bluuebunny/crossref_metadata_2025_split huggingface dataset:
Radiographic tumor burden score is useful for stratifying the overall survival of hepatocellular carcinoma patients undergoing resection at different Barcelona Clinic Liver
Authors: Li Wei-Feng , Liu Yueh-Wei , Wang Chih-Chi , Yong Chee-Chien , Lin Chih-Che , Yen Yi-Hao 
Published: October 2022

Abstract
Purpose:The Barcelona Clinic Liver Cancer (BCLC) staging system has been recommended for prognostic prediction. However, prognosis is variable at different BCLC stages. We aimed to evaluate whether the radiographic tumor burden score (TBS) could be used to stratify prognosis in different BCLC stages.
Methods: Hepatocellular carcinoma (HCC) patients undergoing liver resection (LR) at BCLC-0, -A, or -B stage in our institution in 2007–2018 were divided into derivation and validation cohorts. Overall survival (OS) was analyzed according to the TBS and BCLC stage. TBS cutoff values for OS were determined with X-tile.
Results: Of the 749 patients in the derivation cohort, 138 (18.4%) had BCLC-0, 542 (72.3 %) BCLC-A, and 69 (9.2 %) BCLC-B HCC; 81 (10.8%) had a high TBS (> 7.9), 474 (63.3%) a medium TBS (2.6–7.9), and 194 (25.9%) a low TBS (< 2.6). OS worsened progressively with increasing TBS in the cohort (p< 0.001) and in BCLC-A (p = 0.04) and BCLC-B (p = 0.002) stages. Multivariate analysis showed that the TBS was associated with OS of patients with BCLC-A (medium vs. low TBS: hazard ratio [HR] = 2.390, 95% CI = 1.024–5.581, p = 0.04; high vs. low TBS: HR = 3.885, 95% CI =1.443–10.456, p = 0.007) and BCLC-B (high vs. medium TBS: HR = 2.542, 95% CI = 1.077–6.002, p = 0.033) HCC. The TBS could also be used to stratify the OS of patients in the validation cohort (p< 0.001).
Conclusion: The TBS could be used to stratify the OS of the entire cohort and BCLC stages A and B of HCC patients undergoing LR.
Gastrodin regulates expression of angiotensin-SirT3 and proinflammatory mediators in reactive astrocytes via activated microglia
Authors: Zuo Han-Jun , Ren Xue-Qi , Guo Kun , Wang Peng-Xiang , Zhao Min , Li Juan-Juan 
Published: October 2022

Abstract
Use of Chinese herbal compounds have been widely explored in recent years to inhibit excessive proliferation and activation of astrocytes in brain injuries. Thus, it has been reported that Gastrodin, an anti-inflammatory agent, can effectively suppress microglia activation in rats with hypoxic-ischemia brain damage. This study was therefore aimed to determine if Gastrodin would exert a similar effect on reactive astrocytes and alleviate their inflammatory response through the renin-angiotensin system (RAS) and Sirtuin3 (SirT3). Expression of ATO, AT1 and SirT3 was detected in TNC-1 astrocytes, treated respectively with conditioned medium from BV-2 microglia with or without pretreatment of Gastrodin and lipopolysaccharide (LPS) by immunofluorescence and Western blotting. Along with this, expression of C3, S100A10, TNF-α and neurotrophic factors, including BDNF and IGF-1 expression was also evaluated. We showed here that TNC-1 astrocytes incubated in CM + LPS showed a marked increase in ATO, AT1, C3 and TNF-α when compared to cells in the BV-2 conditioned medium (CM), but that of S100A10 was reduced. Of note, TNC-1 astrocytes responded vigorously to conditioned medium derived from BV-2 microglia treated with Gastrodin + LPS when compared to the controls. This was evident by the decreased expression of the above-mentioned proteins, except for S100A10. As opposed to this, SirT3, IGF-1 and BDNF expression as determined by Western and immunofluorescence analysis was enhanced. The results suggest that Gastrodin inhibits the expression of RAS and proinflammatory mediators, but promotes the production of large amounts of neurotrophic factors in reactive astrocytes induced by LPS-stimulated activated microglia. Another novel finding of this study is the unequivocal demonstration that Gastrodin can promote the polarization of A2 phenotype that is regarded to be neuroprotective. This has added a new therapeutic perspective of this herbal compound that is gaining more attention in recent years.
Using observed and modelled heat fluxes for improved extrapolation of wind distributions
Authors: Floors Rogier , Peña Alfredo , Troen Ib 
Published: October 2022

Abstract
Modelling the horizontal and vertical variation of wind speed is crucial for wind energy applications. A model frequently used for this purpose is part of the Wind Atlas Analysis and Application program (WAsP). Here, we modify the model in WAsP to account for local atmospheric stability parameters.
Atmospheric stability effects are treated by using the impact of a temperature scale on the geostrophic drag law and the diabatic logarithmic wind profile. Using this approach, wind-direction dependent mean and standard deviation of a surface-layer temperature scale and a mean boundary-layer height scale can be obtained from either numerical weather prediction model output or observations to improve vertical extrapolations of Weibull wind speed distribution parameters.
The modified atmospheric stability model is validated at six flat sites in northwestern Europe. The surface-layer temperature scale is available from sonic anemometer measurements at three of the sites. At all sites the temperature scale is also estimated from reanalysis data and from mesoscale model output. The modified model improves the estimations of wind speed distributions when extrapolating to nearby locations, when using the temperature scale derived from either observations or mesoscale/reanalysis output.
Burnout Syndrome (Bs) Among Doctors During the Covid-19 Pandemic in Porto Velho-ro, Brazil
Authors: Reimann Raissa Santos , Romano Filippo , Cavatti Mariana Moraes 
Published: October 2022

Abstract
INTRODUCTION: Burnout syndrome (BS) occurs due to chronic exposure to stressors in the workplace. In addition to the stressful conditions to which doctors are exposed under usual situations, the COVID-19 pandemic has added greater pressure to the reality of these professionals.
OBJECTIVES: to identify the frequency of BS, and the possible associated risk factors, among physicians during the COVID-19 pandemic in Porto Velho-RO, Brazil.
METHODOLOGY: it is a cross-sectional study carried out through a questionnaire answered by physicians who signed the Informed Consent. The Maslach Burnout Inventory (MBI) was used as a basis.
RESULTS: The prevalence of BS in this study was 77.5% (107/138), with 43.48% (60/138) with BS in the emotional exhaustion and depersonalization dimensions, 29% (40/138) with emotional exhaustion alone, and 5.1% (7/138) only with depersonalization. The prevalence of low personal accomplishment was 17.4% (24/138), between these 95.8% (23/24) had BS. Statistical tests were carried out and suggest that being female, being under 30 years of age, having less than 5 years of working experience, being single, moving away from family during the pandemic, working or have worked on the frontline are risk factors for BS. While having children, being married, and living with the family are possible protective factors. The number of hours worked between physicians with and without BS was not statistically significant.
CONCLUSION: High levels of Burnout Syndrome were evidenced in the research participants. This study highlights correlated risk factors, with its results being consistent with the literature.
Adaptive Elastic-net Sliced Inverse Regression to Identify Risk Factors Affecting Covid-19 Disease Fatality Rate
Authors: Lashgari Sajedeh , Mohammadzadeh Mohsen , Ghaderi Foad 
Published: October 2022

Abstract
Identifying and modeling variables that affect coronavirus disease (Covid-19) infection fatality rate leads to better macro decisions and reduces the spread of the virus. Moreover, identifying these variables leads to better understanding and interpretation of the prediction models and can improves their performance. So far, different methods have been proposed for variable selection. However, they often face challenges such as non-modeling, high computational cost, overfitting, following certain assumptions like specific distribution, specific model, or lack of collinearity. They also do not consider sufficient dimensions. In this article, to overcome these limitations, we propose a method based on Adaptive Elastic-net Sliced Inverse Regression to identify risk factors for the Covid-19 disease in the presence of collinearity between explanatory variables. Considering the penalty of elastic-net and sliced inverse regression, this method leads to sufficient dimension reduction and presentation of a more stable and accurate model and prevents the occurrence of overfitting. We applied the proposed method to simulated data and new real-world Covid-19 disease dataset with 60 explanatory variables that we collected from available sources and prepared after going through pre-processing steps. We observed that the proposed method has significantly improved by reducing the experimental standard error of bootstrapping by 13\% compared to the previous methods for both datasets. So, it is an efficient and stable method for modeling and identifying risk factors for the Covid-19 disease. This method also has high generalizability, prevents overfitting, and can be used for other similar diseases.
The Effectiveness of Automated Speech Recognition in English with Native Thai Speakers
Authors: Savithi Charuay , Suttidee Arisaphat 
Published: October 2022

Abstract
Usability evaluation performance is one of the cornerstones of user interface design. This study presents the usability evaluation of Apple’s Siri based on Nielsen's usability heuristics. Apple’s Siri is one of the technologies of automatic speech recognition (ASR) that allows the user to use a natural language with smartphones and smart devices. The result shows that this feature still has a problem with the user who speaks English as a second language. This study may lead the developer to provide the best voice interfaces for the user who speaks English with a different accent.
Are anthropogenic soils from dumpsites suitable for arable fields? Evaluation of soil fertility and biomass response to elements
Authors: Opare Michael Asare 
Published: October 2022

Abstract
Background and purpose
The fertility of anthropogenic soils developed from dumpsites used for arable fields is not well-studied. The study aimed to evaluate the fertility of soils from an abandoned dumpsite in Awotan, Nigeria, by measurable indicators and assess the bioaccessibility of elements of identified plant species.
Methods
The study adopted multi-analytical approaches to determine the signatures of the soils and further parameterized the bioaccessibility of elements to plants.
Results
The comparatively high content of Ca and Na in the anthropogenic soil contributed to the slightly alkaline soil reaction against the slightly acidic control. The high amount of organic matter is well-indicated by the enrichment of organic C and N in the anthropogenic soil. Waste deposition significantly contributed to the high accumulation of macronutrients (P, Ca, K, S) and micronutrients (Mn, Na, Fe) sufficient for maximum plant growth and yields, with an adequate C/N ratio supporting effective mineralization. The high cation exchange capacity of the anthropogenic soil contributed to cations binding. Indiscriminate deposition resulted in a high accumulation of potentially toxic elements (PTEs; Cu, Zn, As, Cd, Pb) above permissible limits in agricultural soils following WHO limits. Potential effects on lives are evident by the high PTEs accumulation in roots and leaves of Chromolaena odorata, Saccopetalum tectonum, Passiflora foetida, and Senna siamea. These plant species exhibited various PTEs accumulation, especially excluding Cd and Pb.
Conclusion
Although anthropogenic soils remained fertile, the bioaccessibility of PTEs by plants indicates potential threats to consumers of crops and herbs produced from such sites.
More Alike than Different: Latina Immigrants’ Cancer Causal Attributions
Authors: Fiallos Katie , Owczarzak Jill , Bodurtha Joann , Margarit Sonia , Erby Lori H. 
Published: October 2022

Abstract

Latinos in the U.S. suffer health disparities including stage of disease at time of breast or colon cancer diagnosis. Understanding Latinas’ causal attributions of breast and colon cancer may provide insight into some of the individual level determinants of cancer disparities in this population. Cultural consensus analysis (CCA) is one way to study causal beliefs. The objective of this study was to describe Latina immigrants’ causal attributions of breast and colon cancer. We conducted Spanish-language interviews with 22 Latina immigrants using a qualitative exploratory design comprised of freelisting, ranking, and open-ended questions. Participants freelisted causes and risk factors for breast and colon cancer then ranked risk factors according to their perceived role in the development of each cancer. CCA was conducted on rank orders to identify whether a cultural consensus model was present. Participants answered semi-structured, open-ended questions regarding the risk factors and rankings. Interviews were transcribed and subjected to thematic analysis. CCA showed no consensus around rank of causes for either cancer. “Genetics” and “hereditary factors” ranked first and second on average across participants for both cancers. Based on interview data, participants were less aware of colon cancer than breast cancer. Participants’ causal attributions of breast and colon cancer were similar to those reported in studies of primarily non-Latina populations. While tailoring education in other ways may make it more acceptable, evidence suggests that it is appropriate for the information provided to Latina immigrant populations about breast and colon cancers to be similar to that provided to non-Latina patients.
Knowledge, Attitude and Perceptions about Cancer Genetic Testing in Clinical Practice in Karachi, Pakistan
Authors: Shafqat Shameel , Naseem Masooma , Rana Masooma , Naseem Zehra , Ahmed Warda , Musharraf Muhammad Daniyal , Zaheer Arisha , Shaikh Ahmed Safiullah , Musharraf Muhammad Bazil , Niaz Mahnoor , Khan Saifullah , Irfan Rabiya , Imran Areeba , Mehmood Zahid 
Published: October 2022

Abstract
Health care professionals (HCP) play an important role in the practical application of genetic screening tests but often feel inadequately prepared for cancer genetic testing (CGT) in clinical care. As the complexity of gene related malignancies increases, it demands HCPs’ preparedness to cater to patients’ needs. Therefore, our study aimed to assess the knowledge, attitude, and practices of HCPs in Pakistan regarding the application of cancer genetics. A cross-sectional survey was conducted from April 2022 to June 2022 amongst HCPs at a private and a governmental institution in Karachi, Pakistan. Non-probability random convenience sampling was used to select the population. A total of 210 HCPs, 56.7% (119) were included in this study. Most respondents from both hospitals deemed their knowledge inadequate, with only 2% (2) and 1.8% (2) being extremely knowledgeable, respectively. 68.6% (144) HCPs displayed a positive attitude towards CGT, with 55.2% (116) participants perceiving CGT in a positive light. As compared to the private sector, significantly more HCPs in the public sector dedicated ≥ 5 hours/week for CME (P = 0.006), and were better prepared to counsel patients (P = 0.021) and interpret results concerning CGT (P = 0.020). Additionally, screening tests for specific cancer types were popularly considered a worthwhile avenue of investment to improve the current state of CGT in our healthcare system [47.6% (N=100)]. Our results thus call upon the need for additional training concerning CGT. Understanding specific gaps in knowledge may further help enhance post-graduate training programs and eventually lead to effective incorporation of CGT into our healthcare setting.
HPLC-MS-MS quantification of short-chain fatty acids secreted by probiotic strains
Authors: Calvigioni Marco , Bertolini Andrea , Codini Simone , Mazzantini Diletta , Panattoni Adelaide , Celandroni Francesco , Zucchi Riccardo , Saba Alessandro , Ghelardi Emilia 
Published: October 2022

Abstract
Short-chain fatty acids (SCFAs) are the main by-products of microbial fermentations occurring in the human intestine and are directly involved in the host’s physiological balance. As impaired gut concentrations of acetic, propionic, and butyric acids are often associated with systemic disorders, the administration of SCFA-producing microorganisms has been suggested as attractive approach to solve symptoms related to SCFAs deficiencies. In this research, nine probiotic strains (Bacillus clausii NR, OC, SIN, and T, Bacillus coagulans ATCC 7050, Bifidobacterium breve DSM 16604, Limosilactobacillus reuteri DSM 17938, Lacticaseibacillus rhamnosus ATCC 53103, and Saccharomyces boulardii CNCM I-745) commonly included in commercial formulations were tested for their ability to secrete SCFAs by using an improved and sensitive protocol in high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS-MS). All tested microorganisms were shown to secrete acetic acid, with only B. clausii and S. boulardii additionally able to produce propionic and butyric acids. Quantitative differences in the secretion of SCFAs were also evidenced. The application of HPLC-MS-MS may help in the analysis of SCFA production by probiotics, especially for their administration as targeted bacteriotherapy to improve SCFAs deficiencies.
Controlling time-varying confounding in difference-in-differences studies using the time-varying treatments framework
Authors: Myint Leslie 
Published: October 2022

Abstract
This article clarifies how the biostatistical literature on time-varying treatments can provide tools for dealing with time-varying confounding in difference-in-differences studies. I use a simulation study to compare the bias and standard error of inverse probability weighting estimators from the time-varying treatments framework and from a difference-in-differences framework. I simulated longitudinal data over multiple time points using linear and logistic models. Confounders were time-varying and affected by prior treatment, a realistic occurrence in applied settings. Observed covariates were sufficient to control confounding in one simulation setting and insufficient in a second. Under realistic data settings, estimators from the time-varying treatments framework have lower bias than difference-in-differences estimators based on parallel trends assumptions. Estimators that combined ideas from both frameworks were least biased in settings with unmeasured time-varying confounders. The time-varying treatments framework provides estimation tools that can complement difference-in-differences tools in a wide range of applied settings. It also provides alternate estimands for consideration in policy settings.
On flows of Neural Ordinary Differential Equations that are solutions of universal dynamical systems
Authors: Arratia Argimiro , Ortiz Carlos , Romaní Marcel 
Published: October 2022

Abstract
Neural Ordinary Differential Equations (NODE) have emerged as a novel approach to deep learning, where instead of specifying a discrete sequence of hidden layers, it parameterizes the derivative of the hidden state using a neural network. The solution to the underlying dynamical system is a flow, and various papers have explored the universality of flows, in the senseof being able to approximate any analytical function.In this paper we present preliminary work aimed at identifying families of systems of ordinary differential equations (SODE) that are universal, in the sense that they encompass most of the systems of differential equations that appear in practice. Once one of these (candidate) universal SODEs is found, we define a process that generates a family of NODEs whose flows are precisely the solutions of this universal SODE.
We present three candidates for universal SODE family: the generalized Lotka-Volterra families of differential equations; the Riccati dynamical systems; and the S-systems.We present the NODE models built upon each one of these dynamical systems and a description of their appropriate flows together with some preliminary implementations of these processes and results on learning some analytical functions.
Current assumptions for quantitative microbial risk assessment (QMRA) of Norovirus contamination of drinking water catchments due to recreational activities: an update
Authors: Deere Dan , Ryan Una 
Published: October 2022

AbstractContamination of drinking water from Norovirus (NoV) and other waterborne viruses is a major public health concern globally. Increasingly, quantitative microbial risk assessment (QMRA) is being used to assess the various risks from waterborne pathogens and evaluate control strategies. As urban populations grow and expand, there is increasing demand for recreational activities in drinking water catchments. QMRA relies on context-specific data to map out the pathways by which viruses can enter water and be transferred to drinking water consumers and identify risk factors and appropriate controls. This review examines the current evidence base and assumptions for QMRA analysis of NoV and other waterborne viral pathogens and recommends numerical values based on the most recent evidence to better understand the health risks associated with recreators in Australian drinking water sources; these are broadly applicable to all drinking water sources where recreational access is allowed. Key issues include the lack of an agreed upon data and dose-response models for human infectious NoV genotypes, faecal shedding by bathers, the extent of NoV infectivity and aggregation, resistance (secretor status) to NoV and the extent of secondary transmission.
Determining the Therapeutic Potential of Experimental Antibacterial Agents: The Use of Animal Models
Authors: Alder Jeffrey D. 
Published: October 2022

Abstract:
Animal models of infection are the most predictive preclinical test for projecting clinical success of experimental antibacterial therapeutics. The first screen for antibacterial drug efficacy is usually prevention of mortality in animal models of infection. Secondary trials for drug efficacy measure the reduction of bacterial burden in defined body sites such as lung, kidney, and soft tissue. These trials determine potential clinical indications for the experimental compounds. Promising compounds are then advanced for additional testing in animal models to identify the key pharmacodynamic
parameter predictive of efficacy. The value of the pharmacodynamic parameter that yields efficacy is then numerically defined and related to the blood concentration of experimental drug needed for clinical efficacy. Animal trials to determine appropriate length of therapy are conducted at optimal pharmacodynamic values. Efficacy against relevant drug resistant bacteria should also be determined prior to clinical development. Preliminary toxicity studies are conducted during efficacy testing and safety margins should be known prior to bulk synthesis of drug for formal toxicity studies. At all stages of testing, appropriate clinical antibacterial drugs are used as positive controls. Proper use of animal models will keep the drug development pipeline clear of compounds with little probability of clinical efficacy. This testing program will cause. the selection of experimental anti-bacterial compounds with significant promise for rapid advancement through clinical trials to medical and commercial success.