as long immobilization periods and high complication rates. We hypothesized that AIBG in the strut form might show favorable results in large bone defects with minimal complications. This study aimed to investigate the outcomes of strut-type AIBG and evaluate its effectiveness compared to cancellous AIBG. This retrospective study included 50 patients who underwent AIBG for bone defects at a single institution between March 2011 and April 2020. We performed corticocancellous AIBG in a strut form to manage bone defects ≥ 5 cm in the lower extremities. The strut bone was harvested along the iliac crest and grafted slightly longer than the bone defect to apply a sufficient compressive force. Demographic information and radiographic and clinical results of patients who underwent strut AIBG (Group S) were analyzed. The outcomes of union, time to union, complications, and reoperation were compared with those of patients who underwent cancellous AIBG (Group C). The study population comprised 37 men (74%) and 13 women (26%), with a mean age of 50.0 (range: 19–78). The average follow-up period was 25.6 months (12–104 months). Group S included 16 patients with a mean bone defect length of 6.8 ± 1.2 cm. In Group S, union was achieved in all patients, with an average time to union of 6.7 months. Complications occurred in four cases, all related to wound problems. Group C comprised d 34 patients with a mean defect length of 2.8 ± 1.1 cm. Complications occurred in five patients in Group C, including four soft tissue problems and one implant failure. When comparing the outcomes of Groups S and C, no significant differences were observed. AIBG is an effective and safe technique for managing bone defects. Strut AIBG can be used effectively for bone defects ≥ 5 cm in the lower extremities.