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Effect of visual distraction on pain in adults undergoing colonoscopy: a meta-analysis

Zhang YY, Vimala R, Chui PL, Hilmi IN

Surg Endosc, 2023 Apr;37(4):2633-2643.
PMID: 36369410 DOI: 10.1007/s00464-022-09724-7

BACKGROUND: Pain is a contributing factor to the low compliance rate for performing a colonoscopy on screening for colorectal cancer.
PURPOSE: This meta-analysis aimed to evaluate the effect of visual distraction on adults undergoing colonoscopy.
METHODS: We searched PubMed, EMBASE, Web of Science, and Cochrane Library Database from their inception to February 2022. Randomized controlled trials comparing visual distraction with non-visual distraction were considered for inclusion. The fixed-effects and random-effects models were used to pool the data from individual studies and the Cochrane risk of bias assessment tool was used to determine the methodology quality.
RESULTS: This meta-analysis included four studies (N = 301) for pain level and total procedure time, three studies (N = 181) for satisfaction score, three studies (N = 196) for anxiety level, and four studie (N = 402) for willingness to repeat the procedure. The pooled analysis shown that significantly lower pain levels (SMD, - 0.25; 95% CI - 0.47 to - 0.02; P = 0.03), higher satisfaction score with the procedure (SMD, 0.63; 95% CI, 0.33 to 0.93; P

Matched MeSH terms: Databases, Factual
Computerised image analysis of vitiligo lesion: evaluation using manually defined lesion areas

Nugroho H, Ahmad Fadzil MH, Shamsudin N, Hussein SH

Skin Res Technol, 2013 Feb;19(1):e72-7.
PMID: 22233154 DOI: 10.1111/j.1600-0846.2011.00610.x

Vitiligo is a cutaneous pigmentary disorder characterized by depigmented macules and patches that result from loss of epidermal melanocytes. Physician evaluates the efficacy of treatment by comparing the extent of vitiligo lesions before and after treatment based on the overall visual impression of the treatment response. This method is called the physician's global assessment (PGA) which is subjective. In this article, we present an innovative digital image processing method to determine vitiligo lesion area in an objective manner.

Matched MeSH terms: Databases, Factual
Fulltext Prevalence of asthma-like symptoms and assessment of lung function in schoolchildren born with low birth weight

Zainal N, Rahardja A, Faris Irfan CY, Nasir A, Wan Pauzi WI, Mohamad Ikram I, et al.

Singapore Med J, 2016 Dec;57(12):690-693.
PMID: 26805669 DOI: 10.11622/smedj.2016019

INTRODUCTION: This study aimed to determine the prevalence of asthma-like symptoms among schoolchildren with low birth weight (LBW), and to compare the lung function of these children with that of children with normal birth weight.
METHODS: This was a comparative cross-sectional study. We recruited children aged 8-11 years from eight primary schools in Kota Bharu, Kelantan, Malaysia. The children were divided into two groups: those with LBW (< 2,500 g) and those with normal birth weight (≥ 2,500 g). Parents of the enrolled children were asked to complete a translated version of the International Study of Asthma and Allergies in Childhood questionnaire. Lung function tests, done using a MicroLoop Spirometer, were performed for the children in both groups by a single investigator who was blinded to the children's birth weight.
RESULTS: The prevalence of 'ever wheezed' among the children with LBW was 12.9%. This value was significantly higher than that of the children with normal birth weight (7.8%). Forced vital capacity (FVC), forced expiratory volume in one second, and forced expiratory flow when 50% and 75% of the FVC had been exhaled were significantly lower among the children with LBW as compared to the children with normal birth weight.
CONCLUSION: LBW is associated with an increased prevalence of asthma-like symptoms and impaired lung function indices later in life. Children born with LBW may need additional follow-up so that future respiratory problems can be detected early.

Matched MeSH terms: Databases, Factual
Fulltext Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition

Arnia F, Oktiana M, Saddami K, Munadi K, Roslidar R, Pradhan B

Sensors (Basel), 2021 Jul 04;21(13).
PMID: 34283116 DOI: 10.3390/s21134575

Facial recognition has a significant application for security, especially in surveillance technologies. In surveillance systems, recognizing faces captured far away from the camera under various lighting conditions, such as in the daytime and nighttime, is a challenging task. A system capable of recognizing face images in both daytime and nighttime and at various distances is called Cross-Spectral Cross Distance (CSCD) face recognition. In this paper, we proposed a phase-based CSCD face recognition approach. We employed Homomorphic filtering as photometric normalization and Band Limited Phase Only Correlation (BLPOC) for image matching. Different from the state-of-the-art methods, we directly utilized the phase component from an image, without the need for a feature extraction process. The experiment was conducted using the Long-Distance Heterogeneous Face Database (LDHF-DB). The proposed method was evaluated in three scenarios: (i) cross-spectral face verification at 1m, (ii) cross-spectral face verification at 60m, and (iii) cross-spectral face verification where the probe images (near-infrared (NIR) face images) were captured at 1m and the gallery data (face images) was captured at 60 m. The proposed CSCD method resulted in the best recognition performance among the CSCD baseline approaches, with an Equal Error Rate (EER) of 5.34% and a Genuine Acceptance Rate (GAR) of 93%.

Matched MeSH terms: Databases, Factual
Fulltext Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture

Eu CY, Tang TB, Lin CH, Lee LH, Lu CK

Sensors (Basel), 2021 Aug 20;21(16).
PMID: 34451072 DOI: 10.3390/s21165630

Colorectal cancer has become the third most commonly diagnosed form of cancer, and has the second highest fatality rate of cancers worldwide. Currently, optical colonoscopy is the preferred tool of choice for the diagnosis of polyps and to avert colorectal cancer. Colon screening is time-consuming and highly operator dependent. In view of this, a computer-aided diagnosis (CAD) method needs to be developed for the automatic segmentation of polyps in colonoscopy images. This paper proposes a modified SegNet Visual Geometry Group-19 (VGG-19), a form of convolutional neural network, as a CAD method for polyp segmentation. The modifications include skip connections, 5 × 5 convolutional filters, and the concatenation of four dilated convolutions applied in parallel form. The CVC-ClinicDB, CVC-ColonDB, and ETIS-LaribPolypDB databases were used to evaluate the model, and it was found that our proposed polyp segmentation model achieved an accuracy, sensitivity, specificity, precision, mean intersection over union, and dice coefficient of 96.06%, 94.55%, 97.56%, 97.48%, 92.3%, and 95.99%, respectively. These results indicate that our model performs as well as or better than previous schemes in the literature. We believe that this study will offer benefits in terms of the future development of CAD tools for polyp segmentation for colorectal cancer diagnosis and management. In the future, we intend to embed our proposed network into a medical capsule robot for practical usage and try it in a hospital setting with clinicians.

Matched MeSH terms: Databases, Factual
Fulltext Spatial Landslide Susceptibility Assessment Based on Novel Neural-Metaheuristic Geographic Information System Based Ensembles

Moayedi H, Osouli A, Tien Bui D, Foong LK

Sensors (Basel), 2019 Oct 29;19(21).
PMID: 31671801 DOI: 10.3390/s19214698

Regular optimization techniques have been widely used in landslide-related problems. This paper outlines two novel optimizations of artificial neural network (ANN) using grey wolf optimization (GWO) and biogeography-based optimization (BBO) metaheuristic algorithms in the Ardabil province, Iran. To this end, these algorithms are synthesized with a multi-layer perceptron (MLP) neural network for optimizing its computational parameters. The used spatial database consists of fourteen landslide conditioning factors, namely elevation, slope aspect, land use, plan curvature, profile curvature, soil type, distance to river, distance to road, distance to fault, rainfall, slope degree, stream power index (SPI), topographic wetness index (TWI) and lithology. 70% of the identified landslides are randomly selected to train the proposed models and the remaining 30% is used to evaluate the accuracy of them. Also, the frequency ratio theory is used to analyze the spatial interaction between the landslide and conditioning factors. Obtained values of area under the receiver operating characteristic curve, as well as mean square error and mean absolute error showed that both GWO and BBO hybrid algorithms could efficiently improve the learning capability of the MLP. Besides, the BBO-based ensemble surpasses other implemented models.

Matched MeSH terms: Databases, Factual
Identification of Distributed Denial of Services Anomalies by Using Combination of Entropy and Sequential Probabilities Ratio Test Methods

Ali BH, Sulaiman N, Al-Haddad SAR, Atan R, Hassan SLM, Alghrairi M

Sensors (Basel), 2021 Sep 27;21(19).
PMID: 34640773 DOI: 10.3390/s21196453

One of the most dangerous kinds of attacks affecting computers is a distributed denial of services (DDoS) attack. The main goal of this attack is to bring the targeted machine down and make their services unavailable to legal users. This can be accomplished mainly by directing many machines to send a very large number of packets toward the specified machine to consume its resources and stop it from working. We implemented a method using Java based on entropy and sequential probabilities ratio test (ESPRT) methods to identify malicious flows and their switch interfaces that aid them in passing through. Entropy (E) is the first technique, and the sequential probabilities ratio test (SPRT) is the second technique. The entropy method alone compares its results with a certain threshold in order to make a decision. The accuracy and F-scores for entropy results thus changed when the threshold values changed. Using both entropy and SPRT removed the uncertainty associated with the entropy threshold. The false positive rate was also reduced when combining both techniques. Entropy-based detection methods divide incoming traffic into groups of traffic that have the same size. The size of these groups is determined by a parameter called window size. The Defense Advanced Research Projects Agency (DARPA) 1998, DARPA2000, and Canadian Institute for Cybersecurity (CIC-DDoS2019) databases were used to evaluate the implementation of this method. The metric of a confusion matrix was used to compare the ESPRT results with the results of other methods. The accuracy and f-scores for the DARPA 1998 dataset were 0.995 and 0.997, respectively, for the ESPRT method when the window size was set at 50 and 75 packets. The detection rate of ESPRT for the same dataset was 0.995 when the window size was set to 10 packets. The average accuracy for the DARPA 2000 dataset for ESPRT was 0.905, and the detection rate was 0.929. Finally, ESPRT was scalable to a multiple domain topology application.

Matched MeSH terms: Databases, Factual
Fulltext Plant Disease Detection and Classification: A Systematic Literature Review

Ramanjot, Mittal U, Wadhawan A, Singla J, Jhanjhi NZ, Ghoniem RM, et al.

Sensors (Basel), 2023 May 15;23(10).
PMID: 37430683 DOI: 10.3390/s23104769

A significant majority of the population in India makes their living through agriculture. Different illnesses that develop due to changing weather patterns and are caused by pathogenic organisms impact the yields of diverse plant species. The present article analyzed some of the existing techniques in terms of data sources, pre-processing techniques, feature extraction techniques, data augmentation techniques, models utilized for detecting and classifying diseases that affect the plant, how the quality of images was enhanced, how overfitting of the model was reduced, and accuracy. The research papers for this study were selected using various keywords from peer-reviewed publications from various databases published between 2010 and 2022. A total of 182 papers were identified and reviewed for their direct relevance to plant disease detection and classification, of which 75 papers were selected for this review after exclusion based on the title, abstract, conclusion, and full text. Researchers will find this work to be a useful resource in recognizing the potential of various existing techniques through data-driven approaches while identifying plant diseases by enhancing system performance and accuracy.

Matched MeSH terms: Databases, Factual
Fulltext Remote Arrhythmia Detection for Eldercare in Malaysia

Chew KT, Raman V, Then PHH

Sensors (Basel), 2021 Dec 08;21(24).
PMID: 34960291 DOI: 10.3390/s21248197

Cardiovascular disease continues to be one of the most prevalent medical conditions in modern society, especially among elderly citizens. As the leading cause of deaths worldwide, further improvements to the early detection and prevention of these cardiovascular diseases is of the utmost importance for reducing the death toll. In particular, the remote and continuous monitoring of vital signs such as electrocardiograms are critical for improving the detection rates and speed of abnormalities while improving accessibility for elderly individuals. In this paper, we consider the design and deployment characteristics of a remote patient monitoring system for arrhythmia detection in elderly individuals. Thus, we developed a scalable system architecture to support remote streaming of ECG signals at near real-time. Additionally, a two-phase classification scheme is proposed to improve the performance of existing ECG classification algorithms. A prototype of the system was deployed at the Sarawak General Hospital, remotely collecting data from 27 unique patients. Evaluations indicate that the two-phase classification scheme improves algorithm performance when applied to the MIT-BIH Arrhythmia Database and the remotely collected single-lead ECG recordings.

Matched MeSH terms: Databases, Factual
Maternal and perinatal outcomes of pregnancies in systemic lupus erythematosus: A nationwide population-based study

Chen YJ, Chang JC, Lai EL, Liao TL, Chen HH, Hung WT, et al.

Semin Arthritis Rheum, 2020 06;50(3):451-457.
PMID: 32115237 DOI: 10.1016/j.semarthrit.2020.01.014

OBJECTIVES: Systemic lupus erythematosus (SLE) is an autoimmune disease that develops mainly in women of reproductive age. We aimed to explore the risk of pregnancy complications in Asian patients with SLE.
METHODS: From January 2005 to December 2014, we conducted a nationwide case-control study, using Taiwan's National Health Insurance Research Database. Obstetric complications and perinatal outcomes in SLE patients were compared with those without SLE.
RESULTS: 2059 SLE offspring and 8236 age-matched, maternal healthy controls were enrolled. We found increased obstetric and perinatal complications in SLE population compared with healthy controls. SLE patients exhibited increased risk of preeclampsia/eclampsia (8.98% vs.1.98%, odds ratio [OR]: 3.87, 95% confidence interval [95% CI]: 3.08-4.87, p<0.0001). Their offspring tended to have lower Apgar scores (<7) at both 1 min (10.7% vs. 2.58%, p<0.0001) and 5 min (4.25% vs. 1.17%, p<0.0001), as well as higher rates of intrauterine growth restriction (IUGR, 9.91% vs. 4.12%, OR: 2.24, 95% CI: 1.85-2.71, p<0.0001), preterm birth (23.70% vs 7.56%, OR: 3.00, 95% CI: 2.61-3.45, p<0.0001), and stillbirth (4.23% vs. 0.87%, OR: 3.59, 95% CI: 2.54-5.06, p<0.0001). The risks of preterm birth and stillbirth were markedly increased in SLE patients with concomitant preeclampsia/eclampsia or IUGR. Preterm birth of SLE patients was 1~4 gestational weeks earlier than that of healthy controls and the peak occurrence of stillbirth in SLE population was at 20~30 gestational weeks.
CONCLUSIONS: Asian SLE patients exhibited increased risks of maternal complications and adverse birth outcomes. Frequent antenatal visits before 20 gestational weeks are recommended in high-risk SLE patients.

Matched MeSH terms: Databases, Factual
Fulltext Uncovering drug repurposing candidates for head and neck cancers: insights from systematic pharmacogenomics data analysis

Chai AWY, Tan AC, Cheong SC

Sci Rep, 2021 12 14;11(1):23933.
PMID: 34907286 DOI: 10.1038/s41598-021-03418-1

Effective treatment options for head and neck squamous cell carcinoma (HNSCC) are currently lacking. We exploited the drug response and genomic data of the 28 HNSCC cell lines, screened with 4,518 compounds, from the PRISM repurposing dataset to uncover repurposing drug candidates for HNSCC. A total of 886 active compounds, comprising of 418 targeted cancer, 404 non-oncology, and 64 chemotherapy compounds were identified for HNSCC. Top classes of mechanism of action amongst targeted cancer compounds included PI3K/AKT/MTOR, EGFR, and HDAC inhibitors. We have shortlisted 36 compounds with enriched killing activities for repurposing in HNSCC. The integrative analysis confirmed that the average expression of EGFR ligands (AREG, EREG, HBEGF, TGFA, and EPGN) is associated with osimertinib sensitivity. Novel putative biomarkers of response including those involved in immune signalling and cell cycle were found to be associated with sensitivity and resistance to MEK inhibitors respectively. We have also developed an RShiny webpage facilitating interactive visualization to fuel further hypothesis generation for drug repurposing in HNSCC. Our study provides a rich reference database of HNSCC drug sensitivity profiles, affording an opportunity to explore potential biomarkers of response in prioritized drug candidates. Our approach could also reveal insights for drug repurposing in other cancers.

Matched MeSH terms: Databases, Factual*
Fulltext Automated detection of pain levels using deep feature extraction from shutter blinds-based dynamic-sized horizontal patches with facial images

Barua PD, Baygin N, Dogan S, Baygin M, Arunkumar N, Fujita H, et al.

Sci Rep, 2022 Oct 14;12(1):17297.
PMID: 36241674 DOI: 10.1038/s41598-022-21380-4

Pain intensity classification using facial images is a challenging problem in computer vision research. This work proposed a patch and transfer learning-based model to classify various pain intensities using facial images. The input facial images were segmented into dynamic-sized horizontal patches or "shutter blinds". A lightweight deep network DarkNet19 pre-trained on ImageNet1K was used to generate deep features from the shutter blinds and the undivided resized segmented input facial image. The most discriminative features were selected from these deep features using iterative neighborhood component analysis, which were then fed to a standard shallow fine k-nearest neighbor classifier for classification using tenfold cross-validation. The proposed shutter blinds-based model was trained and tested on datasets derived from two public databases-University of Northern British Columbia-McMaster Shoulder Pain Expression Archive Database and Denver Intensity of Spontaneous Facial Action Database-which both comprised four pain intensity classes that had been labeled by human experts using validated facial action coding system methodology. Our shutter blinds-based classification model attained more than 95% overall accuracy rates on both datasets. The excellent performance suggests that the automated pain intensity classification model can be deployed to assist doctors in the non-verbal detection of pain using facial images in various situations (e.g., non-communicative patients or during surgery). This system can facilitate timely detection and management of pain.

Matched MeSH terms: Databases, Factual
An Architecture of a Query Evaluation System For Deductive Databases

Ali Mamat

Sains Malaysiana, 1996;25.

The technology of deductive database is now mature enough due to the considerable research efforts that have been made on the field for the last ten years. This achievement is demonstrated by the emergence of efficient and easy to use systems with their capability of supporting a declarative, rule based style of expressing queries and applications on databases. This paper describes an overview of architecture of a query evaluation system for deductive databases that has been developed.
Teknologi pangkalan data deduktif sudah matang hasil daripada penyelidikan yang telah banyak dilakukan dalam tempoh 10 tahun yang lepas. Pencapaian ini dibuktikan melalui kemunculan sistem yang cekap dan mudah guna serta mempunyai keupayaan untuk mengungkap pertanyaan dan penggunaan ke atas pangkalan data secara deklaratif menerusi penggunaan petua. Dalam kertas ini diterangkan suatu ringkasan mengenai senibina sistem penilaian pertanyaan untuk pangkalan data deduktif yang sudah dibangunkan.

Matched MeSH terms: Databases, Factual
Sparking attention on African swine fever research on social media platform: An altmetric evaluation of top 100 highly cited articles

Basumatary B, Yunus MN, Verma MK

Res Vet Sci, 2023 May;158:26-33.
PMID: 36898955 DOI: 10.1016/j.rvsc.2023.02.010

African swine fever (ASF) is one of the highly contagious diseases of pigs that affect both domestic and wild pigs. The primary purpose of this research was to evaluate the online social attention on the ASF research to inform the research scientists and key stakeholders in the field by reporting the concise information of the most influential articles, social engagement, and impacts of the research. This study employed the altmetrics tool to evaluate the research papers. Bibliographic data of 100 articles were collected from Scopus; altmetric data was collected from the Altmetric.com database and analyzed using SPSS and Tableau. The articles were mainly mentioned on Twitter, followed by News Outlets and significant readers on Mendeley. Pearson correlation coefficients revealed a weak and insignificant correlation between Scopus Citation and Altmetric Attention Score (AAS). Mendeley Readership and Scopus Citation were moderately correlated. However, there was a significant positive correlation between the AAS and Mendeley readership. Using altmetric tools, the paper is the first research to shed light on the characteristics of ASF on social media.

Matched MeSH terms: Databases, Factual
A proposed stepwise approach to reducing medication errors in older people

Salmasi S, Wimmer BC, Khan TM, Zaidi STR, Ming LC

Res Social Adm Pharm, 2018 Feb;14(2):207-209.
PMID: 28330781 DOI: 10.1016/j.sapharm.2017.02.015
Matched MeSH terms: Databases, Factual
Response to Linguistic and psychometric validation of the Malaysian version of Diabetes Quality of Life-Brief Clinical Inventory (DQoL-BCI): Methodological issues to avoid misinterpretation

Neoh CF, Samah S, Wong YY, Hassali MA, Shafie AA, Lim SM, et al.

Res Social Adm Pharm, 2017 02 12;13(4):884.
PMID: 28259586 DOI: 10.1016/j.sapharm.2017.02.004
Matched MeSH terms: Databases, Factual/standards
Exploration of Global Trend on Biomedical Application of Polyhydroxyalkanoate (PHA): A Patent Survey

Paulraj P, Vnootheni N, Chandramohan M, Thevarkattil MJP

Recent Pat Biotechnol, 2018;12(3):186-199.
PMID: 29384069 DOI: 10.2174/1872208312666180131114125

BACKGROUND: Polyhydroxyalkanoates are bio-based, biodegradable naturally occurring polymers produced by a wide range of organisms, from bacteria to higher mammals. The properties and biocompatibility of PHA make it possible for a wide spectrum of applications. In this context, we analyze the potential applications of PHA in biomedical science by exploring the global trend through the patent survey. The survey suggests that PHA is an attractive candidate in such a way that their applications are widely distributed in the medical industry, drug delivery system, dental material, tissue engineering, packaging material as well as other useful products.
OBJECTIVE: In our present study, we explored patents associated with various biomedical applications of polyhydroxyalkanoates.
METHOD: Patent databases of European Patent Office, United States Patent and Trademark Office and World Intellectual Property Organization were mined. We developed an intensive exploration approach to eliminate overlapping patents and sort out significant patents.We demarcated the keywords and search criterions and established search patterns for the database request. We retrieved documents within the recent 6 years, 2010 to 2016 and sort out the collected data stepwise to gather the most appropriate documents in patent families for further scrutiny.
RESULTS: By this approach, we retrieved 23,368 patent documents from all the three databases and the patent titles were further analyzed for the relevance of polyhydroxyalkanoates in biomedical applications. This ensued in the documentation of approximately 226 significant patents associated with biomedical applications of polyhydroxyalkanoates and the information was classified into six major groups. Polyhydroxyalkanoates has been patented in such a way that their applications are widely distributed in the medical industry, drug delivery system, dental material, tissue engineering, packagingmaterial as well as other useful products.
CONCLUSION: There are many avenues through which PHA & PHB could be used. Our analysis shows patent information can be used to identify various applications of PHA and its representatives in the biomedical field. Upcoming studies can focus on the application of PHA in the different field to discover the related topics and associate to this study.We believe that this approach of analysis and findings can initiate new researchers to undertake similar kind of studies in their represented field to fill the gap between the patent articles and research publications.

Matched MeSH terms: Databases, Factual
Emerging trends in gene and bipolar disorder research: a bibliometric analysis and network visualisation

Zakaria WNA, Wijaya A, Al-Rahbi B, Ahmad AH, Zakaria R, Othman Z

Psychiatr Genet, 2023 Jun 01;33(3):102-112.
PMID: 36825833 DOI: 10.1097/YPG.0000000000000338

This study aims to use a bibliometric technique to evaluate the scientific output of gene and bipolar disorder research. The search query related to gene and bipolar disorder from the Scopus database identified 1848 documents from 1951 to 2020. The growth in the publications increased since early 1990, peaked in 2011, and started to decline thereafter. High occurrence in author keywords suggests that some research topics, such as "polymorphism", "linkage" and "association study" have waned over time, whereas others, such as "DNA methylation," "circadian rhythm," "" and "meta-analysis," are now the emerging trends in gene and bipolar disorder research. The USA was the country with the highest production followed by the UK, Canada, Italy and Germany. The leading institutions were Cardiff University in the UK, the National Institute of Mental Health (NIMH) in the USA, King's College London in the UK and the University of California, San Diego in the USA. The leading journals publishing gene and bipolar literature were the American Journal of Medical Genetics Neuropsychiatric Genetics, Molecular Psychiatry and Psychiatric Genetics. The top authors in the number of publications were Craddock N, Serretti A and Rietschel M. According to the co-authorship network analysis of authors, the majority of the authors in the same clusters were closely linked together and originated from the same or neighbouring country. The findings of this study may be useful in identifying emerging topics for future research and promoting research collaboration in the field of genetic studies related to bipolar disorder.

Matched MeSH terms: Databases, Factual
EcoliOverExpressionDB: a database of recombinant protein overexpression in E. coli

Habibi N, Samian MR, Hashim SZ, Norouzi A

Protein Expr Purif, 2014 Mar;95:92-5.
PMID: 24333540 DOI: 10.1016/j.pep.2013.11.014

Recombinant protein production is a significant biotechnological process as it allows researchers to produce a specific protein in desired quantities. Escherichia coli (E. coli) is the most popular heterologous expression host for the production of recombinant proteins due to its advantages such as low cost, high-productivity, well-characterized genetics, simple growth requirements and rapid growth. There are a number of factors that influence the expression level of a recombinant protein in E. coli which are the gene to be expressed, the expression vector, the expression host, and the culture condition. The major motivation to develop our database, EcoliOverExpressionDB, is to provide a means for researchers to quickly locate key factors in the overexpression of certain proteins. Such information would be a useful guide for the overexpression of similar proteins in E. coli. To the best of the present researchers' knowledge, in general and specifically in E. coli, EcoliOverExpressionDB is the first database of recombinant protein expression experiments which gathers the influential parameters on protein overexpression and the results in one place.

Matched MeSH terms: Databases, Factual*
Fulltext An estimate of the number of tropical tree species

Slik JW, Arroyo-Rodríguez V, Aiba S, Alvarez-Loayza P, Alves LF, Ashton P, et al.

Proc Natl Acad Sci U S A, 2015 Jun 16;112(24):7472-7.
PMID: 26034279 DOI: 10.1073/pnas.1423147112

The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Matched MeSH terms: Databases, Factual

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