bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparison Analysis on Car User Decision When Faced with Different Congestion Pricing Policy (Case Study: Jakarta Metropolitan Area)
Authors: Alvinsyah  , Fathurrizqi Muhammad
Published: May 2022

This research aims to analyze the car user’s decision in their mode choice when faced with two different congestion pricing, namely Road Pricing (RP) and Parking Pricing (P2) policy scheme. The comparison analysis is conducted through the developed binomial logit model both for RP and P2 policy schemes. Data is collected by utilizing a stated preference survey, where the car user is asked their preference towards the mode choice on a given set of price and timesaving combination for both policies. Then the utility function for each policy is established by conducting some statistical procedures to have a feasible and reasonable model. Having set the utility functions, the validity test is carried out to the developed model using a different set of data from the survey. Further analysis is done to select the model that satisfies the statistical feasibility and the validity threshold number. Comparison to both different choice models yields different decisions represented in the form of shifting mode percentages. The research results show that the RP policy scheme tends to shift the car user higher than the P2 policy scheme at the same total additional charging fare.
Integrated Transport System in Yogyakarta, Indonesia: Aspect Policy
Authors: Setiawan Danny , Susilo Dibyo , Setyadi Arien
Published: May 2022

The application of an intermodal transportation integration system will make it easier for people to carry out activities, guarantee travel travel time, and optimize the use of public transportation, and have an impact on reducing the use of private vehicles which can affect road performance. The policy for implementing the transportation integration system needs to be considered in order to accommodate travel activities by following regional development conditions. This study aims to determine the management integration and the constraints in implementing the transportation integration system. This study uses a qualitative method by taking into account the aspects of the policy which involve elements of regulators, operators and consumers. This research shows that the regulator is able to carry out the management of the transportation integration system through the implementation of government affairs in the transportation sector, however, there are obstacles in the form of regulatory linkages, coordination and limited authority. So it is necessary to optimize the role of regulators to be able to coordinate intensely with public transport operators in order to realize an integrated transportation system management that can meet the travel needs of the community.
Verification of vertical temperature profiles in the COSMO and ICON models with available observational data
Authors: Gochakov A V , Tokarev V M , Kolker A B
Published: May 2022

This paper presents results of numerical estimates of vertical temperature profiles in the COSMO and ICON NWP models. Data from two vertical profilers, an MTP-5 microwave temperature profiler and a classic AVK-type radiosonde, are used for the estimates. Mean errors, correlation coefficients, and root-mean-square errors are calculated for different seasons. The simulation results are analysed depending on configurations of the horizontal resolution of the models and between the models. The estimates are plotted, and comparisons are made between the models using each of the measurement types: between different measurements for each model. The response to spatial variability in the measurements and model grid cells is assessed. Conclusions are formulated by comparing the quality of reproduction of the atmospheric boundary layer between the models and the model configurations. The findings provide useful information for the interpretation of modeling results by forecasters.
Measurements of aerosol particle concentrations in the atmosphere of the south-eastern coast of Lake Baikal (at Boyarsky station) in the summer of 2020
Authors: Tcydypov V V , Zhamsueva G S , Zayakhnov A S , Dementeva A L , Balzhanov T S
Published: May 2022

Atmospheric measurements of aerosol particle concentrations were made at a station named Boyarsky, the south-eastern coast of Lake Baikal (Russia) in the summer of 2020. The measurement period was conventionally divided into two ranges: 1) the smoke emission period of July 17-25; 2) the period of weakening of the influence of smoke emissions from forest fires in the neighbouring regions (from 14 August to 10 September). The diurnal behaviour of the total number concentrations of ultrafine particles in the size range from 5 to 200 nm (UFA) and submicron aerosols (SMA) from 0.2 to 1 μm was studied. The mean concentrations of UFA and SMA are 2705 (±1791) cm−3 and 40 (±19) cm−3 in July; 1247 (±780) cm−3 and 57 (±58) cm−3 in August; 1205 (±764) cm−3 and 37 (±19) cm−3 in September, respectively (the values in parentheses represent the respective standard deviations). The temporal evolution of the UFA particle number concentrations has shown a pronounced variation with lower concentrations in August-September and higher concentrations in July, whereas the diurnal patterns have been mostly found to be strongly influenced by the wildfire emissions. A strong relationship between the total particle number concentration has been established with the concentration of nitrogen dioxide NO2 (R =0.81), O3 (R = 0.66) and a weaker one with the concentration of sulphur dioxide (R =0.46). The thus obtained data on aerosol particle concentrations have been used to identify the events of bursts of nanoparticle formation in the atmosphere.
Considerable Arctic Sea ice loss as a factor of cold weather and heavy snowfalls in Eurasia
Authors: Frolov D
Published: May 2022

There goes climate warming on the Earth. An especially tremendous warming goes in the Arctic. This causes shrinking of the sea ice extent in the Arctic. Considerable Arctic Sea ice loss can lead to some extra evaporation of water vapor from the sea surface and saturation of the atmosphere with water vapor. Due to atmospheric circulation, extreme temperature anomalies and heavy snowfalls can appear in the following winter season in the lower latitudes, according to a number of studies. Some warm winters in Eurasia and America are associated with a situation in the Arctic where an extremely stable area of low pressure in the vicinity of the North Pole was present during a long time period and did not let cold air masses to move away from its borders. As a consequence, in most of the territory of Russia, USA, Northern Europe, and Eastern Canada the temperature of the winter months was a few degrees more than the usual one, for example in 2019/2020 winter months. The resulting destruction of the North Pole vortex and coming of cold air masses to Eurasia and America lead to a cold snowy winter.
Quality assessment of surface temperature reproduction by a model archive, the COSMO-CLM Russian Arctic hindcast, based on station data
Authors: Duntsev Sergey , Platonov Vladimir
Published: May 2022

The COSMO-CLM Russian Arctic hindcast data are compared with station data on monthly and long-term timescales using surface air temperature data at 146 weather stations in the study region. Some of the climatological ETCDDI indices are calculated, and the quality of the model archive reproduction of mean and extreme 2 m temperatures is evaluated. Generally, the hindcast succeeds in reproducing the thermal regime of the Arctic. The existing errors are caused by the large distances of the nearest model grid points from a station and the inaccuracies in the coastline or surface elevation description. The model underestimates the mean monthly temperatures by one degree on the average. The hindcast shows a tendency to underestimate the temperatures in the western part of the region, which has a mild climate, and to overestimate the low temperatures in the severe climate regions.
Digital Transformation of the Hydrometeorological Support for the Users - a Basis for Improving the Safety of Population and Enterprises
Authors: Viazilov E D
Published: May 2022

Major directions in solving problems of adaptation of enterprises and population to natural disasters are presented. This is done with an end-to-end technology of user support which begins with observations and finishes with decision-making in the business processes of enterprises. Increasing the awareness for the business leaders and the public about possible impacts of the disasters is a need. The heads of enterprises must receive recommendations for making decisions to prevent or reduce these impacts. It is proposed to solve this problem by a digital transformation and a new paradigm of hydrometeorological support for the users. The main software components of the end-to-end technology include tools for integration of distributed and heterogeneous data by autonomously detecting the anomalies of the current values from the local threshold values. This information is delivered to the users by mobile Internet devices. An Information Panel and MeteoMonitor applications have been developed. To increase the information delivery to the enterprise heads and the public, decision support tools are created. Some tools for assessing the potential damage and calculating the preventive actions cost will be provided. It is proposed to organize a knowledge base in the form of local threshold values of disaster indicators. The knowledge base is to be created on the possible impacts of climate change and disasters on enterprises and population for various levels of danger based on climatic, observed, and predictive information.
Inverse modeling of atmospheric chemistry with a differential evolution solver: Inverse problem and Data assimilation
Authors: Penenko A V , Konopleva V S , Penenko V V
Published: May 2022

In this paper, we numerically compare an inverse problem for an atmospheric chemistry model, when all the measurement data is available a priory, to a corresponding data assimilation problem when the data are obtained in some portions during the simulation. In both cases, we reconstruct the unobservable parts of the model state function by the observable ones (i.e., solve a continuation problem). This is done by identifying the model reaction rate parameters with the available measurement data by solving an optimization problem with a derivative-free differential evolution solver. In our numerical experiments, the inverse problem formulation of the continuation problem has not necessarily provided better results than the data assimilation formulation despite the latter being more limited in the measurement data.
Large-scale single-cell encapsulation in microgels through metastable droplet-templating combined with microfluidic-integration
Authors: Zhang Haoyue , Zhang Liyuan , An Chuanfeng , Zhang Yang , Shao Fei , Gao Yijie , Zhang Yonghao , Li Hanting , Zhang Yujie , Ren Changle , Sun Kai , He Wei , Cheng Fang , Wang Huanan , Weitz David A
Published: May 2022

Current techniques for the generation of cell-laden microgels are limited by numerous challenges, including poorly uncontrolled batch-to-batch variations, processes that are both labor- and time-consuming, the high expense of devices and reagents, and low production rates; this hampers the translation of laboratory findings to clinical applications. To address these challenges, we develop a droplet-based microfluidic strategy based on metastable droplet-templating and microchannel integration for the substantial large-scale production of single cell-laden alginate microgels. Specifically, we present a continuous processing method for microgel generation by introducing amphiphilic perfluoronated alcohols to obtain metastable emulsion droplets as sacrificial templates. In addition, to adapt to the metastable emulsion system, integrated microfluidic chips containing 80 drop-maker units are designed and optimized based on the computational fluid dynamics simulation. This strategy allows single cell encapsulation in microgels at a maximum production rate of 10 ml h−1 of cell suspension while retaining cell viability and functionality. These results represent a significant advance toward using cell-laden microgels for clinical-relevant applications, including cell therapy, tissue regeneration and 3D bioprinting.
Trapping multiple absorbing particles in air using an optical fiber by photophoretic forces
Authors: Sil Souvik , Pahi Anita , Punse Aman Anil , Banerjee Ayan
Published: May 2022

We demonstrate photophoretic force-based optical trapping of multiple absorbing particles in air by loosely focusing a Gaussian beam emanating from a single mode fiber using convex lenses of different focal lengths, and investigate the dependence of the number of trapped particles and their sizes on the focal length. We observe the formation of particle chains at a particular focal length, and measure the axial dynamic range of optical trapping for each lens system. We then develop a numerical simulation to explain this observed dynamic range by estimating the temperature distribution across a particle surface, and determining the axial photophoretic force. Our simulation results are in reasonable agreement with experimental results. Interestingly, we also observe that the average size of trapped particles reduces as we increase the lens focal lengths. This is somewhat intriguing as each lens produces the same intensity profile, albeit at different axial distances. However, the axial intensity gradient reduces as the lens focal length is increased, which suggests that such gradients may somehow be involved in the mechanism of photophoretic confinement.
Analysis of hydroclimatic trends and variability and their impacts on hydropower generation in two river basins in Côte d’Ivoire (West Africa) during 1981–2017
Authors: Obahoundje Salomon , Diedhiou Arona , Kouassi Kouakou Lazare , Ta Marc Youan , Mortey Eric Mensah , Roudier Philippe , Kouame Didier Guy Marcel
Published: May 2022

Climate change (CC) and variability impacts on hydroelectric generation have become critical for hydropower management. The trends of inflow, outflow, reservoir water level, and storage as well as hydraulicity indices of three main dams in Côte d’Ivoire, namely Kossou and Taabo in the Bandama basin and Buyo in the Sassandra basin were examined during 1981–2017 and their impacts on hydropower generation were analyzed. Moreover, the hydropower generation sensitivity to CC of these dams was assessed using statistical analysis. The results reveal that the inflow is highly dependent on rainfall while the water level is highly influenced by the outflow, which is a function of the inflow to the reservoirs and water management policy. Furthermore, the Mann Kendall test revealed that temperature and potential evapotranspiration have increased significantly in all three sub-basins while precipitation shows a significant upward trend only within the Taabo dam catchment area. Meanwhile, inflow to reservoir increased significantly and greatly than precipitation probably due to land use/cover change. Precipitation and inflow show a strong correlation as energy generation is significantly and strongly correlated to outflow (inflow) in all stations (except Kossou). Furthermore, the energy generation at Buyo and Taabo dams is more sensitive to reservoir inflow, while that of Kossou dam is more affected by water level. In addition, the power of a given year is also dependent on the total rainfall of that year and/or the previous year depending on the plant.
MINE 2.0: enhanced biochemical coverage for peak identification in untargeted metabolomics
Authors: Strutz Jonathan , Shebek Kevin M , Broadbelt Linda J , Tyo Keith E J
Published: May 2022

Although advances in untargeted metabolomics have made it possible to gather data on thousands of cellular metabolites in parallel, identification of novel metabolites from these datasets remains challenging. To address this need, Metabolic in silico Network Expansions (MINEs) were developed. A MINE is an expansion of known biochemistry which can be used as a list of potential structures for unannotated metabolomics peaks. Here, we present MINE 2.0, which utilizes a new set of biochemical transformation rules that covers 93% of MetaCyc reactions (compared to 25% in MINE 1.0). This results in a 17-fold increase in database size and a 40% increase in MINE database compounds matching unannotated peaks from an untargeted metabolomics dataset. MINE 2.0 is thus a significant improvement to this community resource.

Availability and implementation

The MINE 2.0 website can be accessed at https://minedatabase.ci.northwestern.edu. The MINE 2.0 web API documentation can be accessed at https://mine-api.readthedocs.io/en/latest/. The data and code underlying this article are available in the MINE-2.0-Paper repository at https://github.com/tyo-nu/MINE-2.0-Paper. MINE 2.0 source code can be accessed at https://github.com/tyo-nu/MINE-Database (MINE construction), https://github.com/tyo-nu/MINE-Server (backend web API) and https://github.com/tyo-nu/MINE-app (web app).

Supplementary information

Supplementary data are available at Bioinformatics online.
Powerful molecule generation with simple ConvNet
Authors: Yu Hongyang K , Yu Hongjiang C
Published: May 2022

Motivation

Automated molecule generation is a crucial step in in-silico drug discovery. Graph-based generation algorithms have seen significant progress over recent years. However, they are often complex to implement, hard to train and can under-perform when generating long-sequence molecules. The development of a simple and powerful alternative can help improve practicality of automated drug discovery method.

Results

We proposed a ConvNet-based sequential graph generation algorithm. The molecular graph generation problem is reformulated as a sequence of simple classification tasks. At each step, a convolutional neural network operates on a sub-graph that is generated at previous step, and predicts/classifies an atom/bond adding action to populate the input sub-graph. The proposed model is pretrained by learning to sequentially reconstruct existing molecules. The pretrained model is abbreviated as SEEM (structural encoder for engineering molecules). It is then fine-tuned with reinforcement learning to generate molecules with improved properties. The fine-tuned model is named SEED (structural encoder for engineering drug-like-molecules). The proposed models have demonstrated competitive performance comparing to 16 state-of-the-art baselines on three benchmark datasets.

Availability and implementation

Code is available at https://github.com/yuh8/SEEM and https://github.com/yuh8/SEED. QM9 dataset is availble at http://quantum-machine.org/datasets/, ZINC250k dataset is availble at https://raw.githubusercontent.com/aspuru-guzik-group/chemical_vae/master/models/zinc_properties/250k_rndm_zinc_drugs_clean_3.csv, and ChEMBL dataset is availble at https://www.ebi.ac.uk/chembl/.

Supplementary information

Supplementary data are available at Bioinformatics online.
CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis
Authors: Liu Zhentao , Zhang Zhengdong , Liang Sheng , Chen Zhen , Xie Xiaoyao , Shen Tie
Published: May 2022

The number of instationary 13C-metabolic flux (INST-MFA) studies grows every year, making it more important than ever to ensure the clarity, standardization and reproducibility of each study. We proposed CeCaFLUX, the first user-friendly web server that derives metabolic flux distribution from instationary 13C-labeled data. Flux optimization and statistical analysis are achieved through an evolutionary optimization in a parallel manner. It can visualize the flux optimizing process in real-time and the ultimate flux outcome. It will also function as a database to enhance the consistency and to facilitate sharing of flux studies.

Availability and implementation

CeCaFLUX is freely available at https://www.cecaflux.net, the source code can be downloaded at https://github.com/zhzhd82/CeCaFLUX.

Supplementary information

Supplementary data are available at Bioinformatics online.
Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks
Authors: Weitz Philippe , Wang Yinxi , Kartasalo Kimmo , Egevad Lars , Lindberg Johan , Grönberg Henrik , Eklund Martin , Rantalainen Mattias
Published: May 2022

Motivation

Molecular phenotyping by gene expression profiling is central in contemporary cancer research and in molecular diagnostics but remains resource intense to implement. Changes in gene expression occurring in tumours cause morphological changes in tissue, which can be observed on the microscopic level. The relationship between morphological patterns and some of the molecular phenotypes can be exploited to predict molecular phenotypes from routine haematoxylin and eosin-stained whole slide images (WSIs) using convolutional neural networks (CNNs). In this study, we propose a new, computationally efficient approach to model relationships between morphology and gene expression.

Results

We conducted the first transcriptome-wide analysis in prostate cancer, using CNNs to predict bulk RNA-sequencing estimates from WSIs for 370 patients from the TCGA PRAD study. Out of 15 586 protein coding transcripts, 6618 had predicted expression significantly associated with RNA-seq estimates (FDR-adjusted P-value <1×10−4) in a cross-validation and 5419 (81.9%) of these associations were subsequently validated in a held-out test set. We furthermore predicted the prognostic cell-cycle progression score directly from WSIs. These findings suggest that contemporary computer vision models offer an inexpensive and scalable solution for prediction of gene expression phenotypes directly from WSIs, providing opportunity for cost-effective large-scale research studies and molecular diagnostics.

Availability and implementation

A self-contained example is available from http://github.com/phiwei/prostate_coexpression. Model predictions and metrics are available from doi.org/10.5281/zenodo.4739097.

Supplementary information

Supplementary data are available at Bioinformatics online.
Effect of Antiviral Treatment on Hepatitis B Virus Integration and Hepatocyte Clonal Expansion
Authors: Chow Ning , Wong Danny , Lai Ching-Lung , Mak Lung-Yi , Fung James , Ma Hoi-Tang , Lei Meng-Wai , Seto Wai-Kay , Yuen Man-Fung
Published: May 2022

Background

This study investigated the effect of nucleos(t)ide analogue (NUC) treatment on hepatitis B virus (HBV) DNA integration and hepatocyte clonal expansion, both of which are implicated in hepatocellular carcinoma (HCC) in chronic hepatitis B.

Methods

Twenty-eight patients receiving NUCs (11 lamivudine, 7 telbivudine, 10 entecavir) were included. All had liver biopsies at baseline and year 1, and 7 had a third biopsy at year 10. HBV DNA integration and hepatocyte clone size were assessed by inverse polymerase chain reaction.

Results

All patients had detectable HBV integration at baseline, with a median integration frequency of 1.01 × 109 per liver and hepatocyte clone size of 2.41 × 105. Neither integration frequency nor hepatocyte clone size correlated with age and HBV virologic parameters. After 1 year of treatment, HBV integration was still detectable in all patients, with a median of 5.74 × 108 integration per liver (0.22 log reduction; P = .008) and hepatocyte clone size of 1.22 × 105 (0.40 log reduction; P = .002). HBV integration remained detectable at year 10 of treatment, with a median integration frequency of 4.84 × 107 integration per liver (0.93 log reduction from baseline) and hepatocyte clone size of 2.55 × 104 (1.02 log reduction from baseline). From baseline through year 1 to year 10, there was a decreasing trend in both integration frequency and hepatocyte clone size (P = .066 and.018, respectively).

Conclusions

NUCs reduced both HBV DNA integration and hepatocyte clonal expansion, suggesting another alternative pathway besides direct viral suppression to reduce HCC risk. Our findings supported the notion for a long-term NUC treatment to prevent HCC.
Simplifying Treatment Criteria in Chronic Hepatitis B: Reducing Barriers to Elimination
Authors: Wong Robert J , Kaufman Harvey W , Niles Justin K , Kapoor Hema , Gish Robert G
Published: May 2022

Background

Early, sustained hepatitis B virus (HBV) DNA suppression reduces long-term risks of hepatocellular carcinoma. Chronic hepatitis B (CHB) treatment criteria are complex. Simplifying criteria will improve timely linkage to therapy. We evaluated treatment eligibility patterns among US patients with CHB and propose stepwise simplification of CHB treatment criteria.

Methods

Using 2016–2020 Quest Diagnostics data, we evaluated treatment eligibility among patients with CHB (2 positive HBV tests [HBV surface antigen, HBV e antigen, or HBV DNA] ≥6 months apart) using American Association for the Study of Liver Disease (AASLD), European Association for Study of the Liver (EASL), Asian Pacific Association for Study of the Liver (APASL), and Asian American Treatment Algorithm (AATA) criteria.

Results

Among 84 916 patients with CHB, 6.7%, 6.2%, 5.8%, and 16.4% met AASLD, EASL, APASL, and AATA criteria, respectively. Among treatment-ineligible patients with CHB, proportion with significant fibrosis (aspartate aminotransferase platelet ratio index >0.5) were 10.4%, 10.4%, 10.8%, and 7.7% based on AASLD, EASL, APASL, and AATA, respectively. In the proposed treatment simplification, the proportion of patients with CHB eligible for therapy increased from 10.3% for step 1 (HBV DNA >20 000 IU/mL, elevated alanine aminotransferase [ALT] level) to 14.1% for step 2 (HBV >2000 IU/mL, elevated ALT level), 33.5% for step 3 (HBV DNA >2000 IU/mL, any ALT level), and 87.2% for step 4 (detectable HBV DNA, any ALT level).

Conclusions

A large proportion of patients with CHB not meeting established treatment criteria have significant fibrosis. Simplifying criteria to treat all patients with detectable HBV DNA will reduce complexity and heterogeneity in assessing treatment eligibility, improving treatment rates and progress toward HBV elimination.
Comparison of Influenza and Coronavirus Disease 2019–Associated Hospitalizations Among Children Younger Than 18 Years Old in the United States: FluSurv-NET (October–April 2017–2021) and COVID-NET (October 2020–September 2021)
Authors: Delahoy Miranda J , Ujamaa Dawud , Taylor Christopher A , Cummings Charisse , Anglin Onika , Holstein Rachel , Milucky Jennifer , O’Halloran Alissa , Patel Kadam , Pham Huong , Whitaker Michael , Reingold Arthur , Chai Shua J , Alden Nisha B , Kawasaki Breanna , Meek James , Yousey-Hindes Kimberly , Anderson Evan J , Openo Kyle P , Weigel Andy , Teno Kenzie , Reeg Libby , Leegwater Lauren , Lynfield Ruth , McMahon Melissa , Ropp Susan , Rudin Dominic , Muse Alison , Spina Nancy , Bennett Nancy M , Popham Kevin , Billing Laurie M , Shiltz Eli , Sutton Melissa , Thomas Ann , Schaffner William , Talbot H Keipp , Crossland Melanie T , McCaffrey Keegan , Hall Aron J , Burns Erin , McMorrow Meredith , Reed Carrie , Havers Fiona P , Garg Shikha
Published: May 2022

Background

Influenza virus and SARS-CoV-2 are significant causes of respiratory illness in children.

Methods

Influenza- and COVID-19–associated hospitalizations among children <18 years old were analyzed from FluSurv-NET and COVID-NET, 2 population-based surveillance systems with similar catchment areas and methodology. The annual COVID-19–associated hospitalization rate per 100 000 during the ongoing COVID-19 pandemic (1 October 2020–30 September 2021) was compared with influenza-associated hospitalization rates during the 2017–2018 through 2019–2020 influenza seasons. In-hospital outcomes, including intensive care unit (ICU) admission and death, were compared.

Results

Among children <18 years, the COVID-19–associated hospitalization rate (48.2) was higher than influenza-associated hospitalization rates: 2017–2018 (33.5), 2018–2019 (33.8), and 2019–2020 (41.7). The COVID-19–associated hospitalization rate was higher among adolescents 12–17 years old (COVID-19: 59.9; influenza range: 12.2–14.1), but similar or lower among children 5–11 (COVID-19: 25.0; influenza range: 24.3–31.7) and 0–4 (COVID-19: 66.8; influenza range: 70.9–91.5) years old. Among children <18 years, a higher proportion with COVID-19 required ICU admission compared with influenza (26.4% vs 21.6%; P < .01). Pediatric deaths were uncommon during both COVID-19– and influenza-associated hospitalizations (0.7% vs 0.5%; P = .28).

Conclusions

In the setting of extensive mitigation measures during the COVID-19 pandemic, the annual COVID-19–associated hospitalization rate during 2020–2021 was higher among adolescents and similar or lower among children <12 years compared with influenza during the 3 seasons before the COVID-19 pandemic. COVID-19 adds substantially to the existing burden of pediatric hospitalizations and severe outcomes caused by influenza and other respiratory viruses.
A case report of recurrent takotsubo cardiomyopathy including the rare ‘inverted’ form
Authors: Carey Charles , Nucifora Gaetano , Macnab Anita
Published: May 2022

Background

Takotsubo cardiomyopathy (TC) is a disease that causes transient left ventricular (LV) dysfunction in multiple vascular territories in the absence of coronary artery disease. Takotsubo cardiomyopathy is typically associated with dilation and dyskinesia of the apical and mid-LV segments induced by acute emotional and/or physical stress. Here, we present a case of recurrent TC including one episode of inverted TC, which is a rare form where dyskinesia occurs in the basal segments with sparing of the apical segments.

Case summary

A 53-year-old female patient with a background history of chronic stress and anxiety was admitted with three episodes of recurrent TC over 4 years. The first episode in 2017 was triggered by an acute stressful event, but no major triggers were identified for the subsequent episodes. Although the first and third episodes displayed the signs of classical TC, the second episode was an inverted TC. Full cardiac function was restored after each episode. She now takes prognostic heart failure medications long term and mental health teams are trying to support her emotional wellbeing.

Discussion

This patient displayed a rare disease course involving three recurrent episodes of TC, including one instance of its inverted form. Although psychiatric conditions and emotional stress are acknowledged as risk factors for TC, further research is needed to assess whether mental health treatment following TC can prevent disease recurrence.
A case report of cardiac cysticercosis in a returning traveller: a rare cause of myocarditis
Authors: Littlewood Simon
Published: May 2022

Background

A 38-year-old male of Indian origin presented via ambulance directly to the cardiac catheter lab with chest pain and electrocardiogram changes suggestive of an ST-elevation myocardial infarction. Serum troponin was recorded at >10 000 ng/L.

Case summary

Angiogram revealed normal coronary arteries. Echocardiography showed myocardial lesions and a subsequent cardiac magnetic resonance imaging showed myocardial cysticercosis.

Discussion

This is a case of myocardial cysticercosis causing myocarditis. He was treated successfully with albendazole for Taenia solium infection and non-steroidal anti-inflammatory drugs and colchicine for myocarditis.
Data mining to retrieve smoking status from electronic health records in general practice
Authors: de Boer Annemarijn R , de Groot Mark C H , Groenhof T Katrien J , van Doorn Sander , Vaartjes Ilonca , Bots Michiel L , Haitjema Saskia
Published: May 2022

Aims

Optimize and assess the performance of an existing data mining algorithm for smoking status from hospital electronic health records (EHRs) in general practice EHRs.

Methods and results

We optimized an existing algorithm in a training set containing all clinical notes from 498 individuals (75 712 contact moments) from the Julius General Practitioners’ Network (JGPN). Each moment was classified as either ‘current smoker’, ‘former smoker’, ‘never smoker’, or ‘no information’. As a reference, we manually reviewed EHRs. Algorithm performance was assessed in an independent test set (n = 494, 78 129 moments) using precision, recall, and F1-score. Test set algorithm performance for ‘current smoker’ was precision 79.7%, recall 78.3%, and F1-score 0.79. For former smoker, it was precision 73.8%, recall 64.0%, and F1-score 0.69. For never smoker, it was precision 92.0%, recall 74.9%, and F1-score 0.83. On a patient level, performance for ever smoker (current and former smoker combined) was precision 87.9%, recall 94.7%, and F1-score 0.91. For never smoker, it was 98.0, 82.0, and 0.89%, respectively. We found a more narrative writing style in general practice than in hospital EHRs.

Conclusion

Data mining can successfully retrieve smoking status information from general practice clinical notes with a good performance for classifying ever and never smokers. Differences between general practice and hospital EHRs call for optimization of data mining algorithms when applied beyond a primary development setting.
Local Adaptation and the Evolution of Genome Architecture in Threespine Stickleback
Authors: Li Qiushi , Lindtke Dorothea , Rodríguez-Ramírez Carlos , Kakioka Ryo , Takahashi Hiroshi , Toyoda Atsushi , Kitano Jun , Ehrlich Rachel L. , Chang Mell Joshua , Yeaman Sam
Published: May 2022

Theory predicts that local adaptation should favor the evolution of a concentrated genetic architecture, where the alleles driving adaptive divergence are tightly clustered on chromosomes. Adaptation to marine versus freshwater environments in threespine stickleback has resulted in an architecture that seems consistent with this prediction: divergence among populations is mainly driven by a few genomic regions harboring multiple quantitative trait loci for environmentally adapted traits, as well as candidate genes with well-established phenotypic effects. One theory for the evolution of these “genomic islands” is that rearrangements remodel the genome to bring causal loci into tight proximity, but this has not been studied explicitly. We tested this theory using synteny analysis to identify micro- and macro-rearrangements in the stickleback genome and assess their potential involvement in the evolution of genomic islands. To identify rearrangements, we conducted a de novo assembly of the closely related tubesnout (Aulorhyncus flavidus) genome and compared this to the genomes of threespine stickleback and two other closely related species. We found that small rearrangements, within-chromosome duplications, and lineage-specific genes (LSGs) were enriched around genomic islands, and that all three chromosomes harboring large genomic islands have experienced macro-rearrangements. We also found that duplicates and micro-rearrangements are 9.9× and 2.9× more likely to involve genes differentially expressed between marine and freshwater genotypes. While not conclusive, these results are consistent with the explanation that strong divergent selection on candidate genes drove the recruitment of rearrangements to yield clusters of locally adaptive loci.
A randomized controlled trial of everolimus for neurocognitive symptoms in PTEN hamartoma tumor syndrome
Authors: Srivastava Siddharth , Jo Booil , Zhang Bo , Frazier Thomas , Gallagher Anne Snow , Peck Fleming , Levin April R , Mondal Sangeeta , Li Zetan , Filip-Dhima Rajna , Geisel Gregory , Dies Kira A , Diplock Amelia , Eng Charis , Hanna Rabi , Sahin Mustafa , Hardan Antonio ,   the Developmental Synaptopathies Consortium, Sahin Mustafa , Eng Charis , Hardan Antonio , Martinez-Agosto Julian A , Frazier Thomas
Published: May 2022

PTEN hamartoma tumor syndrome (PHTS) is a complex neurodevelopmental disorder characterized by mechanistic target of rapamycin (mTOR) overactivity. Limited data suggest that mTOR inhibitors may be therapeutic. No placebo-controlled studies have examined mTOR inhibition on cognition and behavior in humans with PHTS with/without autism. We conducted a 6-month phase II, randomized, double-blinded, placebo-controlled trial to examine the safety profile and efficacy of everolimus (4.5 mg/m2) in individuals (5–45 years) with PHTS. We measured several cognitive and behavioral outcomes, and electroencephalography (EEG) biomarkers. The primary endpoint was a neurocognitive composite derived from Stanford Binet-5 (SB-5) nonverbal working memory score, SB-5 verbal working memory, Conners’ Continuous Performance Test hit reaction time and Purdue Pegboard Test score. Forty-six participants underwent 1:1 randomization: n = 24 (everolimus) and n = 22 (placebo). Gastrointestinal adverse events were more common in the everolimus group (P < 0.001). Changes in the primary endpoint between groups from baseline to Month 6 were not apparent (Cohen’s d = −0.10, P = 0.518). However, several measures were associated with modest effect sizes (≥0.2) in the direction of improvement, including measures of nonverbal IQ, verbal learning, autism symptoms, motor skills, adaptive behavior and global improvement. There was a significant difference in EEG central alpha power (P = 0.049) and central beta power (P = 0.039) 6 months after everolimus treatment. Everolimus is well tolerated in PHTS; adverse events were similar to previous reports. The primary efficacy endpoint did not reveal improvement. Several secondary efficacy endpoints moved in the direction of improvement. EEG measurements indicate target engagement following 6 months of daily oral everolimus. Trial Registration Information: ClinicalTrials.gov NCT02991807 Classification of Evidence: I.
Genetic and pharmacological PARP inhibition reduces axonal degeneration in C. elegans models of ALS
Authors: Tossing Gilles , Livernoche Raphaël , Maios Claudia , Bretonneau Constantin , Labarre Audrey , Parker J Alex
Published: May 2022

Axonal degeneration is observed in early stages of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). This degeneration generally precedes apoptosis and therefore may be a promising therapeutic target. An increasing number of genes have been identified to actively regulate axonal degeneration and regeneration; however, only a few potential therapeutic targets have been identified in the context of neurodegenerative diseases. Here we investigate DLK-1, a major axonal regeneration pathway and its contribution to axonal degeneration phenotypes in several Caenorhabditis elegans ALS models. From this pathway, we identified the poly (ADP-ribose) (PAR) polymerases (PARP) PARP-1 and PARP-2 as the most consistent modifiers of axonal degeneration in our models of ALS. Genetic and pharmacological inhibition of PARP-1 and PARP-2 reduces axonal degeneration and improves related motor phenotypes.
Innovating in a crisis: a qualitative evaluation of a hospital and Google partnership to implement a COVID-19 inpatient video monitoring program
Authors: Gorbenko Ksenia , Mohammed Afrah , Ezenwafor Edward I I , Phlegar Sydney , Healy Patrick , Solly Tamara , Nembhard Ingrid , Xenophon Lucy , Smith Cardinale , Freeman Robert , Reich David , Mazumdar Madhu
Published: May 2022

Objective

To describe adaptations necessary for effective use of direct-to-consumer (DTC) cameras in an inpatient setting, from the perspective of health care workers.

Methods

Our qualitative study included semi-structured interviews and focus groups with clinicians, information technology (IT) personnel, and health system leaders affiliated with the Mount Sinai Health System. All participants either worked in a coronavirus disease 2019 (COVID-19) unit with DTC cameras or participated in the camera implementation. Three researchers coded the transcripts independently and met weekly to discuss and resolve discrepancies. Abiding by inductive thematic analysis, coders revised the codebook until they reached saturation. All transcripts were coded in Dedoose using the final codebook.

Results

Frontline clinical staff, IT personnel, and health system leaders (N = 39) participated in individual interviews and focus groups in November 2020–April 2021. Our analysis identified 5 areas for effective DTC camera use: technology, patient monitoring, workflows, interpersonal relationships, and infrastructure. Participants described adaptations created to optimize camera use and opportunities for improvement necessary for sustained use. Non-COVID-19 patients tended to decline participation.

Discussion

Deploying DTC cameras on inpatient units required adaptations in many routine processes. Addressing consent, 2-way communication issues, patient privacy, and messaging about video monitoring could help facilitate a nimble rollout. Implementation and dissemination of inpatient video monitoring using DTC cameras requires input from patients and frontline staff.

Conclusions

Given the resources and time it takes to implement a usable camera solution, other health systems might benefit from creating task forces to investigate their use before the next crisis.
Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods
Authors: Song Wenyu , Zhang Linying , Liu Luwei , Sainlaire Michael , Karvar Mehran , Kang Min-Jeoung , Pullman Avery , Lipsitz Stuart , Massaro Anthony , Patil Namrata , Jasuja Ravi , Dykes Patricia C
Published: May 2022

Objectives

The coronavirus disease 2019 (COVID-19) is a resource-intensive global pandemic. It is important for healthcare systems to identify high-risk COVID-19-positive patients who need timely health care. This study was conducted to predict the hospitalization of older adults who have tested positive for COVID-19.

Methods

We screened all patients with COVID test records from 11 Mass General Brigham hospitals to identify the study population. A total of 1495 patients with age 65 and above from the outpatient setting were included in the final cohort, among which 459 patients were hospitalized. We conducted a clinician-guided, 3-stage feature selection, and phenotyping process using iterative combinations of literature review, clinician expert opinion, and electronic healthcare record data exploration. A list of 44 features, including temporal features, was generated from this process and used for model training. Four machine learning prediction models were developed, including regularized logistic regression, support vector machine, random forest, and neural network.

Results

All 4 models achieved area under the receiver operating characteristic curve (AUC) greater than 0.80. Random forest achieved the best predictive performance (AUC = 0.83). Albumin, an index for nutritional status, was found to have the strongest association with hospitalization among COVID positive older adults.

Conclusions

In this study, we developed 4 machine learning models for predicting general hospitalization among COVID positive older adults. We identified important clinical factors associated with hospitalization and observed temporal patterns in our study cohort. Our modeling pipeline and algorithm could potentially be used to facilitate more accurate and efficient decision support for triaging COVID positive patients.
Generalizable prediction of COVID-19 mortality on worldwide patient data
Authors: Edelson Maxim , Kuo Tsung-Ting
Published: May 2022

Objective

Predicting Coronavirus disease 2019 (COVID-19) mortality for patients is critical for early-stage care and intervention. Existing studies mainly built models on datasets with limited geographical range or size. In this study, we developed COVID-19 mortality prediction models on worldwide, large-scale “sparse” data and on a “dense” subset of the data.

Materials and Methods

We evaluated 6 classifiers, including logistic regression (LR), support vector machine (SVM), random forest (RF), multilayer perceptron (MLP), AdaBoost (AB), and Naive Bayes (NB). We also conducted temporal analysis and calibrated our models using Isotonic Regression.

Results

The results showed that AB outperformed the other classifiers for the sparse dataset, while LR provided the highest-performing results for the dense dataset (with area under the receiver operating characteristic curve, or AUC ≈ 0.7 for the sparse dataset and AUC = 0.963 for the dense one). We also identified impactful features such as symptoms, countries, age, and the date of death/discharge. All our models are well-calibrated (P > .1).

Discussion

Our results highlight the tradeoff of using sparse training data to increase generalizability versus training on denser data, which produces higher discrimination results. We found that covariates such as patient information on symptoms, countries (where the case was reported), age, and the date of discharge from the hospital or death were the most important for mortality prediction.

Conclusion

This study is a stepping-stone towards improving healthcare quality during the COVID-19 era and potentially other pandemics. Our code is publicly available at: https://doi.org/10.5281/zenodo.6336231.
6 Jurisdiction, Effect of Approval, and Implementation
Authors: Henry Phillips
Published: May 2022

This chapter looks into the jurisdiction, effect of approval and implementation of CVAs. Proposals made in respect of and for a company and its creditors, and composition in satisfaction of the company's debts are the core elements of jurisdiction. Thus, the company's financial position stays highly relevant with the CVA jurisdiction even if it does not depend on the company's insolvency. Moreover, the binding effect of a CVA depends on the statutory hypothesis and creditors will be treated like they have given consent to the arrangement. The chapter expounds on the definition of composition, scheme of the arrangement, creditors, ancillary rights, and necessary compromises in line with CVAs.
Contract Law
Authors: Sester Peter
Published: May 2022

Brazilian contract law is part of the country’s Civil Code that was originally modelled on the German Civil Code of 1900. However, until 2002 the Brazilian Commercial Code of 1850 regulated commercial contracts separately and in a rather liberal way. That Code was revoked in 2002 and commercial contract law became subject to the general contract law as established in the revamped Civil Code of 2002. The new Civil Code emphasized general clauses such as good faith, financial-economic balance, the social functions of contracts, force majeure, excessively burdensome contracts (hardship), thereby fostering ‘corrective justice’ in contract law by facilitating court intervention. This approach is very problematic for businesses, for whom legal certainty is especially important for long-term planning and ‘big ticket’ deals. In 2019 the Law on Economic Freedom was adopted, which seeks to reemphasize party autonomy and pacta sunt servanda. It expressly limits court intervention, thereby facilitating risk allocation and tailor-made interpretation rules in contractual clauses. This chapter focuses on this controversial development and makes comparisons with German and English contract law, whenever appropriate.
Enterprise Law
Authors: Sester Peter
Published: May 2022

When the profoundly revamped Civil Code of 2002 came into force, the Commercial Code of 1850 was revoked and its provisions on partnership law were reformed and integrated into the new Code’s chapter on enterprise law. Thereby, the term ‘commercial’ disappeared from the Code(s). It was to some extent substituted by the expression ‘enterprise law’. However, the CC-2002 does not define an enterprise or business contract. It provides a definition for the terms ‘entrepreneur’ and ‘enterprise’. This makes sense because the Code’s chapter on enterprise law only addresses partnership and company law. Consequently, this chapter will focus on the characteristics of partnerships and limited liability companies. It will analyse these standard forms of business organizations and compare them with the stock corporation, which is regulated in a stand-alone act. Again, the aspect of risk allocation and the robustness of respective contractual clauses in potential conflicts will be a centre piece.