bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors of initial inappropriate antibiotic therapy and the impacts on outcomes of neonates with gram-negative bacteremia
Authors: Chu Shih-Ming , Hsu Jen-Fu , Lai Mei-Yin , Huang Hsuan-Rong , Chiang Ming-Chou , Fu Ren-Huei , Tsai Ming-Horng 
Published: December 2019

Abstract

Background Timely appropriate empirical antibiotic plays an important role in critically ill patients with gram-negative bacteremia. However, the relevant data and significant impacts have not been well studied in the neonatal intensive care unit (NICU). Methods An 8-year (1 January 2007-31 December 2014) cohort study of all NICU patients with gram-negative bacteremia in a tertiary-care medical center was performed. Inadequate empirical antibiotic therapy was defined when a patient didn’t receive any antimicrobial agent to which the causative microorganisms were susceptible within 24 hour of blood culture sampling. Results Among 376 episodes of Gram-negative bacteremia, 75 (19.9%) received inadequate empirical antibiotic therapy. The cause of inadequate treatment was mostly due to the pathogen resistant to prescribed antibiotics (88.0%), and Pseudomonas aeruginosa (Odds ratio [OR]: 20.8, P < 0.001) and ESBL-producing bacteria (OR: 18.4, P < 0.001) had the highest risk. Previous exposure with 3rd generation cephalosporin was identified as the only independent risk factor (OR: 2.52, 95% CI: 1.18-5.37, P = 0.018). Empirically inadequately treated bacteremias were significantly more likely to have worse outcomes than those with adequate therapy, including more prolonged illness, higher rate of infectious complications (25.3% versus 9.3%, P < 0.001) and overall mortality (22.7% versus 11.0%, P = 0.013). Conclusions Inadequate empirical antibiotic therapy occurs in one-fifth of Gram-negative bacteremias in the NICU, and is associated with worse outcomes. Further effort to decrease emergence of antibiotic resistance and highly suspicion of infection by drug-resistant bacteria clinically is important to reduce rates of inadequacy.
IMMUNOPROTECTIVE EFFECT OF MELATONIN ADMINISTRATION ON METHYLPREDNISOLONE-TREATED WISTAR MALE RAT (RATTUS NORVEGICUS)
Authors: Manus Widya Christine , Pangkahila Wimpie , Aman I Gusti Made 
Published: December 2019

Background: Immune system function decreases with age. Steroid use might accelerate this process, especially in adults in Indonesia. Melatonin is a natural hormone which show antioxidant effect and immunoprotective effect. Melatonin administration might help in reviving humane immune system due to aging and exogenous steroid exposure.
Objective: This experiment is aimed to determine the effect of melatonin on leukocyte and lymphocyte count of methylprednisolone-induced immunosuppression on Wistar rat.
Method: This study was true experimental with post-test only control group design using 32 male rats. Rats were divided into control and the intervention group. Control group was given methylprednisolone 0.144 mg/200 g rat 3 times a day and distilled water. The treatment group was given methylprednisolone 0.144/200 g rat 3 times a day and 0.054 mg/200 g melatonin once daily. The blood was taken after 14 days of treatment.
Results: Intervention group shows higher lymphocytes count (4.95 Â±1.58x103/ï­L) compared to the control group (3.09ï­1.33x103/ï­L), with p < 0.01. The intervention group also has higher leukocyte count (8.37Â± 2.02x103/ï­L) compared to the control group (6.70 Â± 1.96x103/ï­L), with p
Selecting rep-PCR markers to source track fecal contamination in Laguna Lake, Philippines
Authors: Labrador Kevin L. , Nacario Mae Ashley G. , Malajacan Gicelle T. , Abello Joseth Jermaine M. , Galarion Luiza H. , Rensing Christopher , Rivera Windell L. 
Published: December 2019

Abstract
Fecal contamination is one of the factors causing deterioration of Laguna Lake. Although total coliform levels are constantly monitored, no protocol is in place to identify their origin. This can be addressed using the library-dependent microbial source tracking (MST) method, repetitive element sequence-based polymerase chain reaction (rep-PCR) fingerprinting. Serving as a prerequisite in developing the host-origin library, we assessed the discriminatory power of three fingerprinting primers, namely BOX-A1R, (GTG)5, and REP1R-1/2-1. Fingerprint profiles were obtained from 290 thermotolerant Escherichia coli isolated from sewage waters and fecal samples of cows, chickens, and pigs from regions surrounding the lake. Band patterns were converted into binary profiles and were classified using the discriminant analysis of principal components. Results show that: (1) REP1R-1/2-1 has a low genotyping success rate and information content; (2) increasing the library size led to more precise estimates of library accuracy; and (3) combining fingerprint profiles from BOX-A1R and (GTG)5 revealed the best discrimination (average rate of correct classification (ARCC) = 0.82 ± 0.06) in a two-way categorical split; while (4) no significant difference was found between the combined profiles (0.74 ± 0.15) and using solely BOX-A1R (0.76 ± 0.09) in a four-way split. Testing the library by identifying known isolates from a separate dataset has shown that a two-way classification performed better (ARCC = 0.66) than a four-way split (ARCC = 0.29). The library can be developed further by adding more representative isolates per host source. Nevertheless, our results have shown that combining profiles from BOX-A1R and (GTG)5 is recommended in developing the MST library for Laguna Lake.
Monthly pan evaporation modelling using multiple linear regression and artificial neural network techniques
Authors: Patle G. T. , Chettri M. , Jhajharia D. 
Published: December 2019

AbstractAccurate estimation of evaporation from agricultural fields and water bodies is needed for the efficient utilisation and management of water resources at the watershed and regional scale. In this study, multiple linear regression (MLR) and artificial neural network (ANN) techniques are used for the estimation of monthly pan evaporation. The modelling approach includes the various combination of six measured climate parameters consisting of maximum and minimum air temperature, maximum and minimum relative humidity, sunshine hours and wind speed of two stations, namely Gangtok in Sikkim and Imphal in the Manipur states of the northeast hill region of India. Average monthly evaporation varies from 0.62 to 2.68 mm/day for Gangtok, whereas it varies from 1.4 to 4.3 mm/day for Imphal during January and June, respectively. Performance of the developed MLR and ANN models was compared using statistical indices such as coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE) with measured pan evaporation values. Correlation analysis revealed that temperature, wind speed and sunshine hour had positive correlation, whereas relative humidity had a negative correlation with pan evaporation. Results showed a slightly better performance of the ANN models over the MLR models for the prediction of monthly pan evaporation in the study area.
On the use of ARIMA models for short-term water tank levels forecasting
Authors: Viccione G. , Guarnaccia C. , Mancini S. , Quartieri J. 
Published: December 2019

Abstract
In this paper a statistical study on the time series of water levels measured, during 2014, in the water tank of Cesine, Avellino (Italy), is presented. In particular, the autoregressive integrated moving average (ARIMA) forecasting methodology is applied to model and forecast the daily water levels. This technique combines the autoregression and the moving average approaches, with the possibility to differentiate the data, to make the series stationary. In order to better describe the trend, over time, of the water levels in the reservoir, three ARIMA models are calibrated, validated and compared: ARIMA (2,0,2), ARIMA (3,1,3), ARIMA (6,1,6). After a preliminary statistical characterization of the series, the models' parameters are calibrated on the data related to the first 11 months of 2014, in order to keep the last month of data for validating the results. For each model, a graphical comparison with the observed data is presented, together with the calculation of the summary statistics of the residuals and of some error metrics. The results are discussed and some further possible applications are highlighted in the conclusions.
Prospecting Potential Inhibitors of Sortase A from Enterococcus faecalis: A Multidrug Resistant Bacteria, through In-silico and In-vitro Approaches
Authors: Das Satyajeet , Kumar H.S. Vijay , Pal Sudhir K. , Srivastava Vijay K. , Jyoti Anupam , Kumar Sanjit , Kaushik Sanket 
Published: December 2019

Background:
Enterococcus faecalis (Ef) infections are becoming dreadfully common in
hospital environments. Infections caused by Ef are difficult to treat because of its acquired
resistance to different class of antibiotics, making it a multidrug resistant bacteria. Key pathogenic
factor of Ef includes its ability to form biofilm on the surface of diagnostic and other medical
devices. Sortase A (SrtA) is a cysteine transpeptidase which plays a pivotal role in the formation of
biofilm in Ef, hence, it is considered as an important enzyme for the pathogenesis of Ef. Thus,
inhibition of (SrtA) will affect biofilm formation, which will reduce its virulence and eventually Ef
infection will be abridged.

Objective:
To find potential inhibitors of Enterococcus faecalis Sortase A (EfSrtA) through insilico
and in-vitro methods.

Methods:
Gene coding for EfSrtA was cloned, expressed and purified. Three-dimensional model of
EfSrtA was created using Swiss-Model workspace. In-silico docking studies using Autodock vina
and molecular dynamics simulations of the modelled structures using Gromacs platform were
performed to explore potential lead compounds against EfSrtA. In-vitro binding experiments using
spectrofluorometric technique was carried out to confirm and validate the study.

Results:
In-silico docking and in-vitro binding experiments revealed that curcumin, berberine and
myricetin bound to EfSrtA at nanomolar concentrations with high affinity.

Conclusion:
This is a first structural report of EfSrtA with curcumin, berberine and myricetin.
Taking in account the herbal nature of these compounds, the use of these compounds as inhibitors
will be advantageous. This study validated curcumin, berberine and myricetin as potential inhibitors
of EfSrtA.
Pathophysiological Functions of the lncRNA TUG1
Authors: Guo Chong , Qi Yuying , Qu Jiayuan , Gai Liyue , Shi Yue , Yuan Chengfu 
Published: December 2019

Background:
Long non-coding RNAs (lncRNAs) with little or no coding capacity are associated with
a plethora of cellular functions, participating in various biological processes. Cumulative study of lncRNA provides
explanations to the physiological and pathological processes and new perspectives to the diagnosis, prevention,
and treatment of some clinical diseases. Long non-coding RNA taurine-upregulated gene 1(TUG1) is one of
the first identified lncRNAs associated with human disease, which actively involved in various physiological
processes, including regulating genes at epigenetics, transcription, post-transcription, translation, and posttranslation.
The aim of this review was to explore the molecular mechanism of TUG1 in various types of human
diseases.

Methods:
In this review, we summarized and analyzed the latest findings related to the physiologic and pathophysiological
processes of TUG1 in human diseases. The related studies were retrieved and selected the last six
years of research articles in PubMed with lncRNA and TUG1 as keywords.

Results:
TUG1 is a valuable lncRNA that its dysregulated expression and regulating the biological processes
were found in a variety of human diseases. TUG1 is found to exhibit aberrant expression in a variety of malignancies.
Dysregulation of TUG1 has been shown to contribute to proliferation, migration, cell cycle changes,
inhibited apoptosis, and drug resistance of cancer cells, which revealed an oncogenic role for this lncRNA, but
some reports have shown downregulation of TUG1 in lung cancer samples compared with noncancerous samples.
In addition, the molecular and biological functions of TUG1 in physiology and disease (relevant to endocrinology,
metabolism, immunology, neurobiology) have also been highlighted. Finally, we discuss the limitations and
tremendous diagnostic/therapeutic potential of TUG1 in cancer and other diseases.

Conclusion:
Long non-coding RNA-TUG1 likely served as useful disease biomarkers or therapy targets and
effectively applied in different kinds of diseases, such as human cancer and cardiovascular diseases.
Development of Atovaquone Nanosuspension: Quality by Design Approach
Authors: Kakade Pratik , Gite Sandip , Patravale Vandana 
Published: December 2019

Objective:
The present study reports the use of MicrofluidizerTM technology to form a stable
nanosuspension of atovaquone (ATQ) using quality by design (QbD) approach.

Methods:
The patient-centric quality target product profile and critical quality attributes (CQAs) were
identified. A Box-Behnken design was employed for the optimization of dependent variables, while
CQAs like particle size and PDI were evaluated as response variables. Effective optimization of ATQ
nanosuspension preparation using Microfluidizer processor as a novel green technology was achieved
using QbD approach.

Result:
The prepared nanosuspension had a mean particle size of 865 nm ± 5%, PDI of 0.261 ± 3%, and
zeta potential of -1.79 ± 5 mV. The characterization of the prepared nanosuspension by SEM, DSC, and
XRD revealed its nano-crystalline nature whereas FTIR spectroscopic analysis confirmed the absence
of any physicochemical interaction because of process parameters between the drug and excipients.

Conclusion:
In vitro dissolution studies of the nanosuspension using USP-IV exhibited a 100% cumulative
drug release over 90 minutes, which is significantly better than that of ATQ pure API. In vivo
pharmacokinetic studies revealed bioequivalence of ATQ nanosuspensions by Microfluidizer homogenization
process to the marketed formulation1.
MCDCalc: Markov Chain Molecular Descriptors Calculator for Medicinal Chemistry
Authors: Carracedo-Reboredo Paula , Corona Ramiro , Martinez-Nunes Mikel , Fernandez-Lozano Carlos , Tsiliki Georgia , Sarimveis Haralambos , Aranzamendi Eider , Arrasate Sonia , Sotomayor Nuria , Lete Esther , Munteanu Cristian Robert , González-Díaz Humbert 
Published: December 2019

Aim:
Cheminformatics models are able to predict different outputs (activity, property,
chemical reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis,
metabolic reactions, nanoparticles, etc.).

Background:
Cheminformatics models are able to predict different outputs (activity, property, chemical
reactivity) in single molecules or complex molecular systems (catalyzed organic synthesis, metabolic
reactions, nanoparticles, etc.).

Objective:
Cheminformatics prediction of complex catalytic enantioselective reactions is a major goal
in organic synthesis research and chemical industry. Markov Chain Molecular Descriptors (MCDs)
have been largely used to solve Cheminformatics problems. There are different types of Markov chain
descriptors such as Markov-Shannon entropies (Shk), Markov Means (Mk), Markov Moments (πk), etc.
However, there are other possible MCDs that have not been used before. In addition, the calculation of
MCDs is done very often using specific software not always available for general users and there is not
an R library public available for the calculation of MCDs. This fact, limits the availability of MCMDbased
Cheminformatics procedures.

Methods:
We studied the enantiomeric excess ee(%)[Rcat] for 324 α-amidoalkylation reactions. These
reactions have a complex mechanism depending on various factors. The model includes MCDs of the
substrate, solvent, chiral catalyst, product along with values of time of reaction, temperature, load of
catalyst, etc. We tested several Machine Learning regression algorithms. The Random Forest regression
model has R2 > 0.90 in training and test. Secondly, the biological activity of 5644 compounds against
colorectal cancer was studied.

Results:
We developed very interesting model able to predict with Specificity and Sensitivity 70-82%
the cases of preclinical assays in both training and validation series.

Conclusion:
The work shows the potential of the new tool for computational studies in organic and medicinal
chemistry.
Novel [6]-gingerol Triazole Derivatives and their Antiproliferative Potential against Tumor Cells
Authors: de Lima Silva William Cezar , Conti Raphael , de Almeida Larissa Costa , Morais Pedro Alves Bezerra , Borges Keyller Bastos , Júnior Valdemar Lacerda , Costa-Lotufo Letícia Veras , de Souza Borges Warley 
Published: December 2019

Background:
Effective cancer treatment is a major public health challenge. The limitations of
current therapies and their adverse effects reduce the efficacy of treatment, leading to significant mortality
rates worldwide. Moreover, natural product chemistry occupies a prominent role in the search for
new treatment alternatives, by contributing a spectrum of chemical structures that may potentially yield
new bioactive compounds. The compound [6]-gingerol (1) is the main active substance in ginger
(Zingiber officinale) and several studies have shown it to produce beneficial effects, including antitumor
activity.

Objective:
This work aims to obtain new gingerol derivatives with cytotoxic activity.

Method:
[6]-gingerol was isolated and its derivatives were produced using click chemistry, obtaining
eight new compounds. All chemical structures were determined by means of IR, NMR and HRMS data,
and cytotoxicity was evaluated in the HCT 116 (colon carcinoma) and MCF-7 (breast carcinoma) cell
lines at concentrations of 5 µmol L-1 and 50 µmol L-1.

Results:
At 50 µmol L-1, more than 70% inhibition of cell growth was achieved with compounds 2e, 2g
against HCT 116, and 2b, 2d, 2e, 2f and 2g against MCF-7.

Conclusion:
The obtained compounds showed only moderate cytotoxic activity. However, the products
with substituents occupying the meta position in relation to the triazole ring showed increased cytotoxic
properties. The brominated compound (2g) showed the strongest activity, inhibiting cell proliferation by
87%.
β-D-Mannuronic Acid (M2000) as a Landmark in Pharmacology
Authors: Gaafar Nada A.G. , Razavi Alireza , Mirshafiey Abbas 
Published: December 2019

Objectives:
The goal of this article is to retrace the studies of β-D-Mannuronic Acid
(M2000) as a new immunosuppressive drug with non-steroidal anti-inflammatory drugs
(NSAIDs) property in miscellaneous aspects including in vitro, in vivo examinations, clinical trials
and related to clinical trials studies. Our goal is to compare the effect of this drug with other
similar drugs through varied researches and to follow tolerability, biocompatibility, potency, safety,
and efficacy of this medication in different studies, as well as to evaluate its therapeutic effectiveness
in various diseases.

Materials and Methods:
Different methods were applied in the studies of β-D-Mannuronic Acid
under in vitro, in vivo examinations, and clinical trials phase I, II and III and related investigations
to these clinical trials using different techniques showing the efficacy of this medication in the
treatment of various diseases.

Results:
The administration of β -D-Mannuronic Acid showed the greatest tolerability and biocompatibility
compared to diclofenac, piroxicam, and dexamethasone without or very low side
effects. The drug has shown a punchy effect on many molecules which participate either in physiologic
or in pathogenic activities in animal models and human. This new drug not only revealed
the anti-inflammatory and immunosuppressive properties but also based on the results of various
investigations, β-D-Mannuronic Acid showed the antidiabetic, cardioprotective and anti-tumoral
effects.

Conclusion:
β-D-Mannuronic Acid (M2000) as a novel immunosuppressive drug with NSAID
properties along with antidiabetic, cardioprotective and anti-tumoral efficacy showed great tolerability
and safety profile. In addition, it has no or mild adverse events compared with many other
medicines, therefore this medicament could be considered as a landmark in pharmacology and
represent turn point in the treatment of different diseases based on the experimental and in vitro
studies explained and clinical and related studies proved.
An Automated Method for Detecting the Scar Tissue in the Left Ventricular Endocardial Wall Using Deep Learning Approach
Authors: Singh Yashbir , Shakyawar Deepa , Hu Weichih 
Published: December 2019

Background:
Image evaluation of scar tissue plays a significant role in the diagnosis of
cardiovascular diseases. Segmentation of the scar tissue is the first step towards evaluating the
morphology of the scar tissue. Then, with the use of CT images, the deep learning approach can
be applied to identify possible scar tissue in the left ventricular endocardial wall.

Objective:
To develop an automated method for detecting the endocardial scar tissue in the left
ventricular using Deep learning approach.

Method:
Pixel values of the endocardial wall for each image in the sequence were extracted.
Morphological operations, including defining regions of the endocardial wall of the LV where
scar tissue could predominate, were performed. Convolutional Neural Networks (CNN) is a deep
learning application, which allowed choosing appropriate features from delayed enhancement cardiac
CT images to distinguish between endocardial scar and healthy tissues of the LV by applying
pixel value-based concepts.

Result:
We achieved 89.23% accuracy, 91.11% sensitivity, and 87.75% specificity in the detection
of endocardial scars using the CNN-based method.

Conclusion:
Our findings reveal that the CNN-based method yielded robust accuracies in LV endocardial
scar detection, which is currently the most extensively used pixel-based method of deep
learning. This study provides a new direction for the assessment of scar tissue in imaging modalities
and provides a potential avenue for clinical adaptations of these algorithms. Additionally this
methodology, in comparison with those in the literature, provides specific advantages in its translational
ability to clinical use.
Synthesis and Evaluation of 5-imino-4-thioxoimidazolidin-2-one Derivatives as Antibacterial and Antifungal Agents
Authors: Abbas Samir Y. , El-Sharief Marwa A.M. Sh. , Al-Harbi Reem A.K. , El-Gammal Eman W. , El-Sharief Ahmed M.S. 
Published: December 2019

Objective:
It was interesting to synthesize some new 5-imino-4-thioxoimidazolidin-2-
one derivatives with different halogenated and alkylated aromatic substituents at N-(1) and N-(3)
and evaluation of their expected antibacterial and antifungal activities.

Methods:
New 5-imino-4-thioxoimidazolidin-2-one derivatives were synthesized through the reaction of different halogenated and alkylated N-arylcyanothioformamides with halogenated and alkylated aryl isocyanates.

Results:
5-Imino-4-thioxoimidazolidin-2-ones were obtained in high yields with excellent purity. The activities of imidazolidines as antibacterial and antifungal agents were studied. Some of imidazolidine derivatives displayed significant antibacterial and antifungal activities.

Conclusion:
5-Imino-4-thioxoimidazolidin-2-ones were obtained in 77-90% yields with excellent purity. The antibacterial and antifungal activities suggest that some of the imidazole derivatives possess significant antimicrobial activity against B. subtilis, K. pneumonia and C. albicans and moderate activity against S. aureus.