bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trend of pediatric trauma during a six-year period in a Level-1 Trauma Center in Northern Italy: epidemiological analysis of trauma mechanisms and the effects of Covid-19 Pandemic
Authors: Maina Cecilia , Cioffi Stefano Piero Bernardo , Altomare Michele , Spota Andrea , Virdis Francesco , Bini Roberto , Ragozzino Roberta , Renzi Federica , Reitano Elisa , Corasaniti Lucia , Macchini Francesco , Chiara Osvaldo , Cimbanassi Stefania 
Published: September 2022

Abstract
Background: Trauma is the leading cause of morbidity and mortality in the pediatric population. During the Covid-19 pandemic (C-19), different trends for Pediatric Trauma (PT) were described. This study aims to explore the trend over time of PT in our center, also considering the effects of C-19, focusing on trauma mechanisms, violence-related trauma (VRT) and intentionality, especially suicide attempts (SA).Methods: All PT patients accepted at Niguarda Trauma Center (NTC) in Milan from January 2015 to December 2020 were retrospectively analyzed. We considered demographics and clinical variables and performed descriptive and year comparison analyzes. Results: 684 PT were accepted at NTC: 84 in 2015, 98 in 2016, 125 in 2017, 119 in 2018, 114 in 2019 and 144 in 2020 (p<0.001); 66.2% male, mean age 9.88 (± 5.17). We observed a higher number of traffic-related, fall-related injuries and an increasing trend for VRT and SA, peaking in 2020. We report an increasing trend over time for head trauma (p=0.002). The Injury Severity Score did not significantly change. During C-19 we recorded a higher number of self-presenting patients with low priority codes.Conclusions: NTC is the adult level I referral trauma center for the Milan urban area, with pediatric commitment. During C-19, every traumatic emergency was centralized to NCT. In 2020 we observed an increasing trend of SA and VRT among PTs. The psychological impact of the C-19 restriction could explain this evidence. The long-term effects of C-19 on the mental health of the pediatric population should not be underestimated. Focused interventions on psychological support and prevention of SA and VRT should be implemented, especially during socio-demographic storms like the last pandemic.
Mitigate Gender Bias using Negative Multi-Task Learning
Authors: Gao Liyuan , Zhan Huixin , Chen Austin , Sheng Victor 
Published: September 2022

Abstract
Deep learning models have shown their great performances in natural language processing tasks. While much attention has been paid towards improvements in utility, privacy leakage and social bias are two major concerns arising in trained models. In this paper, we protect individual privacy and mitigate gender bias on classification models simultaneously. First, we propose a selective privacy-preserving method that only obscure individuals' sensitive information by adding noise on word embeddings. Then we propose a negative multi-task learning framework to mitigate the gender bias which contains a main task and a gender prediction task. The main task uses a positive loss constraint to ensure utility while the gender prediction task applies a negative loss constraint to remove gender-specific features. We analyze two existing word embeddings and evaluate them on sentiment analysis and medical text classification tasks. Our experimental results show that our negative multi-task learning framework can mitigate the gender bias while keeping models’ utility on both sentiment analysis and medical text classification.
OLCE: Optimized Learning-based Cost Estimation for Global Software Projects
Authors: Rao K Nitalaksheswara , Bolla Jhansi Vazram , Mummana Satyanarayana , Krishna CH. V. Murali , Gandhi O. , Stephen M James 
Published: September 2022

Abstract
Software Cost Estimation (SCE) is an integral part of pre-development stage of software project with a target to accomplish a better visibility towards possible risk while gaining more information towards reaching success rate to meet the deadline of delivery. Irrespective of multiple research contribution model towards SCE, the problem and challenges towards accurate cost estimation in presence of dynamicity and uncertainty is yet not reported to be accomplished. Apart from this, learning-based models are slowly gaining pace in almost every field and yet it is still in nascent stage of progress in software engineering. Therefore, the proposed manuscript introduces Optimized Learning-based Cost Estimation (OLCE) which is a novel learning-based model capable of accurate prediction considering global and large scale software project. The proposed system harnesses the learning potential from artificial neural network integrated with novel search-based approach for optimizing the learning method considering the benchmarked COCOMO NASA 2 dataset. The study outcome shows OLCE offers 50% faster response time with approximately 73% of accuracy compared to existing models that are reportedly found to be adopted for SCE. Hence, OLCE is found to offer a balance between accuracy and computational efficiency during SCE.
ABILITY OR LUCK: A Systematic Review of Interpersonal Attributions of Success
Authors: Hamilton Odessa S. , Lordan Grace 
Published: September 2022

Abstract
The role of luck in success has a relatively minor, albeit consistent history in academic discourse, with a striking lack of literature engaging in notions of luck within occupational environments. Elucidating why people attribute their own success to luck over ability has predominated in the literature, with interpersonal attributions receiving less attention. Here we center on systematically summarizing evidence on interpersonal attributions of success as a function of ability or luck, and whether this differs by gender and race. The perception of the success of others and how it is attributed is a crucial leverage point for inclusion and diversity. Ignoring the role of luck conceals and augments privilege, even if not deliberately or consciously invoked. Using the Prisma protocol, this review offers evidence from experiments, published between 1970 and 2020, derived from five electronic bibliographic databases. There were a limited number of studies on gender that found an effect, but with few exceptions, the papers that pertain to race converged on the understanding that interpersonal attributions of success were predicated on this immutable factor. Such that black individuals were more often viewed as lucky in their success and less able, which translates to lesser opportunity and reward. While decades of research point to individuals making systematic attribution errors in success, this review only partially substantiates this consensus and provides narrow support for the view that those believed to be the most talented in society may merely be the luckiest. We add to evidence that context matters.
Bioaccumulation and Biota-Sediment Accumulation Factor of metals and metalloids in edible fish: A systematic review and meta-analysis in Ethiopian surface waters.
Authors: Sintie Tamagnu , Abebe Bealemlay 
Published: September 2022

Abstract

Bioaccumulation and Biota-Sediment Accumulation Factor are used to quantify the bioaccumulation of contaminants from water and sediment to biota due to uptake through all possible routes of exposure. The present study aimed to determine the BAF and BSAF of metals and metalloids in different surface waters of Ethiopia. Furthermore, the ecological and human health risks were also examined. Generally, 902 peer-reviewed papers from 2005 to 2022 were searched using search engines. The most common types of edible fish species in studied surface waters of Ethiopia were Nile tilapia (Oreochromis niloticus), African sharp tooth catfish (Clarias gariepinus) and African big barb (Barbus intermedius). A higher concentration of dissolved metals and metalloids were detected in the dry than rainy season. The concentration of metals and metalloids in sediment were higher than in water. The concentration of metals and metalloids in carnivorous fish were relatively higher than in herbivorous fish. The BSAF of Se in all fish species was greater than 1. Oreochromis niloticus was a bio-concentrator of AS and Se. The concentration of Cu, Cd, Pb, and Ni in water environmental threshold values given by EEPA and OECD, and in sediment Cu, Pb, Ni, Zn and Cr were above TEC values and Cd, Ni and Cr were above PEC levels when compared to the United States Consensus-Based Sediment Quality Guidelines for freshwater which indicates that these metals may pose risk to aquatic organisms. Consumption of raw water, except contaminated with Cd, Pb, and Ni and fish muscle, except contaminated with Cd, As, and Cr may not pose risk to consumers. However, local consumers who live close to each freshwater ecosystem may become more exposed to health risk hazards. The findings of this study will provide baseline information on BAF and BSAF of metals and metalloids in surface waters and will contribute to the effective monitoring of environmental quality.
Determination of the UGT1A1 polymorphism as guidance for irinotecan dose adjustment in gastric cancer treated with second-line chemotherapy
Authors: Lv Huifang , Nie Caiyun , He Yunduan , Chen Beibei , Liu Yingjun , Wang Jianzheng , Xu Weifeng , Zhao Jing , Zhang Junling , Wang Saiqi , Chen Xiaobing 
Published: September 2022

Abstract
Purpose
Uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) is a key enzyme in irinotecan metabolism. However, the relationship between UGT1A1 genotype and the safety and efficacy of irinotecan monotherapy in the treatment of Chinese advanced gastric cancer remains unclear.
Methods
A total of 110 patients were enrolled in this study. Intravenous irinotecan was administered every 3 weeks. Irinotecan dose was selected according to the polymorphism of UGT1A1*6 gene, which was divided into 3 groups: UGT1A1*6 wild-type (GG type): 125mg/m2, d1, d8; UGT1A1*6 mutant heterozygosity (GA type) 100mg/m2, d1, d8; UGT1A1*6 homozygosity mutation (AA type) 75mg/m2, d1, d8 or paclitaxel 125mg/m2, d1, d8.
Results
Among these 110 patients, the genotypes of UGT1A1*28 were wild-type in 78 patients (70.9%), mutant heterozygosity in 28 (25.5%) and mutant homozygosity in 4 (3.6%). UGT1A1*6 were GG in 67 cases (60.9%), GA in 35 cases (31.8%), and AA in 8 cases (7.3%). There was no significant difference in the risk of delayed diarrhea and granulocytopenia in patients with different UGT1A1*28 genotypes (P > 0.05), while there was significant difference in the risk of delayed diarrhea and granulocytopenia in patients with different UGT1A1*6 genotypes (P < 0.05). The dose intensity of irinotecan was different in patients with different subtypes of UGT1A1*6 gene. However, there were no significant differences in PFS and OS among patients with different subtypes after dose adjustment and program adjustment (P > 0.05).
Conclusion
Individualized treatment under the guidance of UGT1A1*6 gene polymorphism can ensure the efficacy and reduce the incidence of adverse reactions of gastric cancer patients.
Numerical prediction of transient electrohydrodynamic instabilities under an alternating current electric field and unipolar injection
Authors: Zhou Chu-Tong , Yao Zhen-Ze , Chen Di-Lin , Luo Kang , Wu Jian , Yi Hong-Liang 
Published: September 2022

Abstract

This paper presents a two-dimensional direct numerical simulation (DNS) of dielectric fluid flow subjected to unipolar injection under an alternating current (AC) electric field. The effect of frequency f of pulsed direct current (PDC) and AC on the transient evolution of electroconvection and their subcritical bifurcations are investigated for the first time. Electroconvection under PDC or AC tends to exhibit oscillating flow due to the periodic boundary condition of electric potential and charge density compared with the direct current (DC) case. The results demonstrate that the linear stability criterion Tc decreases as the frequency increases under a PDC field, while the nonlinear stability criterion Tf is hardly affected. Under the AC field, a critical frequency fc = 0.0316 is found, which separates electroconvection into two typical flow regimes—periodic flow regime (f < fc) and inhibited flow regime (f ≥ fc)—depending on whether free charges can reach the collector electrode before electric field inversion. These mechanisms of electroconvection under PDC/AC field offer possibilities in the field of flow control.
Comparative study on stream flow prediction using the GMNN and wavelet-based GMNN
Authors: Agarwal Shivam , Roy Parthajit , Choudhury Parthasarathi , Debbarma Nilotpal 
Published: September 2022

Abstract
Flood flow forecasting is essential for mitigating damage in flood-prone areas all over the world. Advanced actions and methodology to optimize peak flow criteria can be adopted based on forecasted discharge information. This paper applied the models of the integrated wavelet, multilayer perceptron (MLP), time-delay neural network (TDNN), and gamma memory neural network (GMNN) to predict hourly river-level fluctuations, including storage rate change variable. Accordingly, the researchers initially used the discrete wavelet transform to decompose the water discharge time-series into low- and high-frequency components. After that, each component was separately predicted by using the MLP, TDNN, and GMNN models. The performance of the proposed models, namely wavelet–MLP, wavelet–TDNN, and wavelet–GMNN, was compared with that of single MLP, TDNN, and GMNN models. This analysis affirms that precision is better in the case of integrated models for forecasting river reach levels in the study region. Furthermore, multiple inputs–multiple outputs (MIMO) networks (MIMO-1 artificial neural network (ANN) and MIMO-2 ANN), along with multiple inputs–single output (MISO) ANN were employed for obtaining flow forecasts for several sections in a river basin. Model performances were also evaluated using the root mean squared error having less than 10% of the average mean value, with the coefficient of correlation being more than 0.91 and with the peak flow criteria showing the chances of flash floods being low to moderate with values not more than 0.15.
Exploring Anti-osteoporosis Medicinal Herbs using Cheminformatics and
Deep Learning Approaches
Authors: Lin Ziying , Wang Shengjun , Liu Zhihong , Liu Bingdong , Xie Liwei , Zhou Jingwei 
Published: September 2022

Background:
Osteoporosis is a prevalent disease for the aged population. Chinese herb-derived natural compounds have anti-osteoporosis effects. Due to the complexity of chemical ingredients and natural products, it is necessary to develop a high-throughput approach with the integration of cheminformatics and deep-learning methods to explore their mechanistic action, especially herb/drug-gene interaction networks.

Methods:
Ten medicinal herbs for clinical osteoporosis treatment were selected. Chemical ingredients of top 10 herbs were retrieved from TCMIO database, and their predicted targets were obtained from SEA server. Anti-osteoporosis clinical drugs and targets were collected from multi-databases. Chemical space, fingerprint similarity, and scaffold comparison of the compounds between herbs and clinical drugs were analyzed by RDKit and SKlearn. A network of herb-ingredient-target were constructed via Gephi, and GO and KEGG enrichment analysis were performed using clusterProfiler. Additionally, the bioactivity of compounds and targets were predicted by DeepScreening. Molecular docking of YYH flavonoids to HSD17B2 was accomplished by AutoDockTools.

Results:
Cheminformatics result depicts a pharmacological network consisting of 89 active components and 30 potential genes. The chemical structures of plant steroids, flavonoids, and alkaloids are key components for anti-osteoporosis effects. Moreover, bioinformatics result demonstrates that the active components of herbs mainly participate in steroid hormone biosynthesis and the TNF signaling pathway. Finally, deep-learning-based regression models were constructed to evaluate 22 anti-osteoporosis-related protein targets and predict the activity of 1350 chemical ingredients of the 10 herbs.

Conclusion:
The combination of cheminformatics and deep-learning approaches sheds light on the exploration of medicinal herbs mechanisms, and the identification of novel and active compounds from medical herbs in complex molecular systems.
Effective Cancer Management: Inimitable Role of Phytochemical Based Nano-
Formulations
Authors: Upaganlawar Aman , Polshettiwar Satish , Raut Sushil , Tagalpallewar Amol , Pande Vishal 
Published: September 2022

Background:
Global cancer statistics defines the severity of disease even after significant research
worldwide.

Problem:
Failure of the currently available treatment approaches, including surgery, radiation therapy and traditional
chemotherapy.

Aim:
The aim of this review is to discuss the role of phytochemical based nano-formulations for treatment of cancer.

Discussion:
In the past few decades, phytochemicals have gained popularity for acting as a potential anticancer treatment
with low systemic toxicity, especially in terms of cell cycle control and cancer cell killing. Natural resources, with
their immense structural variety, serve as a vital source of fresh, therapeutically useful new chemical entities for the
treatment of cancer. Vinca alkaloids (VCR), vinblastine, vindesine, vinorelbine, taxanes (PTX), podophyllotoxin and its
derivatives (etoposide (ETP), teniposide, camptothecin (CPT) and its derivatives (topotecan, irinotecan), anthracyclines
(doxorubicin, daunorubicin, epirubicin, idarubicin, as natural products or their derivatives account for half of all anticancer
drugs approved worldwide, and they have been developed utilising the knowledge learned from the natural small
molecules or macromolecules. Trabectedin, an epothilone derivative, ixabepilone, and temsirolimus, three new anticancer
medications launched in 2007, were derived from microbial origins. Current therapy regimens require selective
drug targeting to enhance efficacy against cancer cells while normal cells remain unharmed. Modified medications and
systems for drug delivery based on nanotechnology are in the process of being explored and launched in the industry for
enhanced therapy and management of cancer, along with promising outcomes. Many obstacles related to cancer cell
drug delivery can be overcome by using nano-particulate drug carriers, including enhancing the stability and solubility of
the drug, prolonging half-lives of the drug in the blood, decreasing side effects to undesired organs, and increasing medication
concentration at the desired site. The scientific initiatives and studies concerning the use of nanotechnology for
some selective compounds derived from plants are discussed in this review article.

Conclusion:
The present review highlights the phytochemical-based nanoformulations and their strategies in the
development of novel systems of drug delivery such as nano-liposomes, functionalized nanoparticles (NPs), and
polymer nano-conjugates, SNEDDS (Self nano emulsifying drug delivery system) as this review paper depicts, as
well as their rewards over conventional systems of drug delivery, as evidenced by improved biological activity depicted
in their in vitro and in vivo anticancer assays.
Predictors of Healthcare Utilization Among Older Adults with Moderate
to Severe Cognitive Limitations in Ghana: A Cross-Sectional Analysis of
the WHO Study on Global Ageing and Adult Health (SAGE) Wave 1
Authors: Dai Baozhen , Larnyo Ebenezer , Larnyo Abigail , Nutakor Jonathan Aseye , Amerley Amarteifio Edwina Naa , Frimpong Yaw , Addai-Dansoh Stephen 
Published: September 2022

Background:
As the number of older adults in Ghana keeps increasing, so does the prevalence
of aging-related diseases and conditions that tend to lead to cognitive decline. However,
knowledge on the predicting factors of healthcare utilization among older adults with cognitive limitations
is still scarce.

Objective:
This study examines the predictive factors of healthcare-seeking behavior among older
adults with moderate-to-severe cognitive limitations in Ghana.

Methods:
Based on Andersen's behavioral model of health service utilization, the study analyzed data
from 3106 older adults with moderate to severe cognitive limitations in Ghana aged 50+ using Bivariate
Probit Regression and the Heckman Selection Model.

Results:
Results showed that individuals who were aged 75+, living in urban settlements, educated,
higher income levels and parents who had some level of education, pension benefits, and both mandatory
and voluntary health insurance were more likely to seek inpatient care.
Enabling resources such as the national health insurance scheme and other types of medical insurance,
household income, pension benefits, and predisposition factors like education influenced outpatient
and inpatient healthcare consumption for older adults with moderate to severe cognitive limitations
but had little influence on the choice of healthcare facility except for health insurance.

Conclusion:
Since the healthcare-seeking behavior of older adults with moderate-to-severe cognitive
limitations is driven by an amalgamation of several internal and external factors, there is a need for
policy change to understand and cautiously incorporate these factors into the decision to improve equitable
access to healthcare services for these individuals, as not all sizes fit all in providing quality
care for them.
Gliotoxin Induced Ferroptosis by Downregulating SUV39H1 Expression in
Esophageal Cancer Cells
Authors: Zhang Shengqiang , Guo Jida , Zhang Hongyan , Tong Lu , Zhang Linyou 
Published: September 2022

Background:
Gliotoxin, a secondary metabolite isolated from marine-derived Aspergillus
fumigatus, has demonstrated anti-tumor properties in several cancers. Ferroptosis, a recently
discovered type of programmed cell death that depends on the accumulation of iron and lipid peroxides,
participates in the occurrence and development of various diseases, including cancer. A
recent patent, US20200383943, has suggested that the promotion of ferroptosis is a method of
cancer treatment. Therefore, the development of drugs that induce ferroptosis in cancer cells
would constitute a novel therapeutic approach.

Objective:
Gliotoxin is a natural compound which has exhibited anti-tumor properties in multiple
cancers, however, studies of the effect of gliotoxin on esophageal cancer are lacking. Although
cancer treatment has shown great progress, including traditional surgery, chemotherapy, radiotherapy,
and immunotherapy, the prognosis of esophageal cancer is still poor. Therefore, the development
of new treatment approaches for esophageal cancer is necessary.

Methods:
The effects of gliotoxin on esophageal cancer cells were determined by functional assays,
such as CCK-8, wound healing and transwell assays. We used online tools to predict the target
genes of gliotoxin, followed by further verification using Western blotting assays. To assess
the role of gliotxin in inducing ferroptosis in esophageal cancer, we detected characteristics associated
with ferroptosis including ROS, MDA, GSH and Fe2+.

Results:
Using online tools SEA and SwissTargetPrediction, we predicted that SUV39H1 was the
gliotoxin target gene. Furthermore, in esophageal cancer tissues, SUV39H1 was expressed at
higher levels than in normal tissues, while in patients with Esophageal Squamous Cell Carcinoma
(ESCC), high expression levels of SUV39H1 indicated a poor prognosis. In vitro, we observed
that gliotoxin increased ESCC cell death and inhibited cell migration. We treated ESCC cells with
pan-caspase inhibitor Z-VAD-FMK or ferroptosis inhibitors, including Fer-1 and DFO. Our results
showed that Fer-1 and DFO reduced the toxic effects of gliotoxin, while Z-VAD-FMK did
not. Furthermore, gliotoxin treatment reduced tumor weight and volume in the xenograft tumor
mouse model.

Conclusion:
In summary, our findings indicate that gliotoxin downregulated SUV39H1 expression
in ESCC cells and induced ferroptosis, suggesting a novel natural therapy for ESSC.