Introduction: Dysregulated genes play a critical role in the development and progression of cancer, suggesting their potential as novel independent biomarkers for cancer diagnosis and prognosis. Prognostic model-based gene expression profiles are not widely utilized in clinical medicine. We investigated the prognostic significance of an expression profile-based gene signature for outcome prediction in patients with malignant pleural mesothelioma (MPM).Methods: The gene expression profiles of a large cohort of patients with MPM were obtained and analyzed by repurposing publicly available microarray data. A gene-based risk score model was developed with the training dataset and then validated with the TCGA-MESO (mesothelioma) dataset. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance of survival prediction. The biological function of the prognostic genes was predicted using bioinformatics analysis.Results: Three genes in the training dataset (GSE2549) were identified as significantly associated with the overall survival (OS) of patients with MPM and were combined to develop a three-gene prognostic signature to stratify patients into low-risk and high-risk groups. The MPM patients of the training dataset in the low-risk group exhibited longer OS than those in the high-risk group . Similar prognostic values for the three-gene signature were observed in the validated TCGA-MESO cohort . ROC analysis also demonstrated the good performance in predicting 3-year OS in the GEO and TCGA cohorts . The C-statistic for the 3-gene model was 0.761. Validation with TCGA-MESO confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic: 0.68). Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to MPM.Conclusions: This study has identified and validated a novel 3-gene model to reliably discriminate patients at high and low risk of death in unselected populations of patients with MPM. Further larger, prospective multi-institutional cohort studies are necessary to validate this model. Malignant pleural mesothelioma (MPM) is a rare cancer worldwide . HoweverDysregulated genes play a critical role in the development and progression of MPM, suggesting their potential as novel independent biomarkers for cancer diagnosis and prognosis . In receIn the present study, we integrate the gene expression profiles and matched clinical information from a GEO cohort including the patients with MPM, we detected three prognostic coding genes as biomarkers associated with the overall survival (OS) of patients with MPM. This established 3-gene prognostic risk model can effectively predict OS, and the significant prognostic power of this model was further validated in the TCGA-MESO cohort.PubMed was searched for articles relating to prognostic signatures in MPM using the search expression “prognostic [Title/Abstract] AND signature [Title/Abstract] AND [ OR (MPM[Title/Abstract]) OR (mesothelioma[Title/Abstract])]” with no filters. This search returned 6 articles, which were reviewed. One was a review article , 3 focusn = 40), normal pleura specimens (n = 5), and normal lung specimens (n = 4) in GSE2549 (Affymetrix Human Genome U133A Array) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE2549) (http://cancergenome.nih.gov/publications/publicationguidelines). According to TCGA guidelines, we chose the RNA-Seq count quantified by RSEM for the RNA expression profiles  ≤ 0.05  . The rawprofiles . The dif) ≤ 0.05 . The oveP-value ≤ 0.05 was considered statistically significant. All of data were processed and analyzed by R (version 3.5.0).One of 40 MPM samples did not have complete survival data, and we removed this case. Ultimately, 39 MPM samples and nine normal samples were included for the identification of differentially expressed genes. GSE2549 was used as the training set (39 samples), and TCGA-MESO was used as the validation set (84 samples). To discover the feasibility and reliability of a prognostic signature for MPM, univariate Cox proportional hazards regression analysis was applied to identify OS-related RNAs from differentially expressed RNAs . Then, aP-value of < 0.05 were considered significantly enriched function annotations.The enriched results were reported with Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway categories using the functional annotation clustering and functional annotation chart options , 31. TheP-value of ≤ 0.01, though genes with lower statistical significance may be important as well  in the GSE2549 cohort . This procedure selected a prognostic model containing three genes: LSM6 (ENSG00000164167), GZMB (ENSG00000164167), and HJURP (ENSG00000123485) , 3. A ri9 cohort .n = 42) and a high-risk group (n = 42) with significantly different OS according to the same risk score cutoff point obtained from the training dataset .Furthermore, in order to examine the robustness and practical application of the three-gene risk score model, we validated the prognostic power of this 3-gene signature using the mRNA expression values and survival information of MPM patients in another independent external dataset (TCGA-MESO). As shown in P = 0.020) in the GSE2549 cohort (P = 0.732)  .We performed time-dependent ROC curve analysis to compare the sensitivity and specificity of survival prediction between the 3-gene-signature-based risk score model and the 9-gene prognostic model with the GSE2549 dataset and the TCGA-MESO dataset. The AUC value was obtained from ROC analysis and was compared between these two predictive models. In the GSE2549 and TCGA-MESO datasets, the 3-gene-signature-based risk score model achieved KM-AUC values of 0.989 and 0.618, respectively, and were higher than those  derived from 9-gene prognostic model . The C-sP < 0.05). The result of GO enrichment analysis showed that the genes are involved in multiple biological processes, such as cell adhesion molecule binding, cadherin binding, and unfolded protein binding (To explore the functional implication of the prognostic genes in MPM tumorigenesis and development, we performed bioinformatics analysis to predict gene functions. The functional enrichment assay revealed that 61 GO terms and 10 pathways were involved (In the past years, great progress has been made in our understanding of the initiation and progression of MPM. However, the clinical outcome of patients with MPM still remains highly heterogeneous. Numerous studies devoted to differentially expressed genes in MPM by microarray. Gordon et al used the expression profiling data to accurately distinguish between MPM and adenocarcinoma, however, this method did serve as the prognostic markers . The firWe also note that the high-risk group identified in our analysis displayed enrichment for genes associated with cell adhesion molecule binding, cadherin binding, and so on. Adhesion , 38 and Though the three-gene signature is promising, there are limitations for this initial work. This model included the TCGA-MESO dataset as a validation cohort, but this dataset lacks patient samples. Therefore, these findings must be validated in a prospective study with independent patient samples.The clinical data of the two cohorts did not include TNM stage and other information, which limited our ability to adjust the predictive power of the signature. The TCGA-MESO data did not provide normal tissue, so we had to identify the prognostic signature through the GEO dataset and might have missing a vital signature, e.g., lncRNA and microRNA. Given the small sample size, we had a limited number of patients in the two cohorts for testing the performance of the signature. The training dataset was an array based U133A array, whereas the validation cohort was an NGS transcriptomic sequencing dataset, this might lead to result bias. Microarray results have some sensitivity to bioinformatics parameters that may vary among clinical sequencing programs and affect the performance of the signature, though the validation with the TCGA-MESO cohort demonstrates some robustness to pipeline variations.Here, we have performed the first gene prognostic analysis in MPM with normal tissues, resulting in an independently validated three-gene prognostic signature, as well as the identification of numerous genes with strongly statistically significant prognostic association for further study. Importantly, this three-gene prognostic signature performed well in the GEO and TCGA cohorts. Thus, this prognostic signature could be a clinically useful tool that is easily incorporated into a clinical sequencing program to individualize therapy for patients with MPM.In conclusion, we identified 3 genes associated with the prognosis of patients with MPM. The predicted target genes and biological functions of these genes provided further insight into the role of genes in the development of MPM. This signature has many potential prognostic and therapeutic implications for MPM patient management.J-GZ, S-HJ, and HM conceived, designed, or planned the study. HZ, JZ, and J-GZ analyzed the data. RR and S-HJ acquired data. J-GZ, S-HJ, HZ, JZ, and HM helped interpret the results. J-GZ and HZ provided study materials or patients. J-GZ, S-HJ, and HM drafted the manuscript. All authors revised and reviewed this work, and all authors gave their final approval of the submitted manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The DDBJ Center collects nucleotide sequence data and associated biological information from researchers and also services the Japanese Genotype–phenotype Archive (JGA) with the National Bioscience Database Center for collecting human data. To automate the submission process, we have implemented the DDBJ BioSample validator which checks submitted records, auto-corrects their format, and issues error messages and warnings if necessary. The DDBJ Center also operates the NIG supercomputer, prepared for analyzing large-scale genome sequences. We now offer a secure platform specifically to handle personal human genomes. This report describes database activities for INSDC and JGA over the past year, the newly launched GEA, submission, retrieval, and analysis services available in our supercomputer system and their recent developments.The Genomic Expression Archive (GEA) for functional genomics data from microarray and high-throughput sequencing experiments has been established at the DNA Data Bank of Japan (DDBJ) Center ( Since 1987, the DDBJ Center has been collecting annotated nucleotide sequences as its traditional database service. This endeavor is conducted in collaboration with GenBank   is a pub GenBank  at the N GenBank  at the E GenBank , and itsWithin the INSDC framework, the DDBJ Center also services the DDBJ Sequence Read Archive (DRA) for raw sequencing data and alignment information from high-throughput sequencing platforms , BioProjhttps://www.ddbj.nig.ac.jp/gea), which collects functional genomics data from microarray and high-throughput sequencing experiments. Besides the Gene Expression Omnibus (GEO) at the NCBI , in collaboration with the National Bioscience Database Center  at the Japan Science and Technology Agency (https://humandbs.biosciencedbc.jp/en/guidelines) and reviews data submission and usage requests.In addition to these unrestricted-access databases, the DDBJ Center also services a controlled-access database, the Japanese Genotype–phenotype Archive .From June 2017 to May 2018, the traditional DDBJ accepted 6011 nucleotide data submissions consisting of 5 926 950 entries, most of which were from Japanese research groups . The DDBJ periodical release includes both conventional sequence and bulk sequence data such as whole-genome shotgun (WGS), transcriptome shotgun assembly (TSA), and targeted locus study (TLS) but does not include third-party data (TPA) records . BetweenDuring June 2017 and May 2018, high-throughput sequencing data consisting of 43 174 runs have been registered to the DRA. As of 24 August 2018, the DRA has distributed 3.8 PB of sequencing data in SRA (2.7 PB) and FASTQ (1.1 PB) formats.https://ddbj.nig.ac.jp/jga/viewer/view/studies) and NBDC  websites. A large-scale dataset of the BioBank Japan project (https://humandbs.biosciencedbc.jp/en/data-use).The JGA is a controlled-access database for human genotype and phenotype data  similar  project  is availhttp://fged.org/projects/minseqe)—for unambiguous interpretation and data usage. These guidelines specify the provision of critical experimental elements in raw data, processed data, sample annotation, and protocols.The GEA is a public archive for functional genomics experiments including gene expression, epigenetics, and genome-protein interactions. Along with the GEO and ArrayExpress, the GEA supports two community-derived reporting standards—the Minimum Information About a Microarray Experiment (MIAME)  and the The GEA accepts functional genomics experiments in a structured and standardized MAGE-TAB format adopted by ArrayExpress . A submiThe submission workflow of microarray and sequencing experiment involves three and four steps, respectively Figure . The micThe sequencing submission consists of four steps. (i) preregistration of project information to BioProject, (ii) preregistration of sample information to BioSample, (iii) preregistration of raw data to the DRA and (iv) provision of processed data to the GEA Figure . The subhttps://www.ddbj.nig.ac.jp/gea/validation-e.html).In the GEA submission portal, the submitter creates IDF and SDRF metadata files associated with raw and processed data. In the IDF tab, the submitter provides an overview of the experiment: title, description, type and design; and protocols, array design (microarray), and publications. In the SDRF tab, the submitter verifies a SDRF template generated from the selected BioSample records, DRA submission (sequencing) or array design (microarray), and the IDF. The submitter is also required to include information describing the material and data files obtained from the samples, as well as the experimental variables under investigation. Lastly, in the ‘Overview’ tab, the submitter confirms the created IDF and SDRF metadata files. Then the system validates the submitted IDF and SDRF files and sends error and warning messages according to validation rules . Because the GEA and ArrayExpress share the accession namespace, the GEA numbers are searchable at ArrayExpress as well. The registered data may be kept private for a limited time, typically during the peer-review process of the relevant publication. The submitter can generate an access token for private GEA data in the submission portal for reviewers. The data would then become public either when the accession number associated with the data is published or at the release date designated by the submitter, whichever comes first. Public GEA experiments and array designs are accessible at its FTP (ftp://ftp.ddbj.nig.ac.jp/ddbj_database/gea) and will be indexed by ArrayExpress. In collaboration with the Database Center for Life Science (DBCLS), GEA metadata will become searchable at the DBCLS All Of gene Expression , an interface where public functional genomics data can be searched and viewed. The DDBJ Center also mirrors ArrayExpress data at its FTP site (ftp://ftp.ddbj.nig.ac.jp/mirror_database/arrayexpress).After the metadata and data files are reviewed, the GEA issues unique accession numbers to the experiments and array designs in ‘E-GEAD-The DDBJ Center archived 260 functional genomics experiments at the Center for Information Biology gene EXpression database (CIBEX) , which ohttps://www.ddbj.nig.ac.jp/biosample/validation-e.html). The submitter can correct errors and improve content according to the validation messages displayed in the submission portal. The BioSample submission system automatically assigns accession numbers to submitted records without errors. The BioSample curators have shifted from manual, record-by-record curation to validation rule improvement.As sequencing technologies are changing and submissions are increasing, our submission processes are also transitioning from manual curation to automatic validation. As part of such efforts, we have implemented the DDBJ BioSample validator and it validates submitted BioSample records according to validation rules, autocorrect formats, and sends error messages and warnings (http://ddbj.nig.ac.jp/vecscreen) and TXSearch (http://ddbj.nig.ac.jp/tx_search) services. For programmatic access to the data, the DDBJ Center also provides the Web API for Bioinformatics (WABI) (https://p.ddbj.nig.ac.jp), which is the web service for analyzing high-throughput DNA sequencing reads  , which is (WABI) , getentrng reads .ftp://ftp.ddbj.nig.ac.jp/ddbj_database/ and those in other mirrored databases at ftp://ftp.ddbj.nig.ac.jp/mirror_database/.We provide download services for public data in our archival databases at de novo sequence assembly . The calculation nodes are interconnected with InfiniBand, and the total peak performance of its CPUs is 372 Tflops. To support massive I/O in the big-data analysis, the NIG supercomputer is equipped with 10.6 PB of the Lustre parallel distributed file system (http://lustre.org). Large-scale DRA and JGA data are stored in 30 PB of the hierarchical storage system (the IBM Elastic Storage Server). The NIG supercomputer is also installed with major biological datasets and popular bioinformatics tools. Users can transfer large data between their local computers and the NIG supercomputer by using the high-speed-transfer software IBM Aspera (https://asperasoft.com/).The DDBJ Center also operates the NIG supercomputer, a commodity-based computer cluster designed for storing and analyzing large-scale sequencing data. The NIG supercomputer is composed of calculation nodes for general-purpose (554 thin nodes at 64 GB memory each) and memory-intensive tasks, including https://sc.ddbj.nig.ac.jp/ja/application/individual-genome-analysis-system, Japanese text only).The ever-increasing volume of personal sequencing data makes it difficult for researchers to prepare their own secure computer resources with sufficient storage and computing power and to transfer large data online from public databases including the JGA. To solve these issues, the DDBJ Center has provided a secured NIG supercomputer environment for analyzing personal sequencing data, which is composed of 32 thin nodes and 440 TB of storage and logically separates each user's computing environment Figure . JGA useTo process the growing number of data submissions and access requests to the NBDC and the JGA, the DDBJ Center and the NBDC are developing an integrated system which will seamlessly connect the NBDC request application processes and the JGA data submission/download processes by using the same user account system.https://dfast.nig.ac.jp), which is a bacterial genome annotation pipeline producing submission-ready DDBJ annotation files (To manage the increasing volume of sequencing submissions despite limited resources and budget, we are shifting from manual, record-by-record curation to a more automatic validation-based processing system. We are developing validators for BioProject and the DRA and will implement them to the submission systems to automate submission processes. We are also working to automate bacterial genome submissions by using the DDBJ Fast Annotation and Submission Tool (DFAST, on files .


Neurofeedback is a noninvasive treatment that changes brain activity in children with attention-deficit/hyperactivity disorder and thereby improves performance in these children. We examined the effect of neurofeedback on perceptual organization, visual and auditory memory in children with attention-deficit/hyperactivity disorder. This study was quasi-experimental with pre-test, post-test design, and control group. The sample included 20 children with attention-deficit/hyperactivity disorder were selected through convenience sampling in Khorramabad, central Iran in 2017. The sample was divided into control and experimental groups. Pre-test included Rey-Osterrieth complex figure and Wechsler digit span. Rey-Osterrieth complex figure test was used to measure perceptual organization and visual memory. Wechsler digit span was used to measure auditory memory. After conducting pre-test, the experimental group participated in neurofeedback training sessions. Theta/Beta protocol was applied for all participants. The control group did not receive any intervention. Then post-test was conducted on two groups.P<0.001) but neurofeedback training had no significant effect on the perceptual organization (P>0.05). Moreover, neurofeedback training enhanced auditory short-term memory and auditory working memory (P<0.05). Neurofeedback training significantly improved visual memory (Neurofeedback improved neurocognitive abilities in children with attention-deficit/hyperactivity disorder.  Attention deficit hyperactivity disorder is a neurodevelopmental disorder described by inattention, impulsivity, and hyperactivity. Attention deficit hyperactivity disorder frequently occur in childhood and have prevalence rate proximally 2% to 9% , valued Authors consider damaged neurocognitive functioning as a central dysfunction of the ADHD reflected in lacks, a range of neurocognitive dysfunction such as attention, inhabitation and working memory . SeveralWorking memory deficit is related to ADHD as well as academic problems. The deficit in working memory adversely influenced processes such as focusing attention, inhabitation of unrelated stimuli, recognition the meaning of the stimulus and selecting goals. These cognitive abilities are necessary for learning . WorkingIn this disorder, stimulant medication usually is recommended and assumed that it is an influential treatment of decreasing behavioral symptoms and improving neurocognitive dysfunction in children with ADHD. Nevertheless, the stimulant medication has different side effects including sleep problems, loss of appetite, and headache. Additionally, there is inadequate data about the long-term effect of this treatment .Neurofeedback is noninvasive, without medicine method of brain training that can help the diversity of disorders such as pain, fatigue, depression, anxiety, sleep disorders, cognitive decline, autism, attention and hyperactivity disorder, and post-traumatic stress disorder ,7. This Since the first study that used neurofeedback treatment in ADHD in 1979, a large number studies have examined the special effects of this treatment on diverse symptoms of ADHD for example inattention, impulsivity, and hyperactivity . MoreoveTherefore, we explored the effect of neurofeedback training on cognitive function such as perceptual organization and working memory in ADHA children.This study was quasi-experimental with pre-test, post-test design, and control group. Research community consisted of all children with attention-deficit/hyperactivity disorder in Khoramabad, central Iran in 2017. The sampling method was convenience sampling and participation included 20 children with attention-deficit/hyperactivity disorder. These children were divided into control and experimental groups (10 children in each group). Characteristics of children included: receiving a diagnosis of attention-deficit/ hyperactivity disorder by a psychiatrist and psychologist interview, having IQ more than 85, do not have known neurological or organic diseases or developmental disorders. The mean and standard deviation for the age of children in the experimental group were M=9.7, Std. Deviation= 2.90. In the control group M=9.60, Std. Deviation= 2.45. Before implementing treatment, pre-test was conducted on experimental and control groups. Pre-tests included Rey-Osterrieth complex figure and Wechsler digit span. After conducting pre-test, the experimental group participated in neurofeedback training sessions. Training session consisted of ten sessions (30 min). After finishing the neurofeedback training sessions, post-test were implemented for the experimental and control group. Parental informed consent was received for all of the children participated in this study.Collected data analyzed using SPSS ver. 19 . Statistical indexes such as mean, standard deviation and Covariance analysis were used to analyze the data. Neurofeedback protocol Each participant received ten neurofeedback sessions held 2 times a week. Each session lasted 40 min. One neurofeedback protocol (Theta/Beta) was applied to all participants. Thus they experienced similar location of electrodes that was active electrodes placed on CPz and FCz, according to the international 10/20 system. The reference electrode was located on the mastoid.The aim of Theta/Beta protocol is to inhibit theta (4–8 Hz) and reinforce beta (13–20 Hz) activity. The signal employed in neurofeedback was very much similar to a computer game so that points are gained during three different games: a worm going toward the finish line, a monkey climbing a tree, and a face smiling. There was 30 sec break between each of these three games.In the first 3 min of the first session, the baseline was ascertained by the trial of games using measure the Theta/Beta ratio. The participants were asked to concentrate on games. They must have reduced theta amplitude (4–8 Hz) below the baseline while increasing the beta amplitude (16–20 Hz) above the baseline.Rey-Osterrieth complex figure testRey-Osterrieth complex figure test designed through Andre Rey in 1941 and expanded through Paul-Alex Osterrieth in 1944 . This teFor doing complex figure test, first subjects are asked to copy a complex figure on the blank page in the best way. These complex figures have 18 components -13. ThreRey-Osterrieth complex figure test is usable in the survey of normal and atypical development in children . It is uDigit Span subtest from Wechsler intelligence scale for children Wechsler digit span is an old neuropsychological test used for the measure of auditory working memory . This suIn part two, subjects required to listen to digits and repeat them backward. The digit spans composed of 2 to 8 digits that expressed one second each digit. Thus in each subject digit span measured for two-part . Factor analysis has determined that digit span forward is a task for evaluation of short-term memory and backward digit span is a task for assessment of working memory -16. P=.78) between the experimental and the control groups. According to Therefore, according to This study examined the effectiveness of neurofeedback training on cognitive abilities such as perceptual organization, visual memory, short-term auditory memory and auditory working memory in children with ADHD. Neurofeedback can improve visual memory, short-term auditory memory, and auditory working memory, but neurofeedback training cannot enhance perceptual organization in children with ADDH. Neuropsychological assessments show a significant difference between pretest and posttest scores after receiving neurofeedback training. The results of this study confirm some of the conclusions of researchers who worked on the effects of neurofeedback. The effect of neurofeedback was examined on the symptom of ADHD and neurocognitive abilities. Neurofeedback improved attention and reaction time in children with ADHD . In the A functional magnetic resonance imaging study showed neurofeedback normalized parts of brain engaging in selective attention and inhibitory control . In neurThe sample size was a potential limitation in this study and results hardly related to the population of ADHD individual. This study could be expanded to a larger sample of children with ADHD. Further studies can run on other population with special needs such as learning disabilities and examine other neurocognitive abilities such as attention and reaction time.In conclusion, neurofeedback training did not make a significant difference in the perceptual organization in pre-test and post-test. One explanation for this result is that scores of the subject in pre-test of the perceptual organization was high rather than other assessments, therefore less improvement in the perceptual organization could be expected.


Villages are a relatively new consumer-driven model that promotes aging in place for community-dwelling seniors. Villages promote social engagement, civic engagement, member-to-member-support, and collectively bargain for services of their members. Members report improved social support and more confidence aging in their own homes. Currently, there are over 200 operational villages nationwide and the model is proliferating rapidly. Most Villages members are white, well-educated, and well resourced. Researchers at UC Berkeley conducted 6 focus groups with Latino, African American and Asian seniors (N=58) who have not joined Villages in their regions. Focus group findings describe a lack of awareness of the Village model among underrepresented groups; and barriers to membership including the cost of membership, lack of language inclusion, and lack of diversity. The national anti-immigrant discourse emerged as a barrier to membership for non-white seniors. Participants describe how Villages could make programmatic changes to attract a more diverse membership.


Interleukin-10 (IL-10) is one of the most important anti-inflammatory cytokine produced during bacterial infection. Two related phenomena explain the importance of IL-10 production in this context: first, the wide range of cells able to produce this cytokine and second, the wide effects that it causes on target cells. In a previous report we described opposing roles of IL-10 production during bacterial infection. Overall, during infections caused by intracellular bacteria or by pathogens that modulate the inflammatory response, IL-10 production facilitates bacterial persistence and dissemination within the host. Whereas during infections caused by extracellular or highly inflammatory bacteria, IL-10 production reduces host tissue damage and facilitates host survival. Given that these data were obtained using antibiotic susceptible bacteria, the potential application of these studies to multi-drug resistant (MDR) bacteria needs to be evaluated. MDR bacteria can become by 2050 a major death cause worldwide, not only for its ability to resist antimicrobial therapy but also because the virulence of these strains is different as compared to antibiotic susceptible strains. Therefore, it is important to understand the interaction of MDR-bacteria with the immune system during infection. This review discusses the current data about the role of IL-10 during infections caused by major circulating antibiotic resistant bacteria. We conclude that the production of IL-10 improves host survival during infections caused by extracellular or highly inflammatory bacteria, however, it is detrimental during infections caused by intracellular bacteria or bacterial pathogens that modulate the inflammatory response. Importantly, during MDR-bacterial infections a differential IL-10 production has been described, compared to non-MDR bacteria, which might be due to virulence factors specific of MDR bacteria that modulate production of IL-10. This knowledge is important for the development of new therapies against infections caused by these bacteria, where antibiotics effectiveness is dramatically decreasing. Infectious diseases caused by pathogenic bacteria have been historically a major cause of human death. The discovery and mass production of antibiotics dramatically reduced the mortality associated to bacterial infections for several years. However, the golden age of antibiotic seems to be over: according to a report led by the economist Jim O’Neill, in 2017 around 700,000 deaths were caused by multi-drug resistant (MDR) bacterial infections. His prediction, however, indicates that by 2,050 the mortality associated to MDR-bacterial infections will be around of 10 million .Acinetobacter baumannii, Pseudomonas aeruginosa, and Mycobacterium tuberculosis. Also, different species of the Enterobacteriaceae genus, including Klebsiella pneumoniae, Escherichia coli, are part of this group. The high priority group includes the pathogenic bacteria Staphylococcus aureus, Neisseria gonorrhoeae, Salmonella spp., among others.Due to this phenomenon, the World Health Organization (WHO) has classified the most concerning MDR-bacteria into different groups of priority according with the urgency to develop new antibiotics and therapies . The criStreptococcus pneumoniae, Pseudomonas aeruginosa, Francisella tularensis, Escherichia coli, and Mycobacterium tuberculosis  in the immunity against different pathogenic bacteria . We concrculosis . On the himurium .During extracellular or/and highly pro-inflammatory bacterial infection, the pathogen mostly neutralizes or eliminates the immune response effectors. In this context, the production of IL-10 modulates the immune response intensity and allows a successful bacterial clearance, without excessive host tissue damage. Although in some cases the absence of IL-10 makes the immune response more effective to clear the pathogen, the damage produced on host tissues is more severe and compromise host survival .The strategies used by intracellular pathogens and/or bacteria that modulate the inflammatory response are different and mainly consist in their capacity to evade the immune system . In thisThe studies performed so far that evaluate the role of IL-10 during bacterial infections have been performed using antibiotic susceptible bacteria. The conclusions reached in these reports cannot be translated to MDR-bacteria. Recent data have described that the immune response against antibiotic susceptible and MDR strains of the same bacterial specie may be remarkably different . TherefoIn this mini-review, we will discuss whether the role of IL-10 during infections caused by major antibiotic susceptible bacteria applies to major MDR-bacterial infections. Next, we will analyze whether MDR-bacteria induce a differential production of IL-10 as compared to non-MDR bacteria, to finally discuss about the possible mechanisms that may explain this difference.Acinetobacter baumannii (A. baumannii) is an opportunistic, aerobic, Gram-negative, and extracellular bacteria classified as a critical pathogen by the WHO  degradation  mice (One study demonstrated that during aumannii . Importaaumannii . Anotheraumannii . That reaumannii . The eleWT) mice .Pseudomonas aeruginosa (P. aeruginosa) is another bacterium classified in the critical group   . These se (CRKP)  than antlearance . CRKP shlearance  and the (in vivo . Another(in vivo  probablyresponse .Mycobacterium tuberculosis (M. tuberculosis) is another bacterium included in the critical WHO group. M. tuberculosis is a rod-shaped bacterium with a cell wall rich in lipids able to cause chronic and latent infections in the lung tissue  are the only WHO high priority bacterial species for which the role of IL-10 production has been described (Staphylococcus aureus is an extracellular Gram-positive bacterium able to cause serious lung (S. aureus (MRSA), and the result of this research is the identification of bacterial and host factors involved in MRSA infection  infection there is a rapid production of IL-10 . The consurvival . Howeversurvival . MRSA insurvival , 2015.Neisseria gonorrhoeae is an obligate Gram-negative human pathogen  is a pathogenic bacterium categorized in the high priority group with S. aureus and N. gonerrhoeae  ruginosa . Same reneumonia . Consistrculosis . Howeverrculosis . Moreovehe serum .A. baumannii infection, where children infected either with MDR A. baumannii presented the same levels of IL-10 as compared with children infected with non-MDR A. baumannii , present in bacteria such as K. pneumoniae, P. aeruginosa, A. baumannii, S. aureus, among other bacteria, is an important determinant for antimicrobial peptides and Polymyxin B resistance   .N. gonorrhoeae carries the opa gene .Even though the treatments against MDR bacteria are limited, they mostly consist of antibiotic administration. A recent report describe that Clarithromycin promotes the recruitment of anti-inflammatory myeloid cells able to produce IL-10, Arginase-1 and iNOS to the lung tissue and the spleen . The recIn the last years, increasing data support the idea that IL-10 production drives the development of a successful immune response during bacterial infection. However, whether IL-10 production is beneficial or not for host survival depends of the pathogen nature and the immune response associated to the infection .The rapid emergence of MDR bacteria is a major concern and has pushed the research community to invest more efforts in studying these bacteria. Most of the research done on MDR bacteria has been focused on epidemiological and genetic characterization ; and limA. baumannii and MRSA infection, the production of IL-10 is required for host survival. Both bacteria have acquired different virulence factors that allow them to neutralize the host immune response at different stages. In this scenario, a hyperactive immune response may occur, being IL-10 essential to modulate the intensity of it .The data discussed in this mini-review support the dual role of IL-10, previously described for non-MDR can also be found during MDR bacterial infection. For non-MDR bacterial infection IL-10 production is required for host survival during infections caused by extracellular and/or highly pro-inflammatory bacteria. Conversely, for MDR bacterial infection, IL-10 impairs host survival and bacterial clearance during intracellular and/or weak pro-inflammatory bacteria. During P. aeruginosa has been done using ampicillin resistant strains. In this scenario the production of IL-10 seems to be required for host survival, however, whether these data can be translated to carbapenem-resistant P. aeruginosa is unknown and more studies need to be done.As we discussed previously, most of the studies about host–pathogen interaction of S. enterica and N. gonorrhoeae are both intracellular pathogens, either way; IL-10 absence and/or neutralization improve the host immunity against these microbes and increase host survival . Overall, these data is consistent with our initial hypothesis.K. pneumoniae is a special case. K. pneumoniae is an extracellular bacterium that induces a weak pro-inflammatory response .Carbapenem-resistant response . Publishsurvival . Severalsurvival . It is qfections . These bfections  and durifections . Taking One of the most important concerns of this report is the lack of research regarding host–pathogen interaction on MDR bacteria. It is clear by the whole community that the golden age of antibiotics is over, however, the knowledge of how these bacteria have adapted to the host immune response and how we can improve it is very limited. Therefore, we believe that more research in host immunity and bacterial virulence is required to design new strategies to identify effective therapeutic targets or strategies.Finally, it is quite interesting MDR-bacteria stimulates higher IL-10 production as compared with non-MDR bacteria. We believe that the differential production of IL-10 may be a consequence of the changed expression pattern of different virulence factors displayed by these bacteria. This fact could explain why in general these bacteria are less virulent and why higher bacterial dose are commonly used to study host–pathogen interaction in mice.All authors listed have made substantial, direct, and intellectual contribution to the work and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In August 2017, the Uganda Ministry of Health was notified of increased cases of multidrug-resistant tuberculosis (MDR-TB) in Arua District, Uganda during 2017. We investigated to identify the scope of the increase and risk factors for infection, evaluate health facilities’ capacity to manage MDR-TB, and recommend evidence-based control measures.Mycobacterium tuberculosis resistant to at least rifampicin and isoniazid, confirmed by an approved drug susceptibility test. We reviewed clinical records from ARRH and compared the number of MDR-TB cases during January–August 2017 with the same months in 2013–2016. To identify risk factors specific for MDR-TB among cases with secondary infection, we conducted a case-control study using persons with drug-susceptible TB matched by sub-county of residence as controls. We observed infection prevention and control practices in health facilities and community, and assessed health facilities’ capacity to manage TB.We defined an MDR-TB case-patient as a TB patient attending Arua Regional Referral Hospital (ARRH) during 2013–2017 with a sputum sample yielding p = 0.02). Men were more affected than women , as were cases ≥18 years old compared to those < 18 years . In the case-control study, poor adherence to first-line anti-TB treatment  and initiating treatment > 15 months from symptom onset  were associated with MDR-TB. All ten facilities assessed reported stockouts of TB commodities. All 15 ambulatory MDR-TB patients we observed were not wearing masks given to them to minimize community infection. The MDR-TB ward at ARRH capacity was 4 patients but there were 11 patients.We identified 33 patients with MDR-TB, of whom 30 were secondary TB infection cases. The number of cases during January–August 2017 was 10, compared with 3–4 cases in January–August from 2013 to 2016 (The number of cases during January–August in 2017 was significantly higher than during the same months in 2013–2016. Poor adherence to TB drugs and delayed treatment initiation were associated with MDR-TB infection. We recommended strengthening directly-observed treatment strategy, increasing access to treatment services, and increasing the number of beds in the MDR-TB ward at ARRH. Mycobacterium tuberculosis resistant to at least isoniazid and rifampicin, is an increasing global public health problem [Multidrug-resistant tuberculosis (MDR-TB), caused by  problem . Strains problem . Though  problem , 4. The  problem . The Wor problem . This re problem .A 2013 study suggested that the proportion of TB cases that were drug-resistant in sub-Saharan Africa is lower than in some countries in Eastern Europe and Asia . HoweverSocio-political instability can increase the risk for emergence of MDR-TB . PersonsOf the eight districts in the West Nile sub-region of Uganda, seven have a GeneXpert machine for diagnosis of rifampicin-resistant TB. Patients diagnosed with rifampicin-resistant TB from the sub-region are referred to Arua Regional Referral Hospital (ARRH), where MDR-TB treatment is initiated while samples are referred to the National Tuberculosis Reference Laboratory for drug susceptibility testing (DST) to confirm multidrug-resistance. The GeneXpert was first deployed in the West Nile region in 2012; this was followed by another in, 2013, 2014, and in 2017 . In Arua District, there was no extra deployment of a Genexpert machine since 2013.In August 2017, Medical Teams International, a Non-Governmental Organization that operates in the region among refugees, reported to the Ministry of Health of Uganda that the number of MDR-TB cases in West Nile appeared to be increasing, including confirmed cases among refugees in settlements in Arua District. We conducted an investigation to confirm the reported upsurge in cases, identify risk factors for developing MDR-TB, assess the capacity of health facilities in Arua District to diagnose and manage TB, and recommend control and prevention measures.This was an outbreak investigation. We followed the key steps of disease outbreak investigations as described by the US Centers for Disease Control and Prevention .Arua District, Uganda  is located in northwestern Uganda. It has an estimated population of 840,900 . The district comprises 28 sub-counties, three of which host refugees . In 2017, the sub-region had an HIV prevalence of 3.1% .M. tuberculosis that was resistant to at least rifampicin and isoniazid, confirmed by culture, line probe assay, or any other drug susceptibility test since January 2013 to August 2017.We defined a TB case as one or more positive sputum smears or cultures since 2013 in a person residing in Arua District with clinical features consistent with TB. An MDR-TB case-patient was a person diagnosed with TB, with a sputum sample yielding Using registers obtained from ARRH, we identified all patients who were diagnosed with TB and MDR-TB from ARRH. From their medical records, which were retrieved from the same facility, we abstracted data on those TB and MDR-TB cases who presented during January 2013–August 2017 at the TB initiation center. Patients with MDR-TB were included in the study only if they had results from a drug susceptibility test. Clinically-diagnosed patients and those without test results were excluded from the study. Data abstracted included TB and MDR-TB case-patients’ age, sex, occupation, and place of residence. With the help of the Village Health Team and community key informants, we traced and interviewed each MDR-TB case-patient to collect information on exposure risk factors. These factors were smoking status, alcohol use, self-reported adherence to first-line TB and MDR-TB drugs, reasons for non-adherence, date of initial diagnosis with TB, date they developed symptoms of TB, presence of any co-morbidities, refugee status, type and status of housing, household size, primary or secondary MDR-TB, and contact with anyone diagnosed with TB before they were diagnosed with the disease. Non-adherence to TB treatment was defined as missing at least 10% of total prescribed drugs in a specified period .We conducted a descriptive analysis of MDR-TB case-patients by time, person, and place. Using open-ended questionnaires, we conducted hypothesis-generating interviews with case-patients to gather data on exposure status, date of onset of TB signs and symptoms, date of diagnosis, and commencement of first-line anti-TB treatment, self-reported adherence to TB treatment, HIV status, self-reported adherence to antiretroviral therapy (ART) if HIV-positive and on therapy, smoking, alcohol use, and refugee status.We conducted a case-control study during 24–28 August 2017, using MDR-TB cases identified from the review of health facility records. A control was a TB case-patient in Arua District who had been on anti-TB treatment for at least 2 months, enrolled on treatment within the same period as the case, and with negative GeneXpert results for drug resistance during the course of their treatment. A sampling frame for controls was prepared using health facility records. We used systematic random sampling to select three controls for every case, matched by sub-county of residence.We assessed adherence to IPC practices in health facilities and the community by using a checklist and observing the practices. Indicators assessed included infrastructure adequacy, availability and use of N95 respirators by healthcare workers, and surgical masks by TB patients.We purposefully selected ten health facilities from a total of 84 health facilities in the district, including ARRH, and assessed them for capacity to diagnose and manage TB patients. The selected facilities were health facilities that followed up MDR-TB patients who were discharged from ARRH after the intensive phase of treatment. We assessed each facility with the following indicators: number and skill mix of staff, whether they had received any MDR-TB or HIV/TB co-morbidity training, diagnostic infrastructure , and whether they screened for TB at all service points within the facility. Other variables assessed included whether TB patients were on DOTS verified through the records in the health facilities, availability of reliable transportation for sample referrals for GeneXpert diagnosis, and history of stockout of essential TB commodities .http://qgis.osgeo.org). To determine whether the reported number of MDR-TB cases during January–August in 2017 was a significant aberration from the expected number of cases, we calculated the mean number of cases each year during January–August 2013 to 2017 and estimated the Poisson probability of observing at least the number of reported cases in 2017 [Using surveillance data, we estimated the prevalence of TB in Arua District using the district population as the denominator. Population data were obtained from Uganda Bureau of Statistics projections (unpublished) for 2015–2020 and National Housing and Population Census report, 2014 . We alsoEthical clearance for the investigation was obtained from the Uganda Ministry of Health and from the U.S. Centers for Disease Control and Prevention (CDC), where the evaluation was deemed non-research. Permission was also obtained from the Arua District Health Office; ARRH granted permission to access their data. Health facility administrators gave us permission before any assessments of their facilities were conducted. Before analysis, we removed all identifying data and assigned a study identification number to ensure anonymity.. Three of the cases (9.1%) of the cases were primary MDR-TB cases. The median age of the 33 case-patients was 42 (range: 10–67) years; 26 (79%) were male and 32 (97%) were ≥ 18 years. The average annual population incidence over the 5 years was 0.82 cases per 100,000 population. During January–August 2017, there were 10 MDR-TB cases, compared with three cases during the same 8 months each year in 2013 to 2015, and four in 2016 (p = 0.0195). The average monthly number of MDR-TB cases was 1.3 in 2017, compared with 0.46 during 2013–2016. Considering the district population, the average annual incidence of MDR-TB among men was higher than that among women at  (p < 0.001). Among refugees, the average annual MDR-TB incidence was 2.8/100,000 (6 cases), compared to the average annual incidence among Ugandan nationals of 3.2/100,000 (27 cases) (p = 0.9) (Table 1).We identified 33 MDR-TB cases from Arua District enrolled for treatment from February 2013 to August 2017 .During 2013 to 2017, there were 4742 TB reported cases in Arua District . Hence, the 5-year proportion of all TB cases that was MDR-TB was 0.70 /1000 (33 cases). The 33 MDR-TB patients came from 48% (13/27) of sub-counties in Arua District. Of the affected sub-counties, the proportion of all TB cases that were MDR-TB was highest in Oluko sub-county (0.21/1000) and lowest in Omugo sub-county (0.023/1000) Non-adherence to first-line TB treatment occurred in 45% (15/33) of case-patients compared with 9.9% (10/101) of controls . Similarly, among the case-patients, 12% (4/33) initiated treatment ≥15 months after the start of TB symptoms, compared with 5% (5/101) among controls . Also, 52% (17/33) of case-patients compared with 32% (33/101) of controls had HIV co-infection . Contact with another TB patient, smoking, drinking alcohol, refugee status, and occupation were not significantly associated with development of MDR-TB.(Table 2).In the multivariable conditional logistic regression analysis, non-adherence to first-line anti-TB treatment  and delayed treatment initiation ≥15 months after start of TB symptoms  were significantly associated with MDR-TB (Table 3).Of the 10 facilities assessed, 8 (80%) had an accredited laboratory that could provide TB diagnostic services. All reported having a functional microscope in their laboratories. All facilities reported having experienced stockouts of TB drugs, microscope slides, laboratory reagents, and N95 respirators at some point in the period from 2013 to 2017. ARRH reported that they had experienced stockouts of GeneXpert cartridges. During our visit, all facilities had drugs in stock; however, only ARRH had any N95 respirators. While all accredited facilities reported having a functional laboratory, only 5 (63%) had at least two laboratory staff; 4 (50%) reported not having any clinical staff trained in MDR-TB management During our visit in August 2017, there were 11 inpatients with MDR-TB; however, the MDR-TB isolation ward was built to accommodate only four inpatients. This forced some MDR-TB patients to be shifted to a ward outside the MDR-TB isolation area that was designed to accommodate drug-susceptible TB patients. In all 10 health facilities evaluated, no personnel wore masks when interacting with TB patients. However, ventilation was adequate as windows in all the facilities were left open. In the community, no ambulatory MDR-TB case-patients were wearing masks given to them at discharge from ARRH or any protective masks to minimize transmission. Additionally, in over 80% of homes visited, windows were not open. MDR-TB patients shared sleeping rooms with members of their household without any precautionary measures in place.The average monthly number of incident MDR-TB cases in 2017 in Arua District was more than twice those during 2013–2016. Poor adherence to first-line TB drugs and delayed treatment initiation relative to the onset of signs of TB were associated with development of MDR-TB. Of the 10 health facilities investigated, all reported stockouts of essential TB supplies at some point during the study period from 2013 to 2017 and all had inadequate numbers of trained laboratory personnel. Nearly half of healthcare workers were untrained in MDR-TB management. The MDR-TB treatment initiation center was overcrowded, forcing the hospital leadership to transfer some MDR-TB patients to the regular TB ward, increasing the risk of transmission. In the communities, ambulatory MDR-TB patients did not wear face masks provided to them at discharge from ARRH as they proceed to the stabilization phase of treatment. They therefore mix freely with community and household members without any precautions. Multiple studies have found that obligatory wearing of facemasks reduced transmission of MDR-TB by 56%, though inadequacy in its use in isolation has been highlighted .Poor adherence to first-line TB drugs may have been caused by both patient and institutional factors. Our investigation showed that health facilities managing TB and MDR-TB cases sometimes ran out of essential TB drugs, which could result in treatment interruption. On the other hand, patient-related factors, e.g., financial challenges with transport, lack of social support, forgetfulness, being away from home, alcohol use, and perceived or real side effects of drugs, have been cited as common barriers to adherence to TB treatment in African countries and other developing countries with endemic MDR-TB , 19. OurUnnecessary delay in taking appropriate action may be occasioned by a long turn-around time between sample collection and release of results, and even more time before appropriate treatment is administered. Such delays in diagnosis and initiating treatment among MDR-TB patients prolongs the time spent in the community, and therefore increases the likelihood of transmitting the disease to others in their community . A studyThis increase in MDR-TB cases in Arua District may have been due to a multiplicity of factors. ‘First, delays in diagnosis and treatment among MDR-TB patients may have propagated transmission in the community. Beyond this, stockout of TB drugs in health facilities might have interrupted treatment among TB patients, and therefore facilitated the development of MDR-TB. Studies need to be conducted to assess the contribution of other patient factors including alcohol and poverty. Of note is the influx of refugees from South Sudan into the region in recent years. There was a sharp increase in the refugee population in West Nile in August 2016 . RefugeeAlthough there was no significant association between HIV infection and developing MDR-TB, studies conducted in Ethiopia and Belarus indicate that HIV co-infection is a strong independent risk factor for MDR-TB; in both studies, respondents infected with HIV were at least two times more likely to have MDR-TB than those who were HIV-negative , 30. HowThis study had several limitations. It was not possible to ascertain whether the observed rise in MDR-TB in the West Nile region was due to the increased deployment of improved diagnostic facilities or a real increase in cases in the region. However, records from the Uganda National TB and Leprosy Control indicate that, in the West Nile region, the GeneXpert was first deployed in 2012 in Pakwach Health Center IV and Yumbe Hospital in Nebbi and Yumbe Districts respectively; this was followed by Arua Regional Referral Hospital in Arua District in 2013. This was followed by deployments in Adjumani Hospital in Adjumani District in 2014, and in Nebbi and Moyo Hospitals in Nebbi and Moyo Districts. In Koboko  and Zombo Districts the Genexpert was installed in 2017 . A number of variables had missing values. Nonetheless, we fitted a dummy variable called unknown in the multivariate logistic regression model in order to maintain our sample size in the analysis. In our estimation of sub-county TB incidence, we used TB cases diagnosed at facilities. This may have underestimated the incidence as undiagnosed symptomatic patients were left out.During the investigation, we attempted to mitigate the potential adverse effect of these limitations on the validity of our study findings by using tools and strategies for data collection, triangulation and frequent corroboration of information obtained during the interviews.Reported MDR-TB cases increased in 2017 in Arua District compared with the previous 4 years. MDR-TB was associated with poor adherence to first-line TB treatment and delay in seeking treatment. The capacity of health facilities to adequately manage MDR-TB cases was compromised. Health facilities in the district experienced stockouts of essential commodities, and had an inadequate number of trained staff in MDR-TB. While increase in MDR-TB cases may also occur due to changes in the surveillance system or strengthened laboratory capacity, there was no evidence for that in this study. We recommend reducing delays in diagnosis and treatment initiation through strengthening TB diagnostics, including GeneXpert, improved TB infection control and prevention, and supporting adherence among both local and refugee populations through DOTS and other relevant strategies. Other recommendations include expanding the MDR-TB ward at ARRH, addressing logistical challenges related to drug quantification, ordering and supply, and training healthcare workers in MDR-TB management.


Drosophila system, an excellent platform for understanding the interplay between genetics and biophysics. In sum, the integrative approaches that combine multiple advances in these fields are increasingly necessary to enable a deeper understanding of how to analyze both natural and synthetic multicellular systems.Reverse-engineering how complex multicellular systems develop and function is a grand challenge for systems bioengineers. This challenge has motivated the creation of a suite of bioengineering tools to develop increasingly quantitative descriptions of multicellular systems. Here, we survey a selection of these tools including microfluidic devices, imaging and computer vision techniques. We provide a selected overview of the emerging cross-talk between engineering methods and quantitative investigations within developmental biology. In particular, the review highlights selected recent examples from the  Answers to many human health challenges require an integrated systems-level understanding of the body . BiocompC. elegans, the zebrafish or the fruit fly—Drosophila melanogaster, serve as proof-of-principle platforms for developing tools to analyze multicellular systems or to test new techniques in forward-engineering living systems . T. TDrosopDrosophila embryos is the high-throughput data collection enabled by the number of embryos that can be obtained at low cost. However, sorting, positioning and orienting of many embryos or other post-embryonic organs is a technical hurdle that needs to be addressed. Furlong et al. adopted the concept of fluorescence-activated cell sorting (FACS) and designed a device for sorting embryos expressing a fluorescent protein marker [Drosophila embryos that directs the flow direction of embryos into different outlets [One of the advantages of using n marker . The dev outlets . The com outlets .Drosophila embryos in batch for high-throughput microinjection. They designed a micro-assembly of protruded hydrophobic surfaces to achieve large-scale positioning and orienting of the embryos [Bernstein et al. presented an early attempt to position and orient  embryos . Embryos embryos .Drosophila embryos. A first microfluidic array was designed to utilize passive hydrodynamics to trap, position and vertically orient Drosophila embryos  on multicellular samples often requires multi-modal microfluidic device designs. Lucchetta et al. designed pioneering microfluidic devices to investigate how temperature regulates embryogenesis , 72. Theogenesis . Researcogenesis . To accoulations . The autDrosophila larvae [Drosophila wing disc  and simulation have greatly increased the accuracy and functionality of newly-designed devices , 64, 79.Drosophila tissues, require three-dimensional imaging techniques. An increasingly diverse range of imaging modalities is enabling researchers to investigate deeper into tissues. Recent improvements of fluorescence-based imaging modalities have increased imaging resolution, sample penetration and acquisition rate while reducing phototoxicity and photobleaching [Due to the larger scales involved, multicellular systems, including leaching , 85. In leaching , 87  than lasers used in one-photon confocal microscopy. The near-infrared laser allows deeper penetration (2–3 times deeper for two-photon) into the sample, compared to confocal microscopy , like traditional CT, uses X-rays to produce sectioning of a sample and uses computers to reconstruct the 3D morphology of the specimen . Micro-Cee, etc. , 124. MiDrosophila embryos [The combination of multiple imaging modalities opens new possibilities to utilize the strengths while avoiding the limitations of individual techniques. For example, Truong et al. combined two-photon microscopy with light-sheet microscopy to implement two-photon-scanned light-sheet microscopy for  embryos . This co embryos . However embryos .Drosophila providing a versatile system for proof-of-concept studies.Besides the introduction of new imaging principles, existing imaging technologies are often combined for multiplexing of functionalities that further increases in performance –96, 98. Drosophila wing. In short, the goal of analysis is to convert images into arrays of numbers that are amenable to statistical evaluation. This helps create data-driven models or to validate predictions from phenomenological or mechanistic models. In this section, we discuss how both conventional machine-learning and deep-learning algorithms play critical roles in the analysis of multicellular systems, using selected examples focused on the fruit fly. In particular, we show how deep learning is rapidly emerging as a solution to accelerate the analysis of biological big data  . In a CNl stages . The algDrosophila include image registration. For example, cultured samples often move during image acquisition. The movement, along with deformations within the tissue, makes spatial quantification of features a difficult task. Image registration for biological samples is a two-step process: a) segmentation to identify regions to be registered, and (b) registration of the region of interest. Conventional machine-learning algorithms are not well-suited for this task as they often rely on manual identification of intensity-based features that vary over time. Liang et al. used deep learning to segment out the pouch from time-lapse movies of Drosophila wing discs that expresses GCaMP6, a genetically-encoded fluorescent sensor [2+ dynamics [Additional applications of deep learning for analyzing multicellular systems in t sensor . Segmentdynamics . The fuldynamics .Drosophila. These algorithms can be used to tackle complicated problems and reveal structure in data that is too big or too complex for the human brain to comprehend. One of the biggest challenges in using these algorithms is that they require extremely large datasets that are well-annotated to train the algorithm. To circumvent this challenge, researchers have been working on ways to train models more efficiently with less data. Advancements in transfer learning enable the deep learning to apply classification capabilities acquired from one data type to another data type, thus increasing its robustness [In summary, data-driven learning algorithms, such as machine learning and deep learning, serve as powerful new techniques for image processing of multicellular systems such as bustness . HoweverSystematic approaches that integrate advanced microfluidic devices, imaging acquisition, and machine learning are essential techniques for analyzing the development of multicellular systems. There is an emerging need and intensive focus toward accelerating the cycle of hypothesis generation and testing and interdisciplinary collaboration through the engineering of integrative experimental and computational pipelines Fig. b. SignifDrosophila. Advances in traditional fluorescence-based imaging is also significantly increasing image-acquisition speed, penetration and signal-to-noise ratio [From the traditional fluorescence-based imaging to X-ray-based micro-CT, we are seeing a range of new imaging technologies being applied to multicellular systems, including genetic model systems such as se ratio , 96, 102se ratio , 167. Thse ratio , 96. TheDrosophila larval neural cord, compared with hundreds of images needed for traditional CNN [With the large amount of image data generated from experiments, machine learning is becoming an integral part of bio-image analysis. Significant progress in terms of computational power and availability of open-source modeling languages like TensorFlow has made machine learning accessible to cell and developmental biologists. Recently developed algorithms, based on the concept of transfer learning, has decreased the required sample sizes needed for training learning algorithms. For instance, U-Net required only 30 training images to analyze onal CNN . Algoritonal CNN –170. Howonal CNN . Currentonal CNN –174. TheDrosophila provides an ideal playground for developing and testing computational models of many aspects of development including pattern formation [Finally, computational models are an additional tool for reverse-engineering multicellular systems. They are often required to generate new insights for explaining emergent phenomena. They also systematize the process of hypothesis generation to close the iterative loop in reverse-engineering multicellular systems Fig. a. For exormation –180, orgormation  and morpormation .Drosophila, with a significant focus on modelling cell mechanics during morphogenesis. These methods include cellular Potts models, vertex models, continuum models, viscoelastic models, subcellular element models and immersed boudary methods, to name a few. Interested readers are referred to several reviews that focus on computational model development and validation [Various methods have been used to model cell-based processes in lidation , 47, 183lidation ) and mullidation , 186). Alidation , reviewelidation , 188–190lidation ). A couplidation –194.Drosophila and other genetic model systems paving the way, is now reaching an exponential phase of synergistic growth.A future goal for the reverse engineering of multicellular system should be the integration of data acquisition and analysis as highlighted in this review with the development and validation of computational models to guide the analysis of multicellular systems into generalizable pipelines . Because


Food contains various compounds, and there are many methods available to analyze each of these components. However, the large amounts of low-molecular-weight metabolites in food, such as amino acids, organic acids, vitamins, lipids, and toxins, make it difficult to analyze the spatial distribution of these molecules. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging is a two-dimensional ionization technology that allows the detection of small metabolites in tissue sections without requiring purification, extraction, separation, or labeling. The application of MALDI-MS imaging in food analysis improves the visualization of these compounds to identify not only the nutritional content but also the geographical origin of the food. In this review, we provide an overview of some recent applications of MALDI-MS imaging, demonstrating the advantages and prospects of this technology compared to conventional approaches. Further development and enhancement of MALDI-MS imaging is expected to offer great benefits to consumers, researchers, and food producers with respect to breeding improvement, traceability, the development of value-added foods, and improved safety assessments. Food ingredients contain a wide variety of nutritional components such as carbohydrates, proteins, peptides, lipids, minerals, vitamins, amino acids, and organic acids. In addition to the intentionally included ingredients, food can also contain contaminants such as pesticide residue, the residue of pharmaceuticals given to animals, mycotoxins, food additives, and carcinogenic substances introduced during food processing. Therefore, from the point of view of food safety, it is very important to verify all constituents in food. The diverse physical properties of these constituents require varied methods of analysis for detection, and these ingredients generally must first be purified for qualitative and quantitative analyses. Gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography-mass spectrometry (HPLC-MS) are commonly used to analyze food components. GC-MS is used for the detection and identification of volatile organic compounds such as amino acids, polyols, and vitamins, which are commonly derivatized . HPLC-MSMS-based imaging utilizing the principle of matrix-assisted laser desorption/ionization (MALDI) is a relatively new imaging method for small metabolites ,7,8, lipThe concept of MALDI-MS imaging was first introduced in the early 2000s. Caprioli et al.  performeMALDI-MS imaging was initially developed to analyze protein localization. At this time, there was a great demand for the detection of post-translational modifications according to a mass difference or the localization of hormone-like substances for which specific antibodies are difficult to obtain. However, this was not an easy task owing to quantitative limitations of these molecules. In contrast, lipids and very small molecules such as organic acids and nucleic acids were confirmed to be favorable molecules for detection with MALDI-MS imaging ,19,20. MMALDI-MS imaging has emerged as a valuable tool for the visualization of low-molecular-weight metabolites, but sometimes the matrix itself contributes to ionization interference. For this reason, other ionization methods such as desorption electrospray ionization mass spectrometry (DESI-MS) ,27 and sThe number of published articles with the key term “mass spectrometry imaging” in the PubMed database has gradually increased in the last 20 years. Only 90 papers on the topic were published up to 1995, whereas more than 3000 papers applying this technology have been published from 2016 to 2019. With respect to its application in food sciences, there were only 10 papers retrieved from a search with the key term “mass spectrometry imaging food” up to 2000. However, the number of papers doubled every 5 years thereafter, increasing to 15 in 2001–2005 and to 36 in 2006–2010; moreover, this number has been increasing rapidly in the last decade, with 240 papers reported since 2016 in this field. Many of these studies were aimed at using MS imaging to ensure the reliability of food and to increase the value of the food .A schematic of the protocol for MALDI-MS imaging is shown in The biological tissue samples used for MALDI-MS imaging require storage at −80 °C to maintain the intact form and spatial organization of the biomolecules in the samples. The most favorable tissues for this purpose are fresh-frozen tissues, which can be prepared with various methods such as using powered dry ice, liquid nitrogen, or liquid nitrogen-chilled isopentane, among others . In addiSmall-sized tissues and high-water content samples are hard to cut into appropriate sections without mounting. However, the use of typical embedding agents such as an optimal cutting temperature (OCT) compound must be avoided for samples destined for MALDI-MS imaging since the molecules derived from these agents can introduce ionization interference with respect to the biomolecules of interest . TherefoThe ionization efficiency is partly dependent on the thickness of the tissue section. In general, 5–20-μm-thick sections are prepared for the analysis of low-molecular-weight molecules. The use of thinner tissue sections (2–5 μm in thickness) are recommended for the analysis of high-molecular-weight molecules (3–21 kDa). We recommend the use of an ITO-coated glass slide for thaw-mounting of the sections because these transparent slides enable microscopic observation of the section after MALDI-MS imaging.One of the major challenges of MALDI-MS imaging is maintaining the original shape of the tissue during the preparation of sections, which is particularly difficult when a section is created from fragile, and/or hard samples. High-quality sections can be made by creating a section using an adhesive film , which iN-linked glycans  has also been used to analyze post-translational modifications −) are generally detected, and sodium adduct ions ([M + Na]+) and potassium adduct ions ([M + K]+) are often observed in the analyses of biological samples. Thus, the choice of an appropriate matrix is essential to obtain meaningful biomolecule images ..m/z). HoTo obtain high spatial resolution, new matrix coating methods have also been established. Shuai et al. developed an electric field-assisted scanning-spraying matrix coating system to deposit the matrix on tissue with crystal sizes of <10 μm . This syCoffea arabica beans [N-glycan imaging analysis with high resolution [Recently, new ionization technology for higher ionization efficiency has been reported. Laser ablation DART imaging mass spectrometry was performed to detect the spatial distributions of highly volatile compounds in cross sections of ca beans . Moreovesolution . In 2019solution . It can https://scils.de/) will be needed in the near future to handle such big data for convenient interpretation. These data platforms could also perform multivariate statistical analyses, which could lead to meaningful data interpretation for researchers. In fact, datasets of unlimited size can be visualized and multivariate statistical analyses can be performed for detailed interpretation [https://ms-imaging.org/wp/imzml/)MALDI-MS imaging generates an enormous amount of data. Therefore, diversification of analysis methods such as cloud-based analysis (e.g., SCiLS, retation ,83. The retation . A numbeMALDI-MS imaging is a valuable tool to visualize food compounds and identify not only the nutritional content but also the geographical origin of the food for improved traceability, food safety, and breed enhancement, among other applications. We anticipate that MALDI-MS imaging will be used extensively in the food industry in the near future. However, certain challenges of this technology will need to be overcome, including the limited detection of molecules present at low concentrations or ionization efficiency. Therefore, further improvements to the method and/or new developments in the equipment should be a research focus to enable the sensitive detection of these molecules.


Streptococcus pneumoniae infection as shown by experiments employing murine models of pneumococcal infection. The protective effect of CRP is due to reduction in bacteremia. There is a distinct relationship between the structure of CRP and its anti-pneumococcal function. CRP is functional in both native and non-native pentameric structural conformations. In the native conformation, CRP binds to pneumococci through the phosphocholine molecules present on the C-polysaccharide of the pneumococcus and the anti-pneumococcal function probably involves the known ability of ligand-complexed CRP to activate the complement system. In the native structure-function relationship, CRP is protective only when given to mice within a few hours of the administration of pneumococci. The non-native pentameric conformation of CRP is created when CRP is exposed to conditions mimicking inflammatory microenvironments, such as acidic pH and redox conditions. In the non-native conformation, CRP binds to immobilized complement inhibitor factor H in addition to being able to bind to phosphocholine. Recent data using CRP mutants suggest that the factor H-binding function of non-native CRP is beneficial: in the non-native structure-function relationship, CRP can be given to mice any time after the administration of pneumococci irrespective of whether the pneumococci became complement-resistant or not. In conclusion, while native CRP is protective only against early stage infection, non-native CRP is protective against both early stage and late stage infections. Because non-native CRP displays phosphocholine-independent anti-pneumococcal activity, it is quite possible that CRP functions as a general anti-bacterial molecule.One host defense function of C-reactive protein (CRP) is to protect against  CRP iing site . Once CRing site –12.Streptococcus pneumoniae are gram positive bacteria that asymptomatically colonize the upper respiratory tract   , 20. In  if the LPS is modified by adding a few PCh residues to it. The binding of CRP to PCh-modified LPS increases based on the number of PCh residues added and subsequently affects the resistance of the organism to the killing effects of serum . Also, tt attack .S. pneumoniae, because human CRP does not activate murine complement via the classical pathway  which is a variant of PspC  via Hic that also recruits factor H (2+-independent manner (Besides, factor H, factor H , 75. Pnet manner .S. pneumoniae (Staphylococcus aureus, Bacillus subtilis, Streptococcus pyogenes, and Streptococcus agalactiae (CRP binds to several pathogenic serotypes of eumoniae –79 and beumoniae . CRP, lieumoniae –84. CRP alactiae , 78.Salmonella enterica serovar Typhimurium, which is a gram negative bacterium and to which CRP does not bind in vitro (S. enterica in the presence of serum (Haemophilus influenzae (H. influenzae undergoes phase variation in expression of the PCh on the cell surface-exposed outer core of the LPS. PCh-positive variants are more sensitive to the bactericidal activity of human serum which requires the binding of serum CRP to whole bacteria with subsequent activation of complement (H. influenzae to vary PCh expression to zero may relate to its ability to cause invasive infection by evading attack by CRP (H. influenzae infection have not been established yet to determine whether CRP protects against infection with H. influenzae (Neisseriae spp. in a Ca2+-dependent manner (Neisseriae and, like H. influenzae, Neisseriae also undergo phase variation in expression of the PCh on their LPS (Neisseriae either, employing native or non-native pentameric CRP.The anti-bacterial action of CRP is not limited to gram positive bacteria only. CRP also protects mice from the early stages of infection with in vitro . But CRPof serum . CRP alsfluenzae . H. inflmplement –88. The k by CRP . Mouse mfluenzae . CRP alst manner –91. PCh Carcinoscorpius rotundicauda, CRP was identified as the major LPS-binding protein in infections with Pseudomonas aeruginosa (Some experiments suggest a role of CRP in protecting animals against lethal toxicity of LPS, although the subject has been controversial –96. In truginosa . CRP bouruginosa . The binruginosa . Upon biruginosa , 98. Comin vitro (2+-independent manner depends on the combination of protein form, lipid composition, and membrane shape (in vivo. Structural changes in vivo may be converting CRP into an anti-inflammatory molecule assuming that the ultimate pro-inflammatory by-product, mCRP, is continuously being removed. An intrinsically disordered region of amino acid residues 35–47 in CRP is responsible for mediating the interactions of mCRP with diverse ligands (Native pentameric CRP can dissociate into mCRP via an intermediate non-native pentameric structure , 99–101.in vitro , 102–104in vitro , 105–107in vitro . The mecne shape , 110. Sune shape . Since m ligands , and pos ligands –50.While native CRP is protective only against early stage infection, non-native pentameric CRP is protective against both early stage and late stage infections in murine models of pneumococcal infection. Because non-native pentameric CRP displays PCh-independent anti-pneumococcal activity, it is quite possible that CRP functions as a general anti-bacterial molecule. Thus, pentameric CRP is an anti-inflammatory molecule.S. pneumoniae strains in serum and enhanced antibody-dependent complement activation (A long-term goal could be to focus on the discovery and design of small-molecule compounds to target CRP, a compound that can change the structure of endogenous CRP so that the structurally altered CRP is capable of binding to factor H-bound pneumococci. A recent study showed that injections of sub-inhibitory concentrations of antibiotics enhanced the binding of CRP to three antibiotic-resistant tivation . Based oAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Dipteryx alata Vogel (Fabaceae). The experimental analysis delivered average precision around 92% with an associated processing times below 30 miliseconds.Detection and classification of tree species from remote sensing data were performed using mainly multispectral and hyperspectral images and Light Detection And Ranging (LiDAR) data. Despite the comparatively lower cost and higher spatial resolution, few studies focused on images captured by Red-Green-Blue (RGB) sensors. Besides, the recent years have witnessed an impressive progress of deep learning methods for object detection. Motivated by this scenario, we proposed and evaluated the usage of Convolutional Neural Network (CNN)-based methods combined with Unmanned Aerial Vehicle (UAV) high spatial resolution RGB imagery for the detection of law protected tree species. Three state-of-the-art object detection methods were evaluated: Faster Region-based Convolutional Neural Network (Faster R-CNN), YOLOv3 and RetinaNet. A dataset was built to assess the selected methods, comprising 392 RBG images captured from August 2018 to February 2019, over a forested urban area in midwest Brazil. The target object is an important tree species threatened by extinction known as  Preservation of sensitive tree species requires timely and accurate information on their distribution in the area under threat. Remote sensing techniques have been increasingly applied as alternatives to costly and time consuming field surveys for assessing forest resources. For this purpose, satellite, aerial and, more recently, Unmanned Aerial Vehicle (UAV) have been the most common platforms used for data collection.Multispectral ,2,3,4,5 Immitzer et al.  applied Voss and Sugumaran  combinedWhile numerous studies have been conducted on multispectral, hyperspectral, LiDAR and combinations of them, there are few studies relying on RGB images for tree detection/classification. Feng et al.  used RGBIn the last few years, approaches based on deep learning, such as Convolutional Neural Networks (CNNs) and their variants, gained popularity in many fields, including remote sensing data analysis. Mizoguchi et al.  applied Regarding plant species classification and diseases detection based on leaf images, several works were developed ,26,27,28Dipteryx alata Vogel (Fabaceae), popularly known as baru or cumbaru (henceforth cumbaru), which is threatened by extinction according to the IUCN (2019) . This species has a high economic potential and a wide range of applications, mainly for the use of non-timber forest products. It is distributed over a large territory, being mostly associated to the Brazilian Savanna, although it also occurs in the wetlands [To the best of our knowledge, no study focused thus far on state-of-the-art deep learning-based methods for tree detection on images generated by RGB cameras on board of UAVs. The present study addressed this gap and presented an evaluation of deep learning-based methods for individual tree detection on UAV/RGB high resolution imagery. This study focused on a tree species known as Our work hypothesis is that state-of-the-art deep learning-based methods are able to detect single tree species upon high-resolution RGB images with attractive cost, accuracy and computational load. The contribution of this work is twofold. First, we assessed the usage of high-resolution images produced by RGB cameras carried by UAVs for individual trees detection. Second, we compared three state-of-the-art CNN-based object detection methods, namely FasterRCNN, RetinaNet and YOLOv3, for the detection of cumbaru trees on said UAV/RGB imagery.The rest of this paper is organized as follows. The experiments were conducted in four main steps see . First, In total, 392 UAV images were acquired over seven months (from August 2018 to February 2019 in six missions). An advanced Phantom 4 UAV equipped with a 20-megapixel camera captured the images at flight heights of 20–40 m (see https://github.com/wkentaro/labelme). In this process, a bounding box specified by the top-left and bottom-right corners was annotated for each cumbaru tree sample in the image.Each image was annotated by a specialist using LabelMe software .The object detection methods compared in this study are briefly described in the following . Thus, each prediction in YOLOv3 is composed of four parameters for the bounding box (coordinates), one objectness score and C class probabilities. To improve detection precision, YOLOv3 predicts boxes at three different scales using a similar idea to feature pyramid networks [YOLOv3 : Unlike or boxes . For eacnetworks . As a baRetinaNet : SimilarWe adopted in our experiments a five-fold cross validation strategy. Thus, all images were randomly divided into five equal sized sets, called folds. One fold was separated for testing while the remaining four folds were used as training data. This procedure was repeated five times, each time with a different fold selected for testing. Part of the training set was used for validation. Thus, each round (or iteration) of the cross validation procedure was carried out on training, validation, and testing sets comprising 60%, 20% and 20% of the available images, respectively. To reduce the risk of overfitting, we tuned the learning rate and the number of epochs upon the validation set. The weights of the ResNet backbone were initialized with values pre-trained at ImageNet, a procedure known as transfer learning.The Adam optimizer was used for training all object-detection methods. We set the learning rate to The performance of each method is reported in the next section by precision–recall curves and the average precision (AP) ,37. To eThe average precision is given by the area under the precision–recall curve.This section presents the results collected in our experiments in three ways. The average precision  of the detection methods in each cross validation round is shown in The methods were able to detect cumbaru trees even on images captured under different lighting and scale conditions, as shown in The UAV flight height directly influences the scale of a tree image. Generally, all tested methods were able to handle different scales and flight heights in the range represented in the dataset. The models were trained and tested on a desktop computer with an Intel(R) Xeon(R) CPU E3-1270@3.80GHz, 64 GB memory, and NVIDIA Titan V graphics card (5120 Compute Unified Device Architecture (CUDA) cores and 12 GB graphics memory). The detection algorithms were coded using Keras-Tensorflow  on the UAs expected, the Faster-RCNN variant had the highest computational cost, because it comprises two sequential stages, the first one to propose regions, followed by the second one that classifies the proposed regions. YOLOv3 and RetinaNet were approximately 6.3 and 2.5 times faster than Faster-RCNN, respectively, mainly because they handle object detection as a regression problem.The results in In this work, we proposed and evaluated an approach for the detection of tree species based on CNN and high resolution images captured by RGB cameras in an UAV platform. Three state-of-the-art CNN-based methods for object detection were tested: Faster R-CNN, YOLOv3 and RetinaNet. In the experiments carried out on a dataset comprising 392 images, RetinaNet achieved the most accurate results, having delivered 92.64% average precision. Regarding computational cost, YOLOv3 was faster than its counterparts. Faster RCNN was the least accurate and at the same time the most computationally demanding among the assessed detection methods.The experimental results indicate that RGB cameras attached to UAVs and CNN-based detection algorithms constitute a promising approach towards the development of operational tools for population estimates of tree species, as well for demography monitoring, which is fundamental to integrate economic development and nature conservation. Future works will investigate the application of the proposed techniques considering other tree species. Real-time tree detection using embedded devices will also be investigated.


The resulting cellulose networks exhibit superhydrophilicity and underwater superoleophobicity and they are mechanically reinforced. Therefore, the described treatment makes cellulose fiber networks excellent candidates for the filtration and subsequent removal of oil from oil-in-water non-stabilized emulsions with oil separation efficiency up to 99%. The good selectivity, reproducibility, and cost effectiveness of the preparation process leads to the production of low cost filters that can be used in oil–water separation applications.The separation of oil from water in emulsions is a great environmental challenge, since oily wastewater is industrially produced. Here, we demonstrate a highly efficient method to separate oil from water in non-stabilized emulsions, using functionalized cellulose fiber networks. This is achieved by the modification of the wetting properties of the fibers, transforming them from oil- and water-absorbing to water-absorbing and oil-proof. In particular, two diverse layers of polymeric coatings, paraffin wax and poly(dimethylsiloxane)- As a Cellulose networks are porous, micro-textured materials ,16, withb-poly(ethylene oxide) (PDMS-b-PEO) diblock copolymer. The PFW treatment makes the FP hydrophobic and oleophilic. The subsequent application of PDMS-b-PEO offers the final desired properties to the FP, transforming it into a superhydrophilic and underwater superoleophobic porous material, able to separate oil from oil-in-water non-stabilized emulsions efficiently. In contrast to traditional separation processes, such as ultrafiltration membranes, where the applied driven-pressure for emulsion separation is hundreds of kPas, the proposed method demands much less energy in order to separate water from oil effectively. In fact, the separation process is gravity-driven . As . As 8]. b-PEO treatment. The SEM and TEM analysis revealed that the morphology of the filter paper is not altered significantly while the mechanical properties of the system are improved. The superhydrophilic and underwater superoleophobic filter paper possesses excellent oil–water separation efficiency up to 99% and a rate of about 77 L·m−2·d−1. As such, the treatment presented here can be easily industrialized due to fact that both the substrate (cellulose) and polymers used are abundant and produced at industrial scales.In conclusion, we present a novel method to modify the surface properties of filter paper using polymeric solutions, rendering them superhydrophilic and underwater superoleophobic in a simple, straightforward and cost effective way. Various oils such as mineral oil, olive oil, and vegetable oil can be efficiently separated from their water emulsions based on the gravity-driven separation process. The filter paper becomes superhydrophilic and also exhibits underwater superoleophobic properties after PFW/PDMS-