bluuebunny/crossref_metadata_2025_split huggingface dataset:
CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis
Authors: Wang Yizhuo , Flowers Christopher R , Li Ziyi , Huang Xuelin 
Published: July 2022

AbstractSummaryIn the era of big data, machine learning techniques are widely applied to every area in biomedical research including survival analysis. It is well recognized that censoring, which is a common missing issue in survival time data, hampers the direct usage of these machine learning techniques. Here, we present CondiS, a web toolkit with graphical user interface to help impute the survival times for censored observations and predict the survival times for future enrolled patients. CondiS imputes a censored survival time based on its distribution conditional on its observed part. When covariates are available, CondiS-X incorporates this information to further increase the imputation accuracy. Users can also upload data of newly enrolled patients and predict their survival times. As the first web-app tool with an imputation function for censored lifetime data, CondiS web can facilitate conducting survival analysis with machine learning approaches.Availability and implementationCondiS is an open-source application implemented with Shiny in R, available free at: https://biostatistics.mdanderson.org/shinyapps/CondiS/.Supplementary informationSupplementary data are available at Bioinformatics online.
DelaySSAToolkit.jl: stochastic simulation of reaction systems with time delays in Julia
Authors: Fu Xiaoming , Zhou Xinyi , Gu Dongyang , Cao Zhixing , Grima Ramon 
Published: July 2022

AbstractSummaryDelaySSAToolkit.jl is a Julia package for modelling reaction systems with non-Markovian dynamics, specifically those with time delays. These delays implicitly capture multiple intermediate reaction steps and hence serve as an effective model reduction technique for complex systems in biology, chemistry, ecology and genetics. The package implements a variety of exact formulations of the delay stochastic simulation algorithm.Availability and implementationThe source code and documentation of DelaySSAToolkit.jl are available at https://github.com/palmtree2013/DelaySSAToolkit.jl.
IIFDTI: predicting drug–target interactions through interactive and independent features based on attention mechanism
Authors: Cheng Zhongjian , Zhao Qichang , Li Yaohang , Wang Jianxin 
Published: July 2022

AbstractMotivationIdentifying drug–target interactions is a crucial step for drug discovery and design. Traditional biochemical experiments are credible to accurately validate drug–target interactions. However, they are also extremely laborious, time-consuming and expensive. With the collection of more validated biomedical data and the advancement of computing technology, the computational methods based on chemogenomics gradually attract more attention, which guide the experimental verifications.ResultsIn this study, we propose an end-to-end deep learning-based method named IIFDTI to predict drug–target interactions (DTIs) based on independent features of drug–target pairs and interactive features of their substructures. First, the interactive features of substructures between drugs and targets are extracted by the bidirectional encoder–decoder architecture. The independent features of drugs and targets are extracted by the graph neural networks and convolutional neural networks, respectively. Then, all extracted features are fused and inputted into fully connected dense layers in downstream tasks for predicting DTIs. IIFDTI takes into account the independent features of drugs/targets and simulates the interactive features of the substructures from the biological perspective. Multiple experiments show that IIFDTI outperforms the state-of-the-art methods in terms of the area under the receiver operating characteristics curve (AUC), the area under the precision-recall curve (AUPR), precision, and recall on benchmark datasets. In addition, the mapped visualizations of attention weights indicate that IIFDTI has learned the biological knowledge insights, and two case studies illustrate the capabilities of IIFDTI in practical applications.Availability and implementationThe data and codes underlying this article are available in Github at https://github.com/czjczj/IIFDTI.Supplementary informationSupplementary data are available at Bioinformatics online.
How Did Levels of Psychological Distress and Perceptions of Workplace Support amongst Children’s Social Work Staff Change during the Covid-19 Pandemic?
Authors: Jones Rebecca K , Wilkins David , Bezeczky Zoe , Thompson Sarah 
Published: July 2022

AbstractCovid-19 brought about drastic changes in day-to-day life and working practices, and had a profound impact on the mental health and well-being of the general population. Certain professional groups have also been particularly affected. This study sought to explore how levels of psychological distress and perceptions of workplace support amongst social work staff changed during the pandemic. We present the results from a series of surveys conducted in four local authorities (LAs) in England, before and during the Covid-19 pandemic. Social workers and other social care staff (n = 62) were asked about their experiences of psychological distress, using the twelve-item General Health Questionnaire. Overall, we found the proportion of staff reporting elevated levels of psychological distress increased and, in line with previous studies involving social workers, was high relative to the general population. Yet, most staff also said they had high levels of support from managers and colleagues, whilst a small proportion reported an increased perception of workplace support during the pandemic, compared to before. We consider these findings in relation to Organisational Support Theory and reflect on the ability of LAs to provide effective support for social care staff.
Resilience and Resistance in the Community Sector: Organisational Challenges and Responses by the Australian DFV Sector in the Time of COVID-19 Pandemic
Authors: Clarke Joanne , Morley Christine , Warren Shane , Carrington Kerrie , Vitis Laura , Ryan Vanessa , Ball Matthew 
Published: July 2022

Abstract
The COVID-19 pandemic led to increases in family violence in Australia and elsewhere. In response, organisations in the domestic and family violence (DFV) sector, had to adapt to the emerging public health measures and worked collaboratively to protect the most vulnerable in the community. These services, including courts, rapidly transformed their methods of service delivery that are likely to continue for some time. But what have been the implications/impacts of these rapid changes on the DFV service sector in Australia? How have these impacts informed the future needs of the DFV sector? And what is needed to strengthen this community sector of the future? This article reports on the findings of a national research project examining the impacts of COVID-19 on the DFV service sector and the adaptations and innovations that emerged in response. The study highlights that the surge in demand for services put pressure on an already overwhelmed workforce/service sector and provided an opportunity for front line workers to contribute to building a robust sector to respond to future crisis events. These findings have significant implications for future DFV sector service delivery, and for the social work profession as a whole.
In vivo quantitative imaging of hippocampal inflammation in autoimmune neuroinflammatory conditions: a systematic review
Authors: Nwaubani P , Cercignani M , Colasanti A 
Published: July 2022

AbstractThe hippocampus is a morphologically complex region of the brain limbic system centrally involved in important cognitive, affective, and behavioural regulatory roles. It has exquisite vulnerability to neuroinflammatory processes, with some of its subregions found to be specific sites of neuroinflammatory pathology in ex-vivo studies. Optimizing neuroimaging correlates of hippocampal neuroinflammation would enable the direct study of functional consequences of hippocampal neuroinflammatory pathology, as well as the definition of therapeutic end-points for treatments targeting neuroinflammation, and their related affective or cognitive sequelae. However, in vivo traditional imaging of the hippocampus and its subregions is fraught with difficulties, due to methodological challenges deriving from its unique anatomical characteristics. The main objective of this review is to provide a current update on the characterization of quantitative neuroimaging correlates of hippocampal neuroinflammation by focusing on three prototypical autoimmune neuro-inflammatory conditions [multiple sclerosis (MS), systemic lupus erythematosus (SLE), and autoimmune encephalitis (AE)]. We focused on studies employing TSPO-targeting positron emission tomography (PET), quantitative magnetic resonance imaging (MRI), and spectroscopy techniques assumed to be sensitive to neuroinflammatory tissue changes. We found 18 eligible studies (14, 2, and 2 studies in MS, AE, and SLE, respectively). Across conditions, the largest effect was seen in TSPO PET and diffusion-weighted MRI studies. No study examined neuroinflammation-related changes at the hippocampal subfield level. Overall, results were largely inconsistent due to heterogeneous imaging methods, small sample sizes, and different population studies. We discuss how these data could inform future study design and conclude by suggesting further methodological directions aimed at improving the precision and sensitivity of neuroimaging techniques to characterize hippocampal neuroinflammatory pathology in the human brain.
Estimating Analytical Errors of Glomerular Filtration Rate Measurement
Authors: Ognissanti Damiano , Andresen Bergström Moa , Theodorsson Elvar , Larsson Anders , Nordin Gunnar , Hammarsten Ola 
Published: July 2022

Abstract

Background
Few studies are available on how to optimize time points for sampling and how to estimate effects of analytical uncertainty when glomerular filtration rate (GFR) is calculated.

Methods
We explored the underlying regression mathematics of how analytical variation of a kidney filtration marker affects 1-compartment, slope-and-intercept GFR calculations, using 2 or 3 time points following a bolus injection, and used this to examine the results from 731 routine 3-point iohexol plasma clearance measurements.

Results
GFR calculations inflated analytical uncertainty if the time points were taken too late after the bolus injection and too close after each other. The uncertainty in GFR calculation was, however, the same as the analytical uncertainty if optimal time points were used. The middle of the 3 samples was of little value. The first sample should be taken as early as possible after the distribution phase. Sampling before the patient specific half-life of the kidney filtration marker resulted in an exponential error inflation whereas no error inflation was seen when sampling occurred later than 2 half-lives. Theoretical GFR uncertainty could be lowered 3.2-fold if individually optimized time points for sampling had been used in our 731 clearance measurements. Using Taylor expansions to approximate the moments of transformed random variables, the uncertainty of an individual GFR measurement could be calculated in a simple enough way to be applicable by laboratory software.

Conclusions
We provide a theoretical foundation to select patient-optimal time points that may both limit errors and allow calculation of GFR uncertainty.
An unusual case of stabbing chest pain …literally: a case report
Authors: Santos João , Neto Vanda , Marmelo Bruno , Correia Miguel 
Published: July 2022

Abstract

Background
Cardiac surgery is associated with a significant risk of potential postoperative complications. We describe a case of a patient with an unusual late cardiac perforation caused by a needle used to fix temporary epicardial pacing wires to the skin, which slowly migrated across subcutaneous tissues for 2 years following postoperative period.

Case summary
We report a case of middle-aged woman admitted to the cardiac intensive care unit due to suspected acute myocardial infarction. Multimodality imaging revealed the presence of an unusual intracardiac foreign body, located inside the interventricular septum and perforating towards the left atria, complicated by a small intracardiac fistula between septal coronary branches and the right ventricle. Analysis of previous examinations revealed that a needle used to fix temporary epicardial pacing wires to the skin had been left inside the patient, beneath the level of the diaphragm, after cardiac surgery in 2018. This foreign body slowly migrated across the diaphragm, towards the mediastinum, finally lodging inside the heart, after a period of 3 years. The patient was referred to cardiac surgery for foreign body retrieval.

Discussion
We describe an unusual case of cardiac perforation caused by a needle used to fix these wires to the skin, which migrated across subcutaneous tissues and finally lodged inside the basal interventricular septum and left atria. Full compliance with standardized surgical care bundles, as well as the implementation of a structured incident reporting system, is of upmost importance to prevent postoperative complications and improve surgical care.
Fulminant myocarditis after the first dose of mRNA-1273 vaccination in a patient with previous COVID-19: a case report
Authors: Horiuchi Kohei , Kosugi Shumpei , Abe Haruhiko , Ueda Yasunori 
Published: July 2022

Abstract

Background
COVID-19 vaccines have shown success in protecting people worldwide, although serious adverse effects have been reported in very rare cases.

Case summary
A 32-year-old male with a prior medical history of mild COVID-19 infection developed fulminant myocarditis five days after mRNA-1273 vaccination (first dose), which was confirmed using endomyocardial biopsy. He acutely developed respiratory failure and cardiogenic shock with ventricular tachycardia, but recovered completely with short-term high-dose steroid therapy and mechanical cardiac support, which is the recommended treatment for fulminant lymphocytic myocarditis.

Discussion
COVID-19 vaccine-induced myocarditis varies from mild to severe. In the present case, the patient was treated as for fulminant lymphocytic myocarditis and recovered relatively quickly. The mechanism of COVID-19 vaccine-associated myocarditis needs to be urgently investigated.
Behavioural Economics and ISDS Reform: A Response to Maria Laura Marceddu and Pietro Ortolani
Authors: Grant Thomas D , Kieff F Scott 
Published: July 2022

Abstract
Academic investigators have used behavioural economics, a method developed originally to study consumers and their sentiments towards products, to study matters of public policy. A recent article in the European Journal of International Law – ‘What Is Wrong with Investment Arbitration? Evidence from a Set of Behavioural Experiments’ – gives a detailed summary of a series of experiments performed in order to study public sentiment towards investment arbitration. The investigators, Maria Laura Marceddu and Pietro Ortolani observe that public sentiment improves towards the outcome of a dispute settlement procedure when survey respondents are told that the procedure was a ‘court’ with tenured judges, and it worsens when they are told that it was ‘arbitration’ with temporary appointees. From their observations, Marceddu and Ortolani conclude that an international investment court, such as that which the European Union promotes, is a good idea. We suggest, however, that a further inquiry should investigate in greater detail public understanding of what qualities the individuals who serve as judges or arbitrators ought to display, as distinct from the institutional format in which dispute settlement takes place.
Modeling Individual Extended Attack Wildfire Suppression Expenditures in British Columbia
Authors: MacMillan Robert , Sun Lili , Taylor Stephen W 
Published: July 2022

AbstractWe developed models of suppression expenditures for individual extended attack fires in British Columbia using parametric and nonparametric machine-learning (ML) methods. Our models revealed that suppression expenditures were significantly affected by a fire’s size, proximity to the wildland–urban interface (WUI) and populated places, a weather based fire severity index, and the amount of coniferous forest cover. We also found that inflation-adjusted individual fire suppression expenditures have increased over the 1981 to 2014 study period. The ML and parametric models had similar predictive performance: the ML models had somewhat lower root mean squared errors but not on mean average errors. Better specification of fire priority as well as resource constraints might improve future model performance.
Rapid quantification of acid value in frying oil using iron tetraphenylporphyrin fluorescent sensor coupled with density functional theory and multivariate analysis
Authors: Gu Haiyang , Dong Yining , Lv Riqin , Huang Xingyi , Chen Quansheng 
Published: July 2022

Abstract
A metalloporphyrin-based fluorescent sensor was developed to determine the acid value in frying oil. The electronic and structural performances of iron tetraphenylporphyrin (FeTPP) were theoretically investigated using time-dependent density functional theory and density functional theory at the B3LYP/LANL2DZ level. The quantified FeTPP-based fluorescent sensor results revealed its excellent performance in discriminating different analytes. In the present work, the acid value of palm olein was determined after every single frying cycle. A total of 10 frying cycles were conducted each day for 10 consecutive days. The FeTPP-based fluorescent sensor was used to quantify the acid value, and the results were compared with the chemical data obtained by conventional titration method. The synchronous fluorescence spectrum for each sample was recorded. Parallel factor analysis was used to decompose the three-dimensional spectrum data. Then, the support vector regression (SVR), partial least squares, and back-propagation artificial neural network methods were applied to build the regression models. After the comparison of the constructed models, the SVR models exhibited the highest correlation coefficients among all models, with 0.9748 and 0.9276 for the training and test sets, respectively. The findings suggested the potential of FeTPP-based fluorescent sensor in rapid monitoring of frying oil quality and perhaps also in other foods with higher oil contents.
Spatio-temporal variations in glass eel recruitment at the entrance pathways of a Mediterranean delta
Authors: Bouchard Colin , Drouineau Hilaire , Lambert Patrick , Boutron Olivier , Nicolas Delphine 
Published: July 2022

AbstractUnderstanding spatio-temporal dynamics of glass eel recruitment is necessary to characterize eel population status and the stock of future elvers. Despite numerous studies that have characterized recruitment across Europe, multiple systems along the Mediterranean coasts need a deeper look. We built a Bayesian State-Space Model to investigate the temporal variations in glass eel recruitment in the Rhône delta (France). The model was suited to address the spatial heterogeneity due to the complexity of this system constituted by numerous entrance pathways. Over 13 years, we found inter-annual variations without a particular trend. Here, an overall migration peak occurred in February–March for the system, but substantial spatial variations in the resulting recruitment were visible. Spatial variations in the inter-annual dynamics and migration peak pointed out the necessity to account for spatial heterogeneity in the dynamics of glass eel recruitment. The highlighted inter-annual variations are consistent with analysis of coincident time-series in other sites in Europe (e.g. WGEEL), and the migration peak’s timing is similar to peaks observed in other estuaries. Spatial variations in the migration peak suggest a potential effect of local environment conditions on the recruitment. Our model provided a suitable approach to investigate temporal variations while accounting for spatial heterogeneity.
Spatial and temporal variability of spawning and nursery grounds of Loligo forbesii and Loligo vulgaris squids in ecoregions of Celtic Seas and Greater North Sea
Authors: Laptikhovsky Vladimir , Allcock A Louise , Barnwall Leigh , Barrett Christopher , Cooke Gavan , Drerup Christian , Firmin Christopher , Lozach Sophie , MacLeod Eleanor , Oesterwind Daniel , Petroni Michael , Robin Jean-Paul , Sheerin Edel , Power Anne-Marie , Pierce Graham J 
Published: July 2022

Abstract
The inshore commercial squids, Loligo vulgaris and L. forbesii, co-occur in the ecoregions of Celtic Seas and Greater North Sea but the spatio-temporal structure of their spawning ranges is poorly understood. To help solve the problem, data sets collected during the last 30 years by British, German, French, and Irish scientists, as well as observations from multinational Citizen Science, were combined. Spawning grounds of L. forbesii were found to form an external semi-circle around the spawning grounds of L. vulgaris, with the latter being centred on the English Channel and southernmost North Sea. The nursery grounds of both species appear to coincide with the respective spawning grounds, though L. forbesii makes much wider use of the North Sea. Seasonally, the position of the spawning grounds of both species is driven by the local temperature regime, although this is possibly subject to interannual variability. Spawning of both species begins around November and gradually progresses eastward following favourable currents and increasing water temperatures. Spawning in both species is mostly over by July, though some egg masses persist until August–November. Nursery grounds follow the same seasonal shift from west to east, at least in L. forbesii.
Necessity or balancing: The protection of rights under different proportionality tests—Experimental evidence
Authors: Steiner Talya , Netzer Liat , Sulitzeanu-Kenan Raanan 
Published: July 2022

Abstract
Despite its global proliferation, there is no standard formulation for proportionality analysis. The result is debate over the optimal formulation and application of the doctrine and the ramifications of adopting different versions. A subset of this debate relates to which element of the doctrine provides rights with greater protection against competing public interests. Although this dispute is essentially empirical, arguments on the matter remain strictly theoretical. This study presents the first experimental analysis of the effects of specific subtests of proportionality analysis on the level of protection afforded to rights. We find strong evidence that applying proportionality in terms of the necessity test—whether there are less restrictive means—results in greater protection of rights in policy decisions than does applying proportionality in terms of the strict proportionality test—balancing the benefit against the harm. The findings suggest that including a necessity component within the proportionality doctrine, and emphasizing it as a central stage of the analysis, can enhance the protection of rights in decisions regarding rights-restricting policy.