bluuebunny/crossref_metadata_2025_split huggingface dataset:
FGF/FGFR-related lncRNAs based classification predicts prognosis and guilds therapy in gastric cancer
Authors: Chen Qiuxiang , Du Xiaojing 
Published: April 2022

Abstract
Background: Precision classification greatly contributes to the individual treatment of gastric cancer (GC). Fibroblast growth factor (FGF)/receptor (FGFR) and long non-coding RNAs (lncRNAs) served as biomarkers for prognosis and treatment response. Hence, identifying FGF/FGFR-related lncRNAs is of importance to precision medicine in GC. Methods: STAD cohort from TCGA was used to identify FGF/FGFR-related lncRNAs. Cox analysis was employed to select lncRNAs with prognosis signature and establish risk score (RS) model. Than the molecular and tumor microenvironment characteristics of GC was estimated in RS groups. Finally, a comprehensive investigation was carried out to identify subclass-specific therapy.Results: We identified some FGF/FGFR-related lncRNAs and established a four-lncRNAs (FGF10-AS1, MIR2052HG, POU6F2-AS2 and DIRC1) RS model. Low RS group displayed high tumor mutation burden and infiltration of immune cells, as well as more sensitivity to immunotherapy or chemotherapy. High RS group showed high infiltration of stromal cells and more oncogenic signatures. In addition, two promising targeted drugs (Panobinostat and Tivantinib) was identified as specific agents for high RS group. Conclusions: Our study not only put forward a novel personalized prognostication classification model according to FGF/FGFR-related lncRNAs, but also provided new strategy for subclass-specific precision treatment in GC.
Anti-SARS-CoV-2 spike antibody titers and neutralizing antibodies in vaccinated rheumatoid arthritis patients.
Authors: Furukawa Hiroshi , Oka Shomi , Higuchi Takashi , Nakama Moriyuki , Nagai Nobuhiro , Tohma Shigeto 
Published: April 2022

Abstract
Objectives: Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A serological test is used to assess the efficacy of vaccination. It has been reported that anti-SARS-CoV-2 spike (S) and neutralizing antibody (Ab) levels are lower following vaccination in patients with rheumatic disease. Here, we investigated anti-SARS-CoV-2 S and neutralizing Abs in vaccinated rheumatoid arthritis (RA) patients in Japan. Methods: Anti-SARS-CoV-2 S and neutralizing Abs were quantified in 101 RA patients and 117 controls. Results: Anti-SARS-CoV-2 S Ab levels were lower in RA patients than both earlier after vaccination in controls (mean RA 324.1±591.8 SDM-vs.-control 1216.6±854.4 U/ml, P=8.02X10-16) and later after vaccination (324.1±591.8 -vs.582.0±415.6, P=0.0002). The interval between vaccination of the RA patients and serum collection was longer than for controls early after vaccination (142.1±31.6-vs.-98.3±11.2, P=6.54X10-32), but shorter than the later sample from the controls (142.1±31.6-vs.-257.3±11.2, P=1.79X10-94). Importantly, anti-SARS-CoV-2 neutralizing Ab titers in RA patients were higher than in either early or later control samples (10.7±4.9-vs.-8.6±6.6%, P=0.0072, and 10.7±4.9-vs.-3.1±3.7%, P=1.04X10-28, respectively). Conclusion: Anti-SARS-CoV-2 S Ab titers in vaccinated RA patients were lower than in controls, but anti-SARS-CoV-2 neutralizing Ab levels were higher.
Vaccine effectiveness of CoronaVac against symptomatic and severe COVID-19 among children in Brazil during the Omicron period
Authors: Florentino Pilar , Alves Flávia , Cerqueira-Silva Thiago , Oliveira Vinicius de Araujo , Júnior Juracy Bertoldo , Jantsch Adelson , Penna Gerson , Boaventura Viviane , Werneck Guilherme , Pearce Neil , Barral-Netto Manoel , Barreto Maurício , Paixao Enny 
Published: April 2022

Abstract
Compared to previous variants, the SARS-CoV-2 B.1.1.529 (Omicron) variant has relatively high infection rates, including among children. Even though severe COVID-19 in children is rare, this group is susceptible to the multisystem inflammatory syndrome in Children (MIS-C), long-COVID and downstream effects of COVID-19, including social isolation and education disruption. There is evidence that vaccination with an mRNA vaccine offers protection against infection and severe forms of COVID-19 for children. However, data on the effectiveness of inactivated virus vaccine, the most used platform worldwide, is scarce during the Omicron period. In Brazil, children between 6 to 11 years are eligible to receive the CoronaVac vaccine. Using a national linked database from January 21, 2022, up to April 19, 2022, during the Omicron dominant period in Brazil, we conducted a test-negative design with 194,258 tests to assess CoronaVac effectiveness against infection and severe (hospitalisation or death) outcomes among children aged 6 to 11 years. The estimated VE for symptomatic infection was 35.0% (95% CI 27.7–41.5) at 0–13 days and 41.5% (95% CI: 34.4–47.7) at ≥ 14 days post-second dose. For severe outcomes (hospitalisation or death) VE was 69.2% (95% CI: 11.7–93.6) at 0–13 days and 63.5% (95% CI: 5.8–90.0). Two doses of CoronaVac in children during the Omicron period showed low levels of protection against symptomatic infection, and modest levels against severe illness.
Predicting Age in Aedes aegypti (Diptera: Culicidae) Females to Monitor Changes in Transmission Potential
Authors: Gutiérrez Eileen H. Jeffrey , Riehle M. A. , Walker K. R. , Ernst K. C. , Davidowitz G. 
Published: April 2022

Abstract
Background: The Aedes aegypti mosquito is a vector of several viruses including dengue, chikungunya, zika, and yellow fever. Vector surveillance and control are the primary methods used for the control and prevention of disease transmission, however, these activities rely on measures of population abundance in surveillance programs as a trigger for initiating control activities. At the northern edge of Ae. aegypti’s geographic range, survival, rather than abundance, seems to be the factor limiting disease transmission. In this study, we sought to test the utility of using body size as an entomological index to surveil changes in the age structure of field collected, female Aedes aegypti. Methods: We collected female Ae. aegypti mosquitoes using BG sentinel traps in three cities at the northern edge of their geographic range. Collections took place during their active season over the course of three years. Female wing size was measured as an estimate of body size and reproductive status was characterized by examining ovary tracheation. Chronological age was determined by measuring transcript abundance of an age-dependent gene. These data were then tested with female abundance at each site and weather data from the estimated larval development period and adulthood (one week prior to capture). Two sources of weather data were tested to see which was more appropriate for evaluating impacts on mosquito physiology. All variables were then used to test models for predicting age via structural equation modeling. Results: In comparing city-specific NOAA weather data and site-specific data from HOBO remote temperature and humidity loggers, we found that HOBO data was more tightly associated with body size. We found that body size itself was not associated with age. Of all the variables measured, we found that temperature during development, body size, and relative humidity in the one week prior to capture produced the strongest model for predicting age. The strength of models improved drastically when testing one city at a time, with Hermosillo (the only study city with seasonal dengue transmission) having the strongest model for predicting age. Despite our finding that there was a bias in the body size of mosquitoes collected alive from the BG sentinel traps that favored large females, there was sufficient variation in body size to significantly improve the predictive capacity of our models. Conclusions: Body size nearly doubled the strength of weather-based models for predicting variation in age. Importantly, we found that variation in age was greater within cities than between cities, meaning that age predictions must be made on a city by city basis. These results contribute to efforts to use weather forecasts to predict changes in the probability of disease transmission by mosquito vectors.
Iron removal from groundwater using granular activated carbon filters by oxidation coupled with the adsorption process
Authors: Thinojah T. , Ketheesan B. 
Published: April 2022

Abstract
Granular activated carbon (GAC) is commonly used as an adsorbent for the removal of organic micropollutants. However, little is known about the inorganic pollutant removal using GAC. In this study, GAC was examined for the removal of iron from synthetic groundwater (SGW) using oxidation coupled with an adsorption mechanism. Batch experiments including kinetic and isotherm studies were carried out to find out the adsorption capacity of GAC. A column test was conducted at different phases to identify the influence of the initial concentration of iron, hydraulic retention time (HRT), and air supply to the system. It was observed that the experimental results for the kinetic experiment best fit the pseudo-first-order kinetics model with 88% maximum removal efficiency achieved in 240 min. A reduction in adsorption capacity was observed with the concomitant increase in the weight of GAC, whereas the maximum adsorption capacity of GAC was found to be 0.17mg Fe/g GAC. Column experiments confirmed that the effluent iron concentration reduced from 0.05 to 0.03mg/L when the iron concentration in the influent increased from 1 to 3mg/L. The reduction in HRT from 7 to 3.5h did not significantly affect the iron removal efficiency. The air supply to the system with the flow rate of 3.5L/min did not show any improvement in the iron removal efficiency due to the increased airflow rate. In all cases, the iron level in the effluent satisfied the drinking water quality standard recommended by the World Health Organization (WHO) which affirms that GAC filters are more suitable for iron removal from groundwater.
Monthly precipitation prediction using neural network algorithms in the Thua Thien Hue Province
Authors: Giang Nguyen Hong , Wang YuRen , Hieu Tran Dinh , Phuong Le Anh , Thinh Nguyen Tien 
Published: April 2022

Abstract
The prediction of precipitation is of importance in the Thua Thien Hue Province, which is affected by climate change. Therefore, this paper suggests two models, namely, the Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model and the Long Short-Term Memory (LSTM) model, to predict the precipitation in the province. The input data are collected for analysis at three meteorological stations for the period 1980–2018. The two models are compared in this study, and the results showed that the LSTM model was more accurate than the SARIMA model for Hue, Aluoi, and Namdong stations for forecasting precipitation. The best forecast model is for Hue station (= 0.94, = 0.94, = 8.15), the second-best forecast model is for Aluoi station ( = 0.89, = 0.89, = 12.72), and the lowest level forecast is for Namdong station ( = 0.89, = 0.89, = 12.81). The study result may also support stakeholderswho apply these models with future data to mitigate natural disasters in Thua Thien Hue.
Implication of bias correction on climate change impact projection of surface water resources in the Gidabo sub-basin, Southern Ethiopia
Authors: Worako Adimasu Woldesenbet , Haile Alemseged Tamiru , Taye Meron Teferi 
Published: April 2022

AbstractClimate change impact studies that evaluated the biases of climate models' simulations showed the presence of large systematic errors in their outputs. However, many studies continue to arbitrarily select bias correction methods for error reduction. This work evaluated the implications of bias correction methods on the projections of climate change impact on streamflow of the Gidabo sub-basin, Ethiopia. Climate outputs from four global climate model and regional climate model (GCM–RCM) combinations for the representative concentration pathway (RCP4.5) scenario were used. Five bias correction methods were used to reduce the systematic errors of the simulated rainfall data. The future changes in rainfall pattern, evapotranspiration, and streamflow were analyzed by using their relative percentage difference between the projected and the baseline period. The distribution mapping method provided better results in mean and extreme rainfall cases. This is also reflected in streamflow projections, as the daily interquartile range value indicates the lowest variability of the projected streamflow. The wet season streamflow will likely decrease in the future, whereas the short rainy season streamflow will increase. Our findings show that climate models and bias correction methods considerably limit the magnitude of future projections of streamflow. However, similar research should be conducted in other catchments to extend the conclusions of this study.
Assessment of the impacts of landscape patterns on water quality in Trondheim rivers and Fjord, Norway
Authors: Chang Tong , Nie Linmei , Killingtveit Ånund , Nøst Terje , Lu Jinmei 
Published: April 2022

Abstract
Due to the impacts of hydrological and ecological processes on water quality, discharges from upstream catchments have induced significant pollution to the recipients. This study aims to investigate the possible pollution sources from catchments with different types of land use and landscape patterns and develop the relationships between water quality and the catchment hydro-geological and environmental variables. Data from 10 monitoring sites in Trondheim formulated the basis of the case study. Thermotolerant coliform bacteria (TCB) and total phosphorus (TP) were applied as main indicators to represent the water quality in the recipient rivers, streams and in Trondheim Fjord. Based on the GIS-oriented spatial analysis, 15 hydro-geographical and landscape parameters were selected as explanatory variables. Multiple linear regression (MLR) models were developed at catchment and river reach scales to study correlations between the explanatory variables and the response variables, TCB and TP, in rain and snow seasons. The study showed that the spatial landscape patterns resulted in differences in the concentrations of TCB and TP in the recipients. The agricultural land was shown to be the main pollution source, leading to a higher concentration of TP in streams. Buildings, roads, and other impervious areas have induced an increase in both TCB and TP. In contrast, the forest areas, lakes, river density and steep river slopes were shown to have capacity to filter incoming P-rich runoff, thus prevent pollutant conveyance and accumulation in recipients.
Nucleic Acid-conjugated Carbohydrate Nanobiosensors: A Multimodal Tool for
Disease Diagnosis
Authors: Kantak Maithili , Shende Pravin 
Published: April 2022

Background:
Nucleic acid-based carbohydrate sensors (NAbCSs) constitute a strategy involving
nucleic acids as recognition elements for the development of a unique, stable, sensitive, mono- or multimodal
detection system in the field of nanomedicine, gas sensing, and gene therapy. Thus, this advanced platform for
next-generation investigation compromises cost-effective, wearable, and noninvasive sensing devices as diagnostics
in healthcare.

Objectives:
This review article highlights the importance of NAbCSs and explores the novel applications of sensors
fabricated via the conjugation of nucleic acids and carbohydrates. Additionally, advances in smart portable
devices, like smartphones, printers, and digital multimeters, are summarized, followed by the challenges involved
in the development of futuristic sensing tools.

Method:
A novel platform has been unfolded for the detection of different chemical toxins (like aflatoxin B1,
ochratoxin A) and biomarkers (like miRNA in cancer) present in biosamples, food and biowarfare agents. The
potential applications of biosensing in the areas of miniaturization, reusability, rapid, point-of-care or portable
for home analysis techniques, cost-effective, eco-friendly, high throughput and personalized sensors for qualitative
analysis of target analyte/s in bio-fluids and food have been explored.

Conclusion:
NAbCSs provide real-time monitoring of biosamples qualitatively and semi-quantitatively (luminometer,
fluorimeter, etc.) in the absence of trained personnel. Explorations of NAbCSs encompass advantages
in remote resource-limited access areas with simultaneous monitoring via smart devices for multiple analytes
with greater precision, sensitivity, and selectivity.
A Review of the Applicability of Classical and Extension of Fuzzy Logic
Approaches to Project Decision-Making using Real Options
Authors: Kouatli Issam , Ben Abdallah Skander , Terhini Abbas , Naccash Hiba 
Published: April 2022

Introduction:
In this study, a review of fuzzy implementation to Real Options Approach
(ROA) theory where the applicability of classical and extended theories of “fuzziness” studied.

Background:
ROA allows taking into account the value of some sources of managerial flexibility and
therefore assessing a more accurately project value. The positive value of flexibility results from limiting
the impacts of adverse events while taking advantage of positive ones. One of the main lessons is
that uncertainty adds value in the presence of flexibility. Ambiguous parameters that have a significant
effect on the project value are usually represented as fuzzy sets using Zadeh's classical theory of
Fuzzy logic (also termed "type-1"). However, there have been so many derivatives, and expansions of
the fuzzy set theories developed by different researchers. Dealing with uncertainty can be manifested
in the different mechanism of fuzziness.

Objective:
The objective of this review is to identify the research gap as well as provide an elementary
guide to the applicability of different varieties of classical and extended applicability of fuzziness to
ROA when evaluating project investment.

Methods:
After a generic review of the progress of ROA theory and fuzzy approaches by researchers
This paper reviews the applicability of ROA to fuzzy sets (classical and extended) implementation to
decision-making for large projects where project timing and uncertainty are key parameters affecting
the project value

Results:
After reviewing the applicability of each of the classical and extended theories of fuzzy logic
to ROA, a tabular format shows the result of this study summarizing the scenario, showing the applicability
of different techniques.

Conclusion:
Most of the reviewed techniques of fuzzy implementation to ROA approach, still based
on the classical theory of fuzzy logic. Implementation of more extended techniques has a potential of
enhancing the outcome of such research.
Virtual Specialist Care During the COVID-19 Pandemic: Multimethod Patient Experience Study
Authors: Dainty Katie N , Seaton M Bianca , Estacio Antonio , Hicks Lisa K , Jamieson Trevor , Ward Sarah , Yu Catherine H , Mosko Jeffrey D , Kassardjian Charles D 
Published: April 2022

Background
Transitioning nonemergency, ambulatory medical care to virtual visits in light of the COVID-19 global pandemic has been a massive shift in philosophy and practice that naturally came with a steep learning curve for patients, physicians, and clinic administrators.

Objective
We undertook a multimethod study to understand the key factors associated with successful and less successful experiences of virtual specialist care, particularly as they relate to the patient experience of care.

Methods
This study was designed as a multimethod patient experience study using survey methods, descriptive qualitative interview methodology, and administrative virtual care data collected by the hospital decision support team. Six specialty departments participated in the study (endoscopy, orthopedics, neurology, hematology, rheumatology, and gastroenterology). All patients who could speak and read English and attended a virtual specialist appointment in a participating clinic at St. Michael’s Hospital (Toronto, Ontario, Canada) between October 1, 2020, and January 30, 2021, were eligible to participate.

Results
During the study period, 51,702 virtual specialist visits were conducted in the departments that participated in the study. Of those, 96% were conducted by telephone and 4% by video. In both the survey and interview data, there was an overall consensus that virtual care is a satisfying alternative to in-person care, with benefits such as reduced travel, cost, time, and SARS-CoV-2 exposure, and increased convenience. Our analysis further revealed that the specific reason for the visit and the nature and status of the medical condition are important considerations in terms of guidance on where virtual care is most effective. Technology issues were not reported as a major challenge in our data, given that the majority of “virtual” visits reported by our participants were conducted by telephone, which is an important distinction. Despite the positive value of virtual care discussed by the majority of interview participants, 50% of the survey respondents still indicated they would prefer to see their physician in person.

Conclusions
Patient experience data collected in this study indicate a high level of satisfaction with virtual specialty care, but also signal that there are nuances to be considered to ensure it is an appropriate and sustainable part of the standard of care.