bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and associated factors of stunting, wasting and underweight of children below five using quintile regression analysis (PDHS 2017–2018)
Authors: Siddiqa Maryam , Zubair Amber , Kamal Asifa , Ijaz Muhammad , Abushal Tahani 
Published: November 2022

AbstractThe objective of the current study is to identify the risk factors for malnutrition among the age of under-five children’s in Pakistan. This is secondary data analysis for the data taken from Pakistan Demographic and Health Survey (PDHS 2017–18) and was analyzed by implementing quantile regression analysis. The sample size included 12,708 alive children in the study, for which the data collection period was from November 22, 2017, to April 30, 2018. The prevalence of malnutrition among boys is high (51.2%). Older age mother’s children have more prevalence of malnutrition (20.7%). A child born with small body size (underweight: Q0.25: − 0.625; Q0.50: − 0.623; Q0.75: − 0.426 and wasting: Q0.50: − 0.513); having uneducated mother (underweight: Q0.25: − 0.387; Q0.50: − 0.247; Q0.75: − 0.328), belonged to a poor household (underweight: Q0.50: − 0.251),residing in rural areas (underweight: Q0.25: − 0.443), not following properly breastfeeding practices (underweight: Q0.50: − 0.439; Q0.75: − 0.438) have negative effect on different measures of malnutrition and this effect is significantly raises across different quantiles of stunting , wasting and underweight (atp value < 0.01 and < 0.05). Older age mother (stunting: Q0.50: 0.777; Q0.75: 1.078; underweight Q0.20: 0.568; Q0.50: 0.429; Q0.75: 0.524) and higher birth order number (stunting: Q0.50: 0.415; Q0.75: 0.535), have a positive effect on three measures of under-nutrition and this effect is gradual raises at different quantile of stunting, wasting and underweight. Elder and smoker mothers were proved associated risk factors of both stunting and being underweight in Pakistan. Moreover, Proper breastfeeding practices, better economic status, average or above the average birth weight of the child, and milk consumption are found protective factors against stunting, wasting, and underweight children in Pakistan.
The clinical experience of the prognosis in opposite CEA and image change after therapy in stage IV colorectal cancer
Authors: Su Yi-Tien , Chen Jia-Wan , Chang Shih-Ching , Jiang Jeng-Kai , Huang Sheng-Chieh 
Published: November 2022

AbstractCarcinoembryonic antigen (CEA) levels and imaging are used to guide treatment for metastatic colorectal cancer (mCRC). This study evaluated changes in CEA and imaging findings in mCRC patients following systemic therapy and their clinical significance, especially the ones with inconsistent results of CEA and image findings. We enrolled 330 stage IV CRC patients who systemic therapy. Based on the Response Evaluation Criteria in Solid Tumors (RECIST) and a modification for CEA, patients were stratified into consistent and inconsistent response groups. Clinicopathological features and prognoses were compared between each groups. Different CEA/IMG groups showed no significant differences in terms of tumor location, initial CEA level, mucinous component, tumor differentiation and further surgical treatment rate. Inconsistent responses were observed in half of the patients (n = 165, 50%). The prognosis in the inconsistent groups with either CEA-SD or IMG-SD was dependent on the result of the other evaluation method (PR or PD). Cases with conflicting results between CEA and image groups (CEA-RD/IMG-PD, CEA-PD/IMG-PR) had an OS close to that of CEA-SD/IMG-SD (18.2 m, 16.2 m vs. 18.8 m, P = 0.620). The overall survival (OS) in the consistent (PR/PR ro PD/PD) groups were significantly different (P < 0.001). Combining CEA and imaging provides more information about mCRC patients who have undergone systemic therapy. Approximately half the patients have inconsistent responses, which is still valuable in predicting the prognosis.
Protein biomarkers of cardiac remodeling and inflammation associated with HFpEF and incident events
Authors: Regan Jessica A. , Truby Lauren K. , Tahir Usman A. , Katz Daniel H. , Nguyen Maggie , Kwee Lydia Coulter , Deng Shuliang , Wilson James G. , Mentz Robert J. , Kraus William E. , Hernandez Adrian F. , Gerszten Robert E. , Peterson Eric D. , Holman Rury R. , Shah Svati H. 
Published: November 2022

AbstractThere is increasing evidence that HFpEF is a heterogeneous clinical entity and distinct molecular pathways may contribute to pathophysiology. Leveraging unbiased proteomics to identify novel biomarkers, this study seeks to understand the underlying molecular mechanisms of HFpEF. The discovery cohort consisted of HFpEF cases and non-HF controls from the CATHGEN study (N = 176); the validation cohort consisted of participants from the TECOS trial of patients with diabetes (N = 109). Proteins associated with HFpEF were included in a LASSO model to create a discriminative multi-protein model and assessed in the validation cohort. Survival models and meta-analysis were used to test the association of proteins with incident clinical outcomes, including HF hospitalization, mortality and HFpEF hospitalization in CATHGEN, TECOS and the Jackson Heart Study. In the derivation set, 190 proteins were associated with HFpEF in univariate analysis, of which 65 remained significant in the multivariate model. Twenty (30.8%) of these proteins validated in TECOS, including LCN2, U-PAR, IL-1ra, KIM1, CSTB and Gal-9 (OR 1.93–2.77, p < 0.01). LASSO regression yielded a 13-protein model which, when added to a clinical model inclusive of NT-proBNP, improved the AUC from 0.82 to 0.92 (p = 1.5 × 10–4). Five proteins were associated with incident HF hospitalization, four with HFpEF hospitalization and eleven with mortality (p < 0.05). We identified and validated multiple circulating biomarkers associated with HFpEF as well as HF outcomes. These biomarkers added incremental discriminative capabilities beyond clinical factors and NT-proBNP.
Lactate causes downregulation of Helicobacter pylori adhesin genes sabA and labA while dampening the production of proinflammatory cytokines
Authors: Somiah Tanvi , Gebremariam Hanna G. , Zuo Fanglei , Smirnova Ksenija , Jonsson Ann-Beth 
Published: November 2022

AbstractChronic inflammation induced by Helicobacter pylori is strongly associated with gastric cancer development, which is influenced by both bacterial virulence and host genetics. The sialic acid-binding adhesin SabA and the MUC5AC-binding adhesin LabA are important H. pylori virulence factors that facilitate adhesion of the bacterium, which is a crucial step in colonization. Lactate utilization has been reported to play a key role in the pathogenicity of different bacterial species. However, this is poorly understood in H. pylori. In this study, we investigated the effect of lactate on H. pylori adhesin gene expression and the regulation of host inflammatory cytokines. We show that the bacterial adhesins SabA and LabA were downregulated at the transcriptional level during incubation of H. pylori with lactate. Downregulation of sabA required the involvement of the two-component system ArsRS, while labA was regulated via the CheA/CheY system, indicating differences in the regulation of these genes in response to lactate. The levels of the proinflammatory cytokines TNF and IL-6 in H. pylori-stimulated macrophages were reduced when lactate was present. Interestingly, glucose did not prevent the secretion of these cytokines. Taken together, our data suggest that lactate affects H. pylori adhesin gene expression and the host response upon infection.
Development and validation of a predictive model for the risk of developing trichomonas vaginitis in women
Authors: Li Qi , Li Yaqin , Bai Ying , Zhang Honglei , Zhao Weihong 
Published: November 2022

AbstractTrichomonas vaginitis (TV) is the most common non-viral sexually transmitted infection (STI) worldwide. The high prevalence of TV combined with mild or asymptomatic early symptoms leads to clinical vulnerability from delayed diagnosis. Latent infection can increase the incidence of pelvic infections, infertility, and adverse pregnancy complications. Data from 898 women who underwent vaginal flora testing from June 2014 to December 2014 were used to create a nomogram to assess the risk of TV in women in order to guide TV prevention and clinical intervention. The prediction model was evaluated in terms of identification, calibration, and clinical utility using the C-index, calibration plots, decision curve analysis, and internal validation. Predictors in the TV nomogram included age, occupation, yearly income, tea drinking, bathing frequency, menopause, spontaneous abortion, use of contraceptives, history of gynecological surgery, and HPV infection. The C-index of the TV risk prediction model was 0.732 (95% confidence interval: 0.695–0.768). It showed good discriminatory and predictive power. Decision curve analysis indicated that the nomogram had a good net benefit when the threshold probability of TV in women was 2–80%. The established TV prediction model easily, accurately, and quickly predicts the risk of TV onset.
Cone-beam CT delta-radiomics to predict genitourinary toxicities and international prostate symptom of prostate cancer patients: a pilot study
Authors: Delgadillo Rodrigo , Spieler Benjamin O. , Deana Anthony M. , Ford John C. , Kwon Deukwoo , Yang Fei , Studenski Matthew T. , Padgett Kyle R. , Abramowitz Matthew C. , Dal Pra Alan , Stoyanova Radka , Dogan Nesrin 
Published: November 2022

AbstractFor prostate cancer (PCa) patients treated with definitive radiotherapy (RT), acute and late RT-related genitourinary (GU) toxicities adversely impact disease-specific quality of life. Early warning of potential RT toxicities can prompt interventions that may prevent or mitigate future adverse events. During intensity modulated RT (IMRT) of PCa, daily cone-beam computed tomography (CBCT) images are used to improve treatment accuracy through image guidance. This work investigated the performance of CBCT-based delta-radiomic features (DRF) models to predict acute and sub-acute International Prostate Symptom Scores (IPSS) and Common Terminology Criteria for Adverse Events (CTCAE) version 5 GU toxicity grades for 50 PCa patients treated with definitive RT. Delta-radiomics models were built using logistic regression, random forest for feature selection, and a 1000 iteration bootstrapping leave one analysis for cross validation. To our knowledge, no prior studies of PCa have used DRF models based on daily CBCT images. AUC of 0.83 for IPSS and greater than 0.7 for CTCAE grades were achieved as early as week 1 of treatment. DRF extracted from CBCT images showed promise for the development of models predictive of RT outcomes. Future studies will include using artificial intelligence and machine learning to expand CBCT sample sizes available for radiomics analysis.
Effects of virtual target size, position, and parallax on vergence-accommodation conflict as estimated by actual gaze
Authors: Lin Chiuhsiang Joe , Canny Susmitha 
Published: November 2022

AbstractDue to the increased utilization of stereoscopic displays, the scope of the vergence–accommodation conflict has been studied extensively to reveal how the human visual system operates. The purpose of this work was to study the phenomenon of vergence–accommodation conflict by comparing the theoretical eye vergence angle (vergence response) and gaze-based eye vergence angle (vergence stimulus) based on eye tracker gaze data. The results indicated that the gaze-based eye vergence angle was largest at the greatest parallax. The result also revealed that the eye vergence angle accuracy was significantly highest at the nearest parallax. Generally, accuracy improves when virtual objects are put in the middle and close to participants' positions. Moreover, the signed error decreases significantly when the virtual object is in the middle. Based on the results of this study, we can gain a greater understanding of the vergence–accommodation conflict in the stereoscopic environment.
Quantifying fluorescent nanoparticle uptake in mammalian cells using a plate reader
Authors: Shin Hye Ji , Kwak Minjeong , Joo Sihwa , Lee Ji Youn 
Published: November 2022

AbstractIn keeping with the rapid expansion of nanoparticle applications, various tools are required to investigate how nanoparticles interact with biological entities. Many assays have been developed to measure the cellular uptake of nanoparticles, but so far most of the methods are laborious and often non-quantitative. Here we developed an easily accessible and robust quantitative measurement method of the level of cellular uptake of fluorescently labeled nanoparticles using a plate reader. In the experimental design, potential issues that could lead to measurement variation were identified and addressed. For example, the variation in fluorescence intensity of samples due to differences in cell number was normalized to optical density, which is a physical value corresponding to the cell number. Number of washings and sample handling temperature were optimized to minimize the interference by residual nanoparticles and possible efflux of nanoparticles from cells, respectively. The developed assay was demonstrated with the lymphocyte cell line Jurkat to measure the cellular uptake of fluorescently labeled 50 nm polystyrene beads, and its applicability was further confirmed with the lung carcinoma cell line A549 and another lymphocyte cell line RPMI8226.
Feasibility and clinical implications of 3-day bladder diary derived classification of female storage lower urinary tract symptoms
Authors: Hsiao Sheng-Mou , Lin Ho-Hsiung 
Published: November 2022

AbstractOur aim was to assess the feasibility of a bladder diary (BD) classification as a surrogate for urodynamic studies in women with storage lower urinary tract symptoms. A total of 3823 women who underwent urodynamic studies were reviewed. Nearly the scores of Patient Perception of Bladder Condition, Indevus Urgency Severity Scale and Overactive Bladder Symptom Score decreased gradually from the overactive bladder (OAB) wet-BD, OAB dry-BD, hypersensitive bladder (HSB) -BD, nocturia-BD to normal-BD groups (all p < 0.001). In addition, there is a trend that the rates of bladder oversensitivity decreased gradually from the OAB wet-BD, OAB dry-BD, HSB-BD, nocturia-BD to normal-BD groups (chi-square test, p < 0.001). Moreover, almost the volumes of first desire to void, normal desire to void, strong desire to void, and urgency increased gradually from the OAB wet-BD, OAB dry-BD, HSB-BD, nocturia-BD to normal-BD groups (all p < 0.001). Thus, this BD classification is correlated significantly with symptom severity, the rate of bladder oversensitivity, and bladder capacity. Nonetheless, a combination of urodynamics, clinical history, and BD is still needed for a thorough diagnosis, but that BD provides an efficient diagnosis in a proportion of patients.
Quantifying deep neural network uncertainty for atrial fibrillation detection with limited labels
Authors: Chen Brian , Javadi Golara , Hamilton Alexander , Sibley Stephanie , Laird Philip , Abolmaesumi Purang , Maslove David , Mousavi Parvin 
Published: November 2022

AbstractAtrial fibrillation (AF) is the most common arrhythmia found in the intensive care unit (ICU), and is associated with many adverse outcomes. Effective handling of AF and similar arrhythmias is a vital part of modern critical care, but obtaining knowledge about both disease burden and effective interventions often requires costly clinical trials. A wealth of continuous, high frequency physiological data such as the waveforms derived from electrocardiogram telemetry are promising sources for enriching clinical research. Automated detection using machine learning and in particular deep learning has been explored as a solution for processing these data. However, a lack of labels, increased presence of noise, and inability to assess the quality and trustworthiness of many machine learning model predictions pose challenges to interpretation. In this work, we propose an approach for training deep AF models on limited, noisy data and report uncertainty in their predictions. Using techniques from the fields of weakly supervised learning, we leverage a surrogate model trained on non-ICU data to create imperfect labels for a large ICU telemetry dataset. We combine these weak labels with techniques to estimate model uncertainty without the need for extensive human data annotation. AF detection models trained using this process demonstrated higher classification performance (0.64–0.67 F1 score) and improved calibration (0.05–0.07 expected calibration error).
Universal logic-in-memory cell enabling all basic Boolean algebra logic
Authors: Baek Eunwoo , Cho Kyoungah , Kim Sangsig 
Published: November 2022

AbstractAmong the promising approaches for implementing high-performance computing, reconfigurable logic gates and logic-in-memory (LIM) approaches have been drawing increased research attention. These allow for improved functional scaling of a chip, owing to the improved functionality per unit area. Although numerous studies have been conducted independently for either reconfigurable logic or LIM units, attempts to construct a hybrid structure based on reconfigurable logic and LIM units remain relatively rare. In this study, we merge reconfigurable logic gates and LIM units to achieve a universal logic-in-memory (ULIM) cell for enabling all basic Boolean logic operations and data storage in a single cell. A ULIM cell consisting of silicon memory devices with reconfigurable n- and p-program modes can reconfigure logic operations within the complete set of Boolean logic operations. Moreover, the ULIM cell exhibits memory behaviors for storing output logic values without supply voltages for a certain period, resulting in zero static power consumption. Hence, this study provides a way to realize high-performance electronics by utilizing the silicon devices with a hybrid function of reconfigurable logic and LIM.
Drivers and potential distribution of anthrax occurrence and incidence at national and sub-county levels across Kenya from 2006 to 2020 using INLA
Authors: Ndolo Valentina A. , Redding David William , Lekolool Isaac , Mwangangi David Mumo , Odhiambo David Onyango , Deka Mark A. , Conlan Andrew J. K. , Wood James L. N. 
Published: November 2022

AbstractAnthrax is caused by,Bacillus anthracis, a soil-borne bacterium that infects grazing animals. Kenya reported a sharp increase in livestock anthrax cases from 2005, with only 12% of the sub-counties (decentralised administrative units used by Kenyan county governments to facilitate service provision) accounting for almost a third of the livestock cases. Recent studies of the spatial extent ofB. anthracissuitability across Kenya have used approaches that cannot capture the underlying spatial and temporal dependencies in the surveillance data. To address these limitations, we apply the first Bayesian approach using R-INLA to analyse a long-term dataset of livestock anthrax case data, collected from 2006 to 2020 in Kenya. We develop a spatial and a spatiotemporal model to investigate the distribution and socio-economic drivers of anthrax occurrence and incidence at the national and sub-county level. The spatial model was robust to geographically based cross validation and had a sensitivity of 75% (95% CI 65–75) against withheld data. Alarmingly, the spatial model predicted high intensity of anthrax across the Northern counties (Turkana, Samburu, and Marsabit) comprising pastoralists who are often economically and politically marginalized, and highly predisposed to a greater risk of anthrax. The spatiotemporal model showed a positive link between livestock anthrax risk and the total human population and the number of exotic dairy cattle, and a negative association with the human population density, livestock producing households, and agricultural land area. Public health programs aimed at reducing human-animal contact, improving access to healthcare, and increasing anthrax awareness, should prioritize these endemic regions.
Improper weapons are a neglected category of harmful objects
Authors: Frugarello Paolo , Rusconi Elena , Job Remo 
Published: November 2022

AbstractAccording to legislation, objects are typically classified as weapons if they are offensive per se (referred to here as proper) and if they are adapted for use as weapons or carried with the intent of causing injury (referred to here as improper), with specific regulations on their usage and possession in public spaces. However, little evidence exists on the validity of this distinction in psychology, despite a widespread recognition of the importance of psychological states and subjective perceptions in risk assessment. We conducted an online survey to evaluate hazard perceptions in relation to three dimensions (dangerousness, frequency of events, controllability) of three object categories: proper weapons, improper weapons, and everyday objects. The data from our 300 respondents reveal that the three categories of objects differ from one another on the three dimensions. Moreover, hazard perceptions differ between males and females for improper weapons but less so for proper weapons. These findings suggest that proper and improper weapons are two psychologically distinct categories, albeit with fuzzy boundaries. Investigations into their differential properties may thus help improve risk assessment in security contexts.
Augmented screwdrivers can increase the performance of orthopaedic surgeons compared with use of normal screwdrivers
Authors: Fletcher James W. A. , Neumann Verena , Silva Juan , Burdon Abigail , Mys Karen , Panagiotopoulou Vasiliki C. , Gueorguiev Boyko , Richards R. Geoff , Whitehouse Michael R. , Preatoni Ezio , Gill Harinderjit S. 
Published: November 2022

AbstractOrthopaedic screws insertion can be trivialised as a simple procedure, however it is frequently performed poorly. Limited work exists defining how well surgeons insert screws or whether augmented screwdrivers can aid surgeons to reduce stripping rates and optimise tightness. We aimed to establish the performance of surgeons inserting screws and whether this be improved with screwdriver augmentation. 302 orthopaedic surgeons tightened 10 non-locking screws to what they determined to be optimum tightness into artificial bone sheets. The confidence in the screw purchase was given (1–10). A further 10 screws were tightened, using an augmented screwdriver that indicated when a predetermined optimum tightness was reached. The tightness for unstripped insertions under normal conditions and with the augmented screwdriver were 81% (95% CI 79–82%)(n = 1275) and 70% (95% CI 69–72%)(n = 2577) (p < 0.001). The stripping rates were 58% (95% CI 54–61%) and 15% (95% CI 12–17%) respectively (p < 0.001). The confidences when using the normal and augmented screwdrivers respectively were 7.2 and 7.1 in unstripped insertions and 6.2 and 6.5 in stripped insertions. Performance improved with an augmented screwdriver, both in reduced stripping rates and greater accuracy in detecting stripping. Augmenting screwdrivers to indicate optimum tightness offer potentially enormous clinical benefits by improving screw fixation.