bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genomic landscape of the emerging XDR Salmonella Typhi for mining druggable targets clpP, hisH, folP and gpmI and screening of novel TCM inhibitors, molecular docking and simulation analyses
Authors: Afzal Muneeba , Hassan Syed Shah , Sohail Saman , Camps Ihosvany , Khan Yasmin , Basharat Zarrin , Karim Asad , Aurongzeb Muhammad , Irfan Muhammad , Salman Muhammad , Morel Carlos M. 
Published: November 2022

Abstract
Typhoid fever is transmitted by ingestion of polluted water, contaminated food, and stool of typhoid-infected individuals, mostly in developing countries with poor hygienic environments. To find novel therapeutic targets and inhibitors, We employed a subtractive genomics strategy towards Salmonella Typhi and the complete genomes of eight strains were primarily subjected to the EDGAR tool to predict the core genome (n = 3207). Human non-homology (n = 2450) was followed by essential genes identification (n = 37). The STRING database predicted maximum protein-protein interactions, followed by cellular localization. The virulent/immunogenic ability of predicted genes were checked to differentiate drug and vaccine targets. Furthermore, the 3D models of the identified putative proteins encoded by the respective genes were constructed and subjected to druggability analyses where only “highly druggable” proteins were selected for molecular docking and simulation analyses. The putative targets ATP-dependent CLP protease proteolytic subunit, Imidazole glycerol phosphate synthase hisH, 7,8-dihydropteroate synthase folP and 2,3-bisphosphoglycerate-independent phosphoglycerate mutase gpmI were screened against a drug-like library (n = 12000) and top hits were selected based on H-bonds, RMSD and energy scores. Finally, the ADMET properties for novel inhibitors ZINC19340748, ZINC09319798, ZINC00494142, ZINC32918650 were optimized followed by binding free energy (MM/PBSA) calculation for ligand-receptor complexes. The findings of this work are expected to aid in expediting the identification of novel protein targets and inhibitors in combating typhoid Salmonellosis, in addition to the already existing therapies.
Correction factors for commissioning and patient specific quality assurance of stereotactic fields in a Monte Carlo based treatment planning system
Authors: Goodall Simon , Rowshanfarzad Pejman , Ebert Martin A 
Published: November 2022

Abstract
Validation of small field dosimetry is crucial for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Accurate and considered measurement of linear accelerator dose must be compared to precise and accurate calculation by the treatment planning system (TPS). Monte Carlo calculated distributions contain statistical noise, reducing the reliance that should be given to single voxel doses. The average dose to small volume of interest (VOI) can minimise the influence of noise, but for small fields introduces significant volume averaging. Similar challenges present during measurement of composite dose from clinical plans when a small volume ionisation chamber is used. This study derived correction factors for VOI averaged TPS doses calculated for small fields, allowing correction to an isocentre dose following account for statistical noise. These factors were used to determine an optimal VOI to represent small volume ionisation chambers during patient specific quality assurance (PSQA). A retrospective comparison of 82 SRS and 28 SBRT PSQA measurements to TPS calculated doses from varying VOI was completed to evaluate the determined volumes. Small field commissioning correction factors of under 5% were obtained for fields sizes of 8 mm and larger. Optimal spherical VOI with radius between 1.5mm to 1.8mm and 2.5 mm to 2.9 mm were determined for IBA cc01 and cc04 ionisation chambers respectively. Review of PSQA confirmed an optimal agreement between cc01 measured doses and a volume of 1.5 mm while cc04 measured doses showed no variation with VOI.
Identification of Potential Biomarkers for Colorectal Cancer Using Bioinformatics Analysis
Authors: luo an , xu henglang , xie mingjun , hu ke , jiang yiping , hu jia 
Published: November 2022

Abstract
Background
Colorectal cancer (CRC) is the most common malignant tumor of the intestine, and its incidence and mortality rate are at the forefront. Early diagnosis and intervention of CRC is of great significance. however, there is a lack of precise diagnostic biomarkers. We aim to explore potential biomarkers for CRC and provide a new treatment idea for CRC.
Methods
We first identified differentially expressed genes (DEGs) in 26 colorectal tumor tissue samples and 26 matched non-tumor tissue samples in the GSE25070 dataset. We then performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs using the Database for Annotation Visualization and Integrated Discovery (DAVID). We further constructed protein-protein interaction (PPI) networks of DEGs using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and screened 10 hub genes using Cytoscape software. GO and KEGG enrichment analysis of hub genes was done by the WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). Finally, we analyzed the expression levels and survival of hub genes using the Gene Expression Profiling Interactive Analysis (GEPIA) database.
Results
We obtained 756 DEGS (254 upregulated genes and 502 downregulated genes) from the GSE25070 dataset, and DEGs were mainly enriched in inflammatory response, neutrophil chemotaxis, and cytokine-cytokine receptor. Ten hub genes were identified, including five upregulated genes (VEGFA, IL1B, MMP9, CXCL8, and CCND1) and five downregulated genes (MAPK3, ADH1A, SLC26A3, ADH1C, and UGT1A8). Five upregulated genes were highly expressed in CRC patients, and IL1B and CXCL8 genes were significantly associated with overall survival in colorectal cancer patients, and high expression of IL1B and CXCL8 had a greater survival advantage.
Conclusion
IL1B and CXCL8 are potential biomarkers for CRC.
The role of miR-488-3p on suppressing colorectal cancer by Codonopsis Bulleyana Forest ex Diels in mice
Authors: Liu Lily , Luan Yunpeng 
Published: November 2022

Abstract
(Background) Colorectal cancer (CRC) is a frequently occurring cancer. We aimed to evaluate the roles and possible mechanism of microRNAs (miRs) and Codonopis bulleynana Forest ex Diels (cbFeD) in the development of mice CRC.
(Methods) The differentially expressed miRNAs (DEMs) in CRC mice and their response to cbFeD were analyzed using global miRNA expression profiling, and then the role of cbFeD on CRC was through regulating the expression of miRNA in mice was identified in MC38 cell lines that was incubated with cbFeD and over-expressed with miRNA mimics.
(Results) Results showed that 54 DEMs were found in CRC mice, and they enriched in the processes of cancer development and apoptosis. Among them, miR-488-3p was significantly increased and decreased following exposure to cbFeD. In cbFeD incubated MC38 cells, the expression of miR-488-3p was significantly decreased, and its target gene PTEN (phosphate and tension homology deleted on chromsome ten) was increased markedly. After over-expressing miR-488-3p mimics in MC38 cells, PTEN was decreased by 20% while a 3-fold increased when exposed to cbFeD for 48h. And it was also found that cbFeD could significantly suppress cell proliferation activity and promote apoptosis in MC38 cells, and it could play the above effects following over-expressed miR-488-3p mimics.
(Conclusions) Overall, our results here suggested that there may be a negative correlation between miR-488-3p and PTEN, and targeting PTEN by miR-488-3p may be a mechanism by which cbFeD suppresseed the CRC in mice.
A normalized differential sequence feature encoding method based on amino acid sequences
Authors: Zhao Xiaoman , Wang Xue , Jin Zhou , Wang Rujing 
Published: November 2022

Abstract
Background
Protein interactions is the foundation of all metabolic activities of cells, such as apoptosis, immune response and metabolic pathway. In order to optimize the performance of protein interaction prediction, a coding method based on normalized difference sequence characteristics (NDSF) of amino acid sequences is proposed.
Methods
By using the positional relationships between amino acids in the sequences and the correlation characteristics between sequence pairs, NDSF is jointly encoded. Using principal component analysis (PCA) and local linear embedding (LLE) dimensionality reduction methods, the coded 174-dimensional human protein sequence vector is extracted by using sequence features. This study compares the classification performance of four ensemble learning methods (AdaBoost, Extra trees, LightGBM, XGBoost) applied to PCA and LLE features, and uses cross-validation and grid search methods to find the best combination of parameters.
Results
The accuracy of NDSF is generally higher than that of MOS coding method, and the loss and coding time can be greatly reduced. The bar chart of feature extraction shows that the classification accuracy is significantly higher when using the linear dimensionality reduction method PCA than the nonlinear dimensionality reduction method LLE. After classification with XGBoost, the model accuracy reaches 99.2%, which is the best performance among all models.
Conclusions
NDSF combined with PCA and XGBoost may be an effective strategy for classifying different human protein interactions.
A Novel Hybrid PSO- and GS-based Hyperparameter Optimization Algorithm for Support Vector Regression
Authors: Acikkar Mustafa , Altunkol Yunus 
Published: November 2022

Abstract

Hyperparameter optimization is vital in improving the prediction accuracy of Support Vector Regression (SVR), as in all machine learning algorithms. This study introduces a new hybrid optimization algorithm, namely PSOGS, which consolidates two strong and widely used algorithms, Particle Swarm Optimization (PSO) and Grid Search (GS). This hybrid algorithm was experimented on five benchmark datasets. The speed and the prediction accuracy of PSOGS-optimized SVR models (PSOGS-SVR) were compared to those of its constituent algorithms (PSO and GS) and another hybrid optimization algorithm (PSOGSA) that combines PSO and Gravitational Search Algorithm (GSA). The prediction accuracies were evaluated and compared in terms of root mean square error and mean absolute percentage error. For the sake of reliability, the results of the experiments were obtained by performing 10-fold cross-validation on 30 runs. The results showed that PSOGS-SVR yields prediction accuracy comparable to GS-SVR, performs much faster than GS-SVR, and provides better results with less execution time than PSO-SVR. Besides, PSOGS-SVR presents more effective results than PSOGSA-SVR in terms of both prediction accuracy and execution time. As a result, this study proved that PSOGS is a fast, stable, efficient, and reliable algorithm for optimizing hyperparameters of SVR.
A ketogenic diet can mitigate SARS-CoV-2 induced systemic reprogramming and inflammation
Authors: Palermo Amelia , Li Shen , Hoeve Johanna ten , Chellappa Akshay , Morris Alexandra , Dillon Barbara , Ma Feiyang , Wang Yijie , Cao Edward , Shabane Byourak , Acin-Perez Rebeca , Petcherski Anton , Lusis Aldons , Hazen Stanley , Shirihai Orian , Pellegrini Matteo , Arumugaswami Vaithilingaraja , Graeber Thomas , Deb Arjun 
Published: November 2022

Abstract
The ketogenic diet (KD) has demonstrated benefits in numerous clinical studies and animal models of disease in modulating the immune response and promoting a systemic anti-inflammatory state. Here we investigate the effects of a KD on systemic toxicity in mice following SARS-CoV-2 infection. Our data indicate that under KD, SARS-CoV-2 reduces weight loss with overall improved animal survival. Muted multi-organ transcriptional reprogramming and metabolism rewiring suggest that a KD initiates and mitigates systemic changes induced by the virus. We observed reduced metalloproteases and increased inflammatory homeostatic protein transcription in the heart, with decreased serum pro-inflammatory cytokines (i.e., TNF-α, IL-15, IL-22, G-CSF, M-CSF, MCP-1), metabolic markers of inflammation (i.e., kynurenine/tryptophane ratio), and inflammatory prostaglandins, indicative of reduced systemic inflammation in animals infected under a KD. Taken together, these data suggest that a KD can alter the transcriptional and metabolic response in animals following SARS-CoV-2 infection with improved mice health, reduced inflammation, and restored amino acid, nucleotide, lipid, and energy currency metabolism.
SVM-based Classification of Multi-temporal Sentinel-2 Imagery of Dense urban Land Cover
Authors: Khurana Yash , Soni Pramod Kumar , Bhatt Devershi Pallavi 
Published: November 2022

Abstract
The technological breakthrough and the availability of multispectral remote sensing data have given rise to an ambitious challenge for the classification of the multispectral images accurately to support administrative bodies in decision-making. In this paper, the multi-temporal medium resolution Sentinel-2 imagery of the densely populated urban area of Delhi-NCR is classified using SVM into five different land cover classes, namely water bodies, barren land, vegetative region, road network, and residential areas. Further, the effect of different kernel functions of SVM on land cover classification performance is contrasted and the radial basis function (RBF) leads to the best results. The experimental results are compared with the maximum likelihood classification (MLC) method on different evaluation metrics. The SVM with RBF kernel shows promising improvements in the overall accuracy by 10 percent relative to the polynomial kernel and by 3 percent compared to MLC. The analysis of multitemporal spectral imagery of the study area reflects the increase in a built-up area (road network, Buildings), water bodies, and decrement in the area of barren land and vegetation.
Velocity-based approach to resistance training: the reproducibility and sensitivity of commercially available velocity monitoring technologies
Authors: Jukic Ivan , King Andrew , Sousa Colby A. , Prnjak Katarina , McGuigan Michael R. 
Published: November 2022

Abstract
This study examined the reproducibility of GymAware, PUSH2 and Vmaxpro velocity monitoring devices during resistance training (RT). The sensitivity of these devices to detect the smallest changes in velocity that correspond to true changes in RT performance was also investigated. Fifty-one resistance-trained people performed an incremental loading (1RM) test, and two repetitions to failure (RTF) tests with different loads, 72 hours apart. During all repetitions, mean velocity (MV) and peak velocity (PV) were simultaneously recorded by two devices of each brand. Overall, GymAware was the most reliable and sensitive device for detecting the smallest changes in RT performance, regardless of the velocity metric used. Vmaxpro can be considered as an equivalent, cheaper alternative to GymAware for RT monitoring and prescription, but only if the MV metric is used. Caution should be exercised when using PUSH2 in practice due to their comparatively higher, unacceptable measurement error and generally low sensitivity to detect changes in RT performance. Collectively, these findings support the use of MV and PV from GymAware and MV from Vmaxpro devices for RT monitoring and prescription due to their low magnitudes of error; thus, allowing for sensible detection of meaningful changes in neuromuscular status and functional performance during RT.
A New Hybrid Metaheuristic Algorithm for Energy-Aware Data Replication Based on IoT Applications
Authors: Khalifa Hamiden Abd El-Wahed , Alharbi Samaher , awad Ahmed 
Published: November 2022

Abstract
The Internet of Things allows us to connect different devices and objects, generate a large volume of huge data, process it, and store it on cloud computing. Recently, cloud computing has become necessary in using pay-for-use spaces to save time and cost. Used data replication in traditional cloud computing leads to excessive use of resources and devices, performance burdens, increased loads, excessive energy consumption, advanced user waiting, and improved response time. This paper proposes the use of multi-objective optimization (MOO) in combination with harris hawks optimization (HHO) and IoT-based salp swarm algorithm (SSA) in cloud computing. The new method called Multi-objective optimization Harris Hawks Optimization with Salp Swarm Algorithm (MOHHOSSA) is based on a set of objectives and integrating two critical technologies, HHO and SSA, to identify and place data replication across nodes using the least path between nodes in cloud computing. The proposed algorithm improves energy consumption (EC), carbon dioxide emission rate (CDER), and means service time (MST). The laboratory results proved the superiority of the proposed algorithm MOHHOSSA over other algorithms in terms of energy, load balancing, Mean service time, and the least expensive path between nodes in the proposed system.
Factors Associated with Decision Making about Family Planning Use by Refugee and Host Population in Adjumani District, West Nile, Uganda; A Cross Sectional Study
Authors: ACHOLA ROSELLINE , Atuyambe Lynn , Nabiwemba Elizabeth , Makumbi Freddrick , Garimoi Christopher Orach 
Published: November 2022

Abstract
Introduction
Uganda currently hosts an estimated 1.5 million refugees. The majority, (60.5%, n = 964,960) come from South Sudan. This study investigated factors associated with decision making for Family Planning (FP) use among host and refugee populations in Adjumani district, Uganda.
Methods
This was a comparative cross sectional study conducted in three refugee settlements of Pagirinya, Nyumazi and Mirieyi, and the surrounding host communities in Adjumani district. A total of 1,307 respondents, comprising 661 refugees and 646 host household heads were randomly selected and interviewed using multi stage cluster sampling. Quantitative data were collected using structured questionnaires with Open Data Kit (ODK). Data were analyzed using STATA V.14 C. Multivariable logistic regression was carried out to establish the factors associated with decision making to use family planning.
Results
The study found that modern contraceptive prevalence rate (mCPR) was 28.6% and 28.4% amongst host and refugees respectively. The factors significantly associated with decision to use FP amongst host population included religion, Anglicans were 6.2 times more likely to use FP compared to Catholics, AOR = 6.21, 95% CI [1.11-34.57]. Respondents who made joint decisions were nearly three times more likely to use modern FP methods compared to those who made personal decision, AOR = 2.69, 95% CI [0.89-138.39].
Similarly, amongst refugees, Anglicans were more likely to use modern family planning methods compared to Catholic refugees; AOR= 5, 95% CI [4.75-13.23] and AOR= 7.05 95% CI [2.8-44.88] respectively; respondents who attained tertiary education. AOR = 2.17 95% CI [0.11-43.08] and those who made joint decision; AOR 6.43 95% CI [1.78-16.08] were more likely to use modern FP methods.
The key barriers to decision making regarding modern FP use by the host, included harassment of women who did not consult their significant others (AOR = 0.07, 95% CI [0.01-0.79] and separation/divorce (AOR = 0.03, 95% CI [0.00-0.35]. Whereas amongst the refugees, main reasons for not using FP included not wanting to use FP” [45.8%], wanting to become pregnant [6.8%], and fear of side effects [5.8%].
Conclusions
Use of modern family planning is low amongst both refugee and host populations in Adjumani district. The main factors associated with decision to use FP amongst both refugee and host populations include religion, level of education and husband’s approval. Main reasons for not using modern FP methods include fear of side effects and not wanting to use FP by both host and refugees respectively. There is need to sensitize both communities about the benefits of FP and promote male involvement including couple counseling at community level.
Association between oral health and swallowing function
Authors: YAMANO TAKAFUMI , NISHI KENSUKE , OMORI FUMITAKA , WADA KAORI , YAMAGUCHI MASAHIRO , NAITO TORU 
Published: November 2022

Abstract
Objective
Oral care is effective for preventing pneumonia, but objective evaluation of its effect on swallowing is lacking. Oral assessment scores, such as the Oral Health Assessment Tool (OHAT), are used to evaluate the oral environment to monitor oral care.
Methods
We investigated the relationship between OHAT score and swallowing function in 24 patients aged 64–97 years.
Results
The OHAT score did not correlate with the video endoscopy (VE) or video fluorography (VF) scores. Furthermore, the OHAT score was not significantly different between the multiple- and no- or single-pneumonia episode groups. The group with multiple episodes of pneumonia had lower VE and VF scores than those with no or a single episode of pneumonia (p < 0.01).
Conclusions
Oral assessment, VE, and VF scores are necessary to evaluate swallowing in patients with suspected dysphagia. In addition, recurrent pneumonia among patients with a good oral environment has multiple contributing factors, including subclinical aspiration, pharyngeal clearance, and delayed activation of the gag reflex.
Behavioral outcome measures in preclinical rodent models for postoperative pain: A protocol for a systematic review and quantitative meta-analysis
Authors: Segelcke Daniel , Burgt Max van der , Pradier Bruno , Rosenberger Daniela , Macháček Philipp André , Jolmes Johanna , Vollert Jan , Pogatzki-Zahn Esther 
Published: November 2022

Abstract
Background
Understanding the (patho-) physiology of pain after surgery is incomplete; this hampers the effective treatment and leads to long-term consequences, including complications, chronification of pain, and potential drug misuse. Evidence-based research is essential to discover novel therapeutic options. Rodent models for postoperative pain have been developed to widen the knowledge about mechanisms and improve translation. These models cause evoked and non-evoked pain-related behaviors with specific duration, intensity, and timing expressions but with differences between studies. Reasons are heterogeneously performed (and/or reported) behavioral assays making it challenging to compare results across studies. Furthermore, indices about the influencing role of animal-related factors like age, sex, or the experimental setting are given. However, most of them were not systematically investigated, e.g., for pain-related behavior in rodent models of postoperative pain. Therefore, this review will systematically examine pain-related behaviour in different postoperative models in rodents. Acquisition of publication and experimental level characteristics will identify possible confounding and multilevel bias factors on results.
Methods
Four databases will be screened, and results will be compared for duplicates by automated and manual screening. Publication and experimental level characteristics will be extracted to (1) determine methodological aspects and use frequency of postoperative pain models and pain-related behavioral outcomes, (2) generate model-dependent behavior profiles, and (3) identify and critically evaluate confounder and bias factors on outcome measures and results.
Discussion
Findings from this study are necessary to inform researchers and improve future studies in design, performance, analysis, and ethical and translational aspects.
Systematic review registration:
Submitted to PROSPERO