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BAS-011 IBM SPSS Statistics Level 1 v2

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BAS-011 exam Dumps Source : IBM SPSS Statistics Level 1 v2

Test Code : BAS-011
Test Name : IBM SPSS Statistics Level 1 v2
Vendor Name : IBM
: 55 Real Questions

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IBM IBM SPSS Statistics Level

IBM to stop helping SPSS statistics part on IBM i | killexams.com Real Questions and Pass4sure dumps

IBM ultimate week introduced that the version 22 free up of SPSS information should be the remaining release of the product to have any element that runs on equipment i (IBM i). it's going to even be the final unencumber with the capacity to pull SQL records out of the DB2 for i database, which is arguably extra destructive for any IBM purchasers that might need to run some statistical evaluation on their DB2/400 facts.

SPSS facts is mature and multi-faceted software equipment that gives users lots of superior statistical analysis capabilities. Surrounding the core evaluation part is a fleet of more than 50 add-on items that, amongst different things, provide record distribution capabilities.

SPSS information has not ever run on IBM i itself, even when it turned into owned via SPSS. before it become bought with the aid of IBM, SPSS supported the IBM i platform with simply two main product strains: the exhibit OLAP and Reporting tools (a few of which had been acquired through assist/methods) and the Clementine facts mining application. but the core SPSS facts kit become always supported on extra “mainstream” platforms, like Unix, Linux, home windows, and the S/390 mainframe, which is where SPSS data acquired its delivery so decades in the past.

besides the fact that children, IBM did, interestingly, aid the SPSS Collaboration and Deployment features part on the IBM i platform, which is enjoyable in its own right. IBM infrequently (if ever) touted this skill, which isn't excellent because it’s a narrowly focused area of interest product that performs a aid position to different items. In any adventure, IBM announced that the Collaboration and Deployment functions part in SPSS information edition 22 will not help the “device I” (a reputation that IBM stopped using in 2010).

possibly more harmful is the undeniable fact that SPSS facts version 22 marks the final edition of the application that could be capable of use DB2 for i (DB2/four hundred) as a source for SQL information, even if the core SPSS facts application is working (because it ought to) on yet another server platform.

IBM i authorities are aware of moving creation records from DB2/four hundred onto other structures the place it will also be analyzed. but, curiously so few SPSS facts clients have been the usage of this capability that it not made sense to keep it.

surely there are alternative routes to get facts off the IBM i server and into SPSS records. in spite of everything, the SQL information normal is supposed to bring greater statistics interoperability among systems. but the incontrovertible fact that it’s no longer worth IBM’s effort to retain this SQL channel open to the IBM i server is not a great signal.

For more assistance see utility Announcement 213-309.

linked experiences

There’s No “i” In French Open Tennis

support/methods Buys show off BI items from IBM

IBM to purchase SPSS for $1.2 Billion

SPSS alterations statistics Miner’s identify, Drops equipment i assist

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IBM sends Cognos, SPSS to the cloud | killexams.com Real Questions and Pass4sure dumps

Two of IBM’s most time-honored analysis products, the Cognos enterprise Intelligence and the SPSS predictive analytics equipment, are headed for the cloud, the newest in an ongoing push with the aid of IBM to port its massive utility portfolio to the cloud.

accessing any such utility from a hosted environment, in place of paying for the package outright, gives a couple of benefits to shoppers.

“We control the infrastructure, and this lets you scale greater without difficulty and get begun with much less upfront investment,” observed Eric Sall, IBM vice president of worldwide analytics advertising.

IBM introduced these additions to its cloud capabilities, as well as a number of new offerings, at its insight consumer convention for facts analytics, held this week in Las Vegas.

by way of 2016, 25 % of recent business analysis deployments might be finished in the cloud, in response to Gartner.

Analytics may assist corporations in lots of methods, according to IBM. It may supply extra insight within the paying for habits of clients, in addition to insight into how smartly its personal operations are performing. It may assist protect programs from assaults and makes an attempt at fraud, in addition to assure that company departments are assembly compliance necessities.

the new on-line edition of Cognos, IBM Cognos company Intelligence on Cloud, can at present be established in a preview mode. IBM plans to present Cognos as a full commercial carrier early subsequent yr. users can run Cognos in opposition t data they keep within the IBM cloud, or against statistics they shop on premises.

A full commercial edition of the on-line IBM SPSS Modeler could be available inside 30 days. This package will consist of all of the SPSS accessories for statistics primarily based predictive modeling, equivalent to a modeler server, analytics decision management software and a information server.

earlier this year, IBM pledged to offer an awful lot of its utility portfolio as cloud features, many through its Bluemix set of platform services.

apart from Cognos and SPSS, IBM additionally unveiled a few new and up to date offerings on the convention.

One new carrier, DataWorks, provides a number of techniques for refining and cleansing records so it is competent for evaluation. The enterprise has launched a cloud-based mostly information warehousing carrier, referred to as dashDB. a new Watson-based provider, known as Watson Explorer, provides a way for clients to ask herbal language questions on varied units of inside records.

To comment on this article and other PCWorld content, seek advice from their fb page or their Twitter feed.

IBM Improves IT Operations with synthetic Intelligence | killexams.com Real Questions and Pass4sure dumps

artificial Intelligence in IT today

Many IT departments have applied software options that go past simple transaction and analytical processing. These programs contain fashions that describe certain information behaviors, and these models devour present information to peer if these patterns of facts habits exist. in that case, operational programs can use this suggestions to make decisions. a pretty good example of here is fraud detection. IT statistics engineers use analytics on historical statistics to verify when fraud occurred, code this right into a model, and install the mannequin as a provider. Then, any operational equipment can invoke the model, circulate it present data and receive a mannequin “ranking” that represents the likelihood that a transaction may well be fraudulent.

The universal term for these new programs is artificial intelligence (AI). They encompass a mix of search, optimization and analytics algorithms, statistical evaluation thoughts and template methods for ingesting information, executing these strategies and making the effects obtainable as features known as models. The subset of AI that deals with model creation and implementation is sometimes known as desktop getting to know (ML).

laptop getting to know and artificial Intelligence

IT departments implement ML and AI solutions in the broader context of their facts and processing footprint. here's always depicted as the following four-layer hierarchy.

Layer 1: The data.

this residue consists of the information allotted across the commercial enterprise. It contains mainframe and distributed records similar to product and sales databases, transactional information and analytical records in the data warehouse and any massive statistics applications. It also may additionally consist of customer, supplier and service provider records, most likely at faraway websites, and even extends to public data comparable to twitter, news feeds and survey consequences. an additional possible supply of statistics is server performance logs that consist of aid utilization heritage.

word that these records exist across distinct hardware systems together with on-premises and cloud-based. As such, various facts features can exist in assorted varieties and formats (e.g. text, ASCII, EBCDIC, UTF-8, XML, photographs, audio clips, and many others.). additionally, at this degree will exist hardware and software that manipulate the facts, together with excessive-speed facts loaders, records purge and archive tactics, put up-and-subscribe methods for records replication, as well as those for typical backup and healing and disaster recuperation planning.

Layer 2: The Analytics Engines.

during this layer exist a mixture of hardware and utility that executes company analytics towards the facts layer. There are a few standard gamers in this space. They encompass:

  • The IBM Db2 Analytics Accelerator (IDAA) than can be applied as standalone hardware or completely built-in inside definite z14 servers;
  • Spark on z/OS;
  • Spark Anaconda on z/OS;
  • Spark clusters on distributed structures.
  • just as the facts layer happens across dissimilar hardware systems and allotted websites, so will the analytics engines layer. The important function of this sediment is to deliver an optimized facts entry layer in opposition t the underlying statistics as a provider for AI and operational purposes.

    Layer 3: The laptop learning Platform.

    IT implements computer getting to know application in this layer. It accesses the data through one or more of the analytics engines. it is during this layer that IBM offers its newest providing, Watson machine learning for z/OS (WMLz). WMLz provides a fundamental desktop researching workflow which includes here steps:

  • statistics Ingestion and coaching — Inputting statistics, filling in missing values, encoding category statistics, creating indexes and normalizing numeric values;
  • model building and practising — An interface for the statistics scientist to create a mannequin of records conduct according to historical analytics, coach the mannequin to realize statistics patterns and validate the mannequin;
  • mannequin Deployment — enforce the model as a production technique, together with tactics for updating models in-vicinity and monitoring mannequin results;
  • remarks Loops — strategies that enable automatic mannequin learning through feeding mannequin outcomes lower back into the mannequin training process to replace models or produce new ones.
  • information scientists recognize that one of the most surest benefits of computing device getting to know is to make use of the results in operational programs; as an instance, having an ML mannequin analyze monetary information to investigate the opportunity of fraud. This capability that you will obtain top-quality performance when you installation ML within the hardware ambiance the place transaction processing occurs. for a lot of tremendous organizations this capability the IBM zServer atmosphere.

    Layer four: computing device studying options.

    Now that they have the machine discovering platform available as ML capabilities, they can create combined AI/ML options that invoke those services. IBM has several competent-made solutions for this layer, together with here:

  • Db2 AI for z/OS (Db2ZAI) -- the use of Db2 SMF records for evaluation, Db2ZAI displays and analyzes Db2 operations in a Z/OS environment. it will probably deliver better question entry direction counsel to the Db2 optimizer to raise SQL performance, diagnose Db2 performance abnormalities and suggest corrective action and notice Db2 statistics anomalies and provide efficiency tuning innovations;
  • IBM Z Operations Analytics (IZOA) -- This product analyzes z/OS SMF statistics and detects changes in subsystem use and forecasts changes that could be required in the future, does computerized issue analysis and gives difficulty insights from wide-spread difficulty signatures.
  • Watson laptop discovering on Z

    Let’s take a deeper dive into how Watson computer getting to know on Z (WMLz) works and what features it may provide.

    Key performance warning signs (KPIs). WMLz doesn't inherently recognize what performance factors are important to you. despite the fact, once these KPIs are defined (either by a person or through enforcing one of the most computing device gaining knowledge of solutions referred to above), WMLz can analyze KPI statistics to seek correlations. as an instance, when one KPI (say, I/O towards a essential database) goes up, yet another KPI (say CPU usage) may additionally go up as well. As a different example, a number of KPIs may well be behaviorally similar, so WMLz can cluster them as a gaggle and operate extra analysis throughout organizations. WMLz can additionally assess KPI baseline behaviors in keeping with time-of-day, time zone of transactions or seasonal exercise.

    Anomaly Detection. as soon as correlations are found out, WMLz can look contrary consequences and file them as anomalies. In their I/O illustration above, an anomaly can be suggested if I/O in opposition t a important database elevated however CPU utilization decreased.

    pattern recognition. As with many computer gaining knowledge of engines, WMLz will look for patterns among KPIs and statistics identifiers. as an instance, CPU may also boost when processing definite classes of transactions.

    KPI prediction. An extension of simple KPI processing, WMLz can use the past behaviors of corporations of KPIs to predict the future. agree with their I/O example once once again. The product may additionally realize that definite transactions develop into more a large number of right through a particular time length, and these transactions consume greatly more CPU cycles. The product can also then predict future CPU spikes.

    Batch workload analysis. Many IT stores have a large contingent of batch processing that is tightly scheduled and comprises job and useful resource dependencies. Some jobs ought to wait for his or her predecessors to finished, some use huge shared substances (corresponding to tape drives or specialty hardware) and a few are so resource-intensive that then can not be finished at the equal time. WMLz can analyze the workload records, together with aid utilization, and supply concepts for balancing components or tuning elapsed times.

    MLC charge sample evaluation and value discount. Some IBM utility license fees are billed monthly, and the license amount can also rely upon optimum CPU usage right through peak periods. WMLz can analyze CPU utilization throughout time, search for patterns and make predictions and suggestions for application license cost reduction.

    Watson desktop learning for z/OS — features

    IBM’s Watson desktop gaining knowledge of for z/OS allows IT its alternative of construction environments to enhance fashions together with IBM SPSS Modeler. These environments help information scientists by using notebooks, facts visualization equipment and wizards to pace the development manner. a couple of short-delivery utility templates are additionally included in the toolset for ordinary company necessities such as fraud detection, load approval and IT operational analytics. The latest edition of WMLz (edition 2.1.0) comprises guide for Ubuntu Linux on Z, java APIs, simplified Python equipment administration and several other elements.

    involved readers may still reference the hyperlinks under for more certain technical information.

    # # #

    See all articles via Lockwood Lyon

    REFERENCES

    computing device gaining knowledge of and synthetic Intelligencehttps://en.wikipedia.org/wiki/Machine_learning

    data and AI on IBM Zhttps://www.ibm.com/analytics/z-analytics

    the usage of Anaconda with Spark — Anaconda 2.0 documentationhttps://docs.anaconda.com/anaconda-scale/spark/

    Watson laptop getting to know - Overviewhttps://www.ibm.com/cloud/machine-studying

    Watson desktop discovering - Resourceshttps://www.ibm.com/cloud/laptop-learning/substances


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    IBM SPSS Statistics Level 1 v2

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    Gut microbiota composition and butyrate production in children affected by non-IgE-mediated cow’s milk allergy | killexams.com real questions and Pass4sure dumps

    Study subjects

    From March to September 2014, 52 consecutive children (age range 1–26 months) visiting their tertiary pediatric allergy center for recent occurrence (last 2–4 weeks) of signs or symptoms of suspected non-IgE-mediated CMA, or for follow up visit after 6 months of exclusion diet upon a confirmed diagnosis of non-IgE-mediated CMA were evaluated and invited to participate in a cross sectional study. The exclusion criteria were: use of pre- or probiotic products and/or antibiotics in the previous 4 weeks; history of cow’s milk-induced anaphylaxis and/or other IgE-mediated signs of food allergy; concomitant presence of other food allergies or allergic diseases, eosinophilic disorders of the gastrointestinal tract, chronic systemic diseases, congenital cardiac defects, active tuberculosis, autoimmune diseases, immunodeficiency, chronic inflammatory bowel diseases, celiac disease, cystic fibrosis, metabolic diseases, lactose intolerance, malignancy, chronic pulmonary diseases or malformations of the gastrointestinal tract. Written informed consent was obtained from the parents/guardians of each subject. The diagnosis of non-IgE-mediated CMA was based on clinical history, negative result of skin prick test, and/or negative level of IgE serum-specific anti-cow’s milk proteins, and the results of a double blind placebo-controlled oral food challenge (DBPCFC)33,34. All DBPCFC were performed in a double-blind, placebo-controlled manner in the outpatient clinic on 2 separate days with a 1-week interval. Parents of patients taking antihistamines were advised to withhold these medications for 72 hours before and during the challenge. Randomization and preparation of the challenges were performed by experienced dietitians who were not directly involved in the procedures. In detail, every 20 minutes, increasing doses (0.1, 0.3, 1, 3, 10, 30, and 100 mL) of fresh pasteurized cow’s milk containing 3.5% of fat or an amino acid formula were administered. Full emergency equipment and medications (epinephrine, antihistamines, and steroids) were available. The results were assessed simultaneously by experienced pediatric allergists. Study subjects were scored for 9 items divided into 4 main categories on a 0 to 3-point scale (0, none; 1, light; 2, moderate; and 3, severe): (1) general (decreased blood pressure plus tachycardia); (2) skin (rash and urticaria/angioedema); (3) gastrointestinal (nausea or repeated vomiting, crampy-like abdominal pain, and diarrhea); and (4) respiratory (sneezing or itching, nasal congestion or rhinorrhea, and stridor deriving from upper airway obstruction or wheezing). If at least 2 of the 3 physicians independently scored one item at level 3 or 2 (or more) items at level 2, the test result was considered positive. Children were observed for up to 4 hours after the final dose and then discharged. In case of a positive DBPCFC result at any testing dose, the patient remained under observation until symptom resolution. If the patient did not show any symptoms within the first 24 hours, parents were advised to provide a single feed of 100 mL of the tested formula (verum or placebo) every day at home for 7 days. If any symptoms occurred during this period, the patients returned to the outpatient clinic on the same day. After 7 days of verum or placebo administration, the patients were examined, and the parents were interviewed at the center. Parents were asked to contact the center if any symptoms occurred in the 7 days after the DBPCFC procedures to rule out false-negative challenge results. The challenge result was considered negative if the patient tolerated the entire challenge, including the observation period. Fifty-two CMA patients were evaluated. Four patients were excluded because of the presence of exclusion criteria, and 2 were excluded for the lack of informed consent. Therefore, 46 CMA patients were included in this study. According to disease state and dietary treatment, CMA patients were divided in three groups: group 1 included patients with non-IgE-mediated CMA at diagnosis, before any therapeutic intervention and receiving standard formula (n = 23); group 2 (n = 9) included patients with diagnosis of non-IgE-mediated CMA after treatment for 6 months with an extensively hydrolyzed casein formula (EHCF; Nutramigen, Mead Johnson Nutrition, Evansville IN, US); group 3 (n = 14) included patients with diagnosis of non-IgE-mediated CMA after treatment for 6 months with EHCF added with the probiotic L. rhamnosus GG (EHCF + LGG; Nutramigen LGG, Mead Johnson Nutrition, Evansville IN, US). The specific formula use was prescribed and adherence was checked according to the standard procedure adopted at their Center. Briefly, the parents received written instructions regarding the commercial name of the product and the formula preparation procedure. Then, the adherence to the treatment was checked monthly during the first 3 months of treatment and then every 6 months. Formula use was evaluated at each time visit by dietitians, counseling parents about issues that could arise during the elimination diet and on how to reach the daily recommended intake for Italian children. This allowed the study staff to evaluate compliance with the formula and to ensure that the patients received an appropriate quantity of formula to meet their nutritional requirements. During the same study period, consecutive healthy children (group 4, n = 23), with negative clinical history for any allergic condition visiting their center because of minimal surgical procedures or vaccination program were also enrolled. Anamnestic, demographic, anthropometric and clinical data were obtained from the parents of each subject and recorded in a clinical database. The 3-day dietary diary was collected from all study subjects at enrolment. All diaries were assessed using a specific software (Winfood, Medimatica srl, Colonnella, Teramo, Italy). For all study subjects, a stool sample (3 g) was collected to evaluate gut microbiota composition and fecal butyrate concentration and stored at −80 °C until analyses.

    Ethics

    The study was approved by the Ethics Committee of the University of Naples Federico II and was registered in the Clinical Trials Protocol Registration System on March 14, 2014 (https://clinicaltrials.gov - ID number: NCT02087930).

    All methods were performed in accordance with the relevant guidelines and regulations.

    DNA extraction and 16S sequencing

    Fecal samples (about 1 g) were fully homogenized in STE buffer (100 mMNaCl, 10 mMTris-Cl pH 8.0, 1 mM EDTA pH 8.0) and centrifuged (500 × g, 1 min) in order to pellet debris. The supernatant was centrifuged again (12,000 × g, 2 min) and the pellet was used for DNA extraction with the PowerFecal DNA Isolation kit (Mo Bio Laboratories, Inc., Carlsbad, CA). V3-V4 region of the 16S rRNA gene was amplified by using primer and PCR conditions recently described35. PCR products were purified with the Agencourt AMPure XP beads (Beckman Coulter) and quantified using a Plate Reader AF2200 (Eppendorf). Amplicon multiplexing, pooling and sequencing were carried out following the Illumina 16S Metagenomic Sequencing Library Preparation protocol, on a MiSeq platform and using the MiSeq Reagent kit v2, leading to 2 × 250 bp, paired-end reads.

    Fecal butyrate analysis

    One gram of frozen feces was diluted with saline buffer, vortexed and centrifuged (12,000 × g) for 10 min in 2 ml tubes. The supernatant was filtered (0.45 μm) and stored at −20 °C until analysis. Frozen fecal extracts were acidified with 20 μl of 85% (w/v) phosphoric acid and 0.5 ml of ethyl acetate, mixed, centrifuged (12,000 × g) for 1 h, and extracted in duplicate. About 0.5 ml of the pooled extract containing the acidified butyrate was transferred into a 2 ml glass vial and loaded onto an Agilent Technologies (Santa Clara, CA, USA) 7890 gas chromatograph (GC) system with automatic loader/injector. The GC column was an Agilent J&W DB-FFAP (Agilent Technologies) of 30 m, internal diameter 0.25 mm and film thickness 0.25 μm. The GC was programmed to achieve the following run parameters: initial temperature 90 °C, hold 0.5 min, ramp of 20 °C min−1 up to a final temperature of 190 °C, total run time 8.0 min, gas flow 7.7 ml min−1 split less to maintain 3.26 p.s.i. column head pressure, septum purge 2.0 ml min−1. Detection was achieved using a flame ionization detector. Peaks were identified using a mixed external standard and quantified by peak height/internal standard ratio.

    Statistical and bioinformatics analysis

    All data were collected in a dedicated database and analysed by a statisticianwith IBM SPSS Statistics version 19.0 for Windows (SPSS Inc, Chicago, IL). The χ2 test and Fisher’s exact test were used for categorical variables. The level of significance for all statistical tests was 2-sided, P < 0.05.

    Raw sequence quality filtering and pre-processing was carried out as recently reported35. Briefly, demultiplexed, forward and reverse reads were joined by using FLASH36. Joined reads were quality trimmed (Phred score < 20) and short reads (<250 bp) were discarded by using Prinseq37. High quality reads were then imported in QIIME38. OTUs were picked through de novo approach and uclust method and taxonomic assignment was obtained by using the RDP classifier and the Greengenes database39, following a pipeline previously reported35. In order to avoid biases deriving from different sequencing depth, OTU tables were rarefied to the lowest number of sequences per sample. Statistical analyses and visualization were carried out in R environment (https://www.r-project.org).

    To discriminate the microbial profiles as a function of disease, a model based on projection on latent structures (PLS) in its discriminant (DA) version was built, based on the normalized abundance (log10) of the microbial genera identified. The R package mixOmics was used. Permutational Multivariate Analysis of Variance (non-parametric (PER)MANOVA) based on Jaccard and Bray Curtis distance matrices was applied with 999 permutations to detect significant differences in the overall microbial community composition, by using the adonis function in vegan package. Non-parametric Kruskal-Wallis and pairwise Wilcoxon tests were carried out in order to find OTUs differentially abundant between the groups. A Generalized Linear Model (R function glm) was built in order to test the importance of continuous or discrete variables available for the subjects (mode of birth, age at weaning, age at sampling, sex, months of exclusive breastfeeding, average daily consumption of proteins and fat, health status – that is, healthy or CMA) on the relative abundance of bacterial genera significantly different between healthy and CMA subjects. Spearman’s pairwise correlations were computed between OTUs or oligotypes and short-chain fatty acid abundance (corr.test function in psych package). Correction of p-values for multiple testing was performed40. Differences in fecal butyrate levels between the groups were evaluated by non-parametric Kruskal-Wallis and pairwise Wilcoxon tests. In order to compare the gut microbiota composition in children with non-IgE (analyzed in the present study) and IgE-mediated CMA from their previous study15, quality filtered reads of the previous study were downloaded from MG-RAST. Since the reads from the previous study included only V4 region of the 16S rRNAgene, they were aligned to those produced in this study, that were trimmed in 5′direction to the same length. Reads from both the studies were re-analysed as described above.

    Sub-genus diversity of Bacteroides

    Reads assigned to Bacteroides genus were extracted and entropy analysis and oligotyping41 were carried out as described previously42. After the initial round of oligotyping, high entropy positions were chosen (−C option): 2, 30, 94, 104, 106, 107, 109, 114, 302, 380. To minimize the impact of sequencing errors, they required an oligotype to be represented by at least 100 reads (−M option). Moreover, rare oligotypes present in less than 10 samples were discarded (−s option). These parameters led 70,142 sequences left in the dataset. BLASTn was used to query the representative sequences against the NCBI nr database, and the top hit was considered for taxonomic assignment. Statistical analyses and visualization were carried out in R environment as described above.

    Data availability

    The 16S rRNA gene sequences produced in this study are available at the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI), under accession number SRP092171.


    Salvianolic acid B plays an anti-obesity role in high fat diet-induced obese mice by regulating the expression of mRNA, circRNA, and lncRNA | killexams.com real questions and Pass4sure dumps

    Introduction

    Obesity has become a worldwide problem and a major risk factor for diabetes, infertility, and cardiovascular disease (Hu et al., 2016; Liang et al., 2017; Ferramosca et al., 2016; Supriya et al., 2018). It is a chronic metabolic disease characterized by abnormal fat distribution or excessive lipid accumulation (Yang et al., 2012). White adipose tissue (WAT), the central metabolic organ that regulates the energy homeostasis of the body (Choe et al., 2016), is closely associated with the occurrence of obesity and related complications (Hajer, Van Haeften & Visseren, 2008).

    Noncoding RNA (ncRNA) is a general term for all functional RNAs that are not translated into proteins. As biological mediators, they can participate in the regulation of gene expression through epigenetic modification, transcriptional regulation and post-transcriptional regulation (Tang, Chen & Zhou, 2018). With the development of sequencing technology, a variety of new non-coding RNAs have been discovered, and their role in gene regulatory networks and regulation of endothelial cell function and metabolism is becoming better understood (Santulli, 2015, 2016; Liu et al., 2018). Among them, circular RNA (circRNA) and long non-coding RNA (lncRNA) play roles in regulating beta cell function, influencing transformation of adipose tissue and its energy metabolism and making them a promising target for anti-obesity therapy (Kaur, Mirza & Pociot, 2018; Li et al., 2018; Zhu et al., 2019).

    Salvianolic acid B (Sal B) is a water-soluble component extracted from the traditional Chinese medicinal plant Salvia miltiorrhiza (Family Labiatae; referred to herein as S. miltiorrhiza) (Wang et al., 2014). In recent years, studies have shown that Sal B can reduce obesity and obesity-related metabolic disorders (Chien et al., 2016; Pan et al., 2018). Their work has shown that Sal B can improve glycolipid metabolism and reduce body weight in obese mice induced by high fat diet (HFD) (Zhao et al., 2017). However, it is not known whether anti-obesity activity of Sal B is related to the regulation of non-coding RNA expression. In this study, they aimed to investigate the effect of Sal B on the expression of lncRNA and circRNA in epididymis white adipose tissue (EP) of obese mice induced by a HFD. The anti-obesity target of Sal B was screened using functional studies of differentially expressed lncRNA and mRNA.

    Materials and Methods Ethics statement

    All the study protocol was approved by the Animal Care and Management Committee of the Beijing University of Chinese Medicine, and all animal manipulations were according to the guidelines of the Animal Care Committee.

    Mice experiment and tissue extraction

    Male C57BL/6J mice provided by SPF (Beijing) Biotechnology Co. Ltd. (Certificate NO. SCXK (Jing) 2016-0002) were used in this study. After 1-week acclimation, the mice were fed a HFD (60% fat) for 12 weeks to induce obesity (average body weight: HFD > (1 + 20%) normal, n = 10). After that, obesity mice were randomly divided into EP-S and EP-M groups (n = 5). Sal B intervention group (EP-S) and model (EP-M) groups were respectively administered Sal B (75 mg/kg body weight/day) or vehicle (an equivalent volume of water) by oral gavage daily for 8 weeks. At the end of the study, blood samples and EPs were collected from all the mice sacrificed by cervical dislocation, and immediately frozen in liquid nitrogen and stored at −80 °C for subsequent analysis.

    Measurement of blood lipid profiles and body fat mass

    The concentrations of serum total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL) were determined using chemistry reagent kits (Nanjing Jiancheng Biology Engineering Institute, Nanjing, China) and an automated biochemical analyzer (Hitachi, Tokyo, Japan). Body composition and total fat mass was measured by magnetic resonance imaging (EchoMRI-100 for mice; Echo Medical System, Houston, TX, USA) after the Sal B administration (weeks 8).

    RNA isolation and RNA-seq analysis

    Total RNAs from tissues were extracted using the Trizol reagent and purified using RiboZero Magnetic Gold Kit according to the manufacturer’s instructions. RNA sequencing libraries were generated using the KAPA Stranded RNA-Seq Library Prep Kit. The constructed cDNA libraries were qualified by Agilent 2100 Bioanalyzer, quantified by qPCR, and sequenced on an Illumina Hiseq 4000.

    Functional enrichment analysis

    Using Gene Ontology (GO) database (http://www.geneontology.org). They analysis the GO enrichment of the differentially expressed mRNAs and their functions, based on three aspects: biological processes (BP), cellular components (CC), and molecular functions (MF). The log 10 values (p-value) denote enrichment scores and represent the significance of the GO term enrichment among the differentially expressed genes. KEGG pathway analysis revealed pathway clusters covering the differentially expressed genes, and the log 10 values (p-value) denote the enrichment score and represent the significance of the pathway correlations. In addition, Gene Set Enrichment Analysis (GSEA) is used to compensate for the shortcomings of individual genes in analysis.

    Correlation and co-expression analysis of mRNA and lncRNA

    Based on the inter-regulatory association between differentially expressed genes in the EP between Sal B treatment group and obesity group, the lncRNA–mRNA regulatory network was constructed using Cytoscape v2.8.2 software (http://www.cytoscape.org/).

    Quantitative real time-PCR

    Quantitative real time (qRT)-PCR was performed to verify the results of RNA-seq. Total RNAs were isolated from samples using the Trizol reagent, then reverse-transcribed into cDNA according to the manufacturers’ instruction. The transcriptase reactions contained 1.5 μg RNA, 0.5 μg/μl random primers (N9, 1 μl), 2.5 mM dNTPs mix (1.6 μl), 5× first-strand buffer (4.0 μl), 0.1M dithiothreitol (1 μl), RNase inhibitor (0.3 μl), and Superscript III RT (0.2 μl). Sybr Green-based qPCR was performed using SYBR Premix ExTaq. All data were normalized to data for ARBP to calculate relative mRNA concentrations. The primers used in this study are shown in Table 1.

    Table 1:

    Primers for quantitative PCR analysis.

    Gene Forward (5′–3′) ARBP F: TTTGGGCATCACCACGAAAAR: GGACACCCTCCAGAATTTTC Wbscr27 F: TGAGCTCTTAAGAGTCACCAAGR: CTTGTTCTGATGTTGCATGCTC Sfrp5 F: CAAGATGCGCATTAAGGAGATCR: CTTGAGCAGCTTCTTCTTC Adig F: TCACACTCTCTTTGGTTTTR: CCAGTTGAAGCACAAATCTGAA chr7:67264864–67268400- F: AGACCTCACGGTGCCAAATR: CTTTCTTTCTTAACGTCCACAGG Saa3 F: CAGTTCATGAAAGAAGCTGGTCR: CGAGCATGGAAGTATTTGTCTG ENSMUST00000169194 F: GGCAGGCATGACTAAATG 3R: CAGGGTTGATTAGCAGTGTC Statistical analysis

    The statistical differences were analyzed using the SPSS (version 20.0; IBM SPSS Statistics, Chicago, IL, USA) by independent-samples t-test. All data were shown as the means ± SD. p-values < 0.05 were regarded as statistically significant.

    Results Effects of Sal B on body fat mass and serum lipid profiles of obese mice induced by HFD

    After 8 weeks of Sal B intervention, the body weights, TG, TC, HDL, LDL, and body fat mass of experimental mice in the two groups were measured. The body weight, TG, TC, HDL, LDL, and body fat mass in the obesity group was significantly higher than that in Sal B treatment group (p < 0.05) (Table 2). These results indicate that Sal B can reduce the body weight and fat mass as well as prevent dyslipidemia caused by HFD feeding.

    Table 2:

    Effects of Sal B on body fat mass and serum lipid profiles of obese mice induced by HFD.

    Name Obesity model group Sal B treatment group TG 0.984 ± 0.106 0.777 ± 0.069* TC 6.229 ± 0.483 5.011 ± 0.391* LDL-C 0.425 ± 0.021 0.317 ± 0.029* HDL-C 1.213 ± 0.191 1.876 ± 0.105* Fat mass 0.431 ± 0.011 0.356 ± 0.015* Effects of Sal B on mRNAs and circRNAs expression in EP of obese mice induced by HFD

    In total, 15,184 mRNAs were identified, of which 132 differentially expressed (DEmRNAs). In the EP-S group, 24 were up-regulated and 108 were down-regulated (Figs. 1A and 1C; Table S1). Compared with EP-M, there were 19 differentially expressed circRNAs in the EP-S, of which nine were up-regulated and 10 were down-regulated (Figs. 1B and 1D; Table S2). Among DEmRNAs, the up-regulated expression of Wbscr27 was the highest, with a fold change of 2.053, while C1rb was the most down-regulated, with a fold change of 0.318. In addition, some mRNAs that have been shown to play a role in fat metabolism, such as Sfrp5, Adig, and Saa3 were also differentially expressed.

    Figure 1: Analysis of DEmRNAs (A, C) and DEcircRNAs (B, D). Hierarchical clustering. Each row represents an mRNA and each column represents a sample. Green and red represent down-and up-regulated mRNAs or circRNAs, respectively. Genes in the volcano-Plot above the green parallel line (p < 0.05) and outside the two longitudinal green lines indicated DEmRNAs and DEcircRNAs between the two compared samples. Effects of Sal B on the expression and function of lncRNAs in EP induced by HFD in obese mice

    We found 234 differentially expressed lncRNAs (DE lncRNAs), including 87 up-regulated and 147 down-regulated in the experimental group (Table S3). Based on this, they performed a GSEA functional analysis of the DElncRNAs, and found that the up-regulated expression of lncRNAs are mainly involved in brown adipocyte differentiation, steroid biosynthesis, lipid transport, and lipid metabolism, while the down-regulated expression of lncRNAs are associated with the immune process and inflammatory responses (Fig. 2). After classifying the DElncRNAs, 179 were found to be exon sense overlapping, 11 were intergenic, 17 were intron sense overlapping, 16 were antisense, and 11 were bidirectional.

    Figure 2: GSEA Cluster Heat Map of top 10 DElncRNAs, in up-regulation and down-regulation, respectively. (A) Biological process; (B) cellular components; (C) molecular functions, and (D) KEGG pathway, each row represents a functional entry, and each column represents an lncRNA. GSEA is a method used to determine whether a given gene set has significant differences among different groups. Genes in these sets have some degree of correlation. Therefore, enrichment analysis of gene sets can make up for the shortcomings of single gene in the analysis. qRT-PCR validation of differentially expressed mRNAs, lncRNAs, and circRNAs

    We selected four DEmRNAs (Wbscr27, Sfrp5, Adig, and Saa3), DEcircRNAs- chr7:67264864–67268400:- and DElncRNA-ENSMUST00000169194, which are most relevant to obesity, for use in verifying RNA-seq results using qRT-PCR. Results showed that the expression levels of Wbscr27, Sfrp5, Adig, and chr7:67264864–67268400:- were up-regulated in the EP-S group compared with the EP-M group, consistent with the sequencing results. The expressions of ENSMUST00000169194 and Saa3 were down-regulated in the EP-S group, which was also consistent with the sequencing results (Fig. 3).

    Figure 3: Sequencing and quantitative PCR. Sequencing and quantitative PCR for mRNAs (Wbscr27, Sfrp5, Adig, and Saa3), circRNAs- chr7:67264864–67268400:- and lncRNA-ENSMUST00000169194. The quantitative PCR results were consistent with the sequencing data. n = 5. LncRNA–mRNA regulatory analysis

    LncRNA has the ability to regulate several groups of mRNAs at the transcriptional level, including positive and negative regulation. Hence, understanding how Sal B alters the expression of lncRNA and its target mRNA expression is key to understanding its molecular mechanism of anti-obesity. They screened two DElncRNAs (ENSMUST0000140351 and ENSMUST00000169194) to construct the lncRNA–mRNA regulatory network map. A total of 11 differentially expressed mRNAs were found to be negatively correlated with the expression of ENSMUST0000140351 (Ms4a14, Cd300ld3, Lum, Glipr1, Cd300ld5, Rgs18, Cd300ld4, Fgd4, Hpgds, Frmd4b, and Osbpl8). They also found that the expressions of S100a8 and Fgl2 were positively correlated with the expression of ENSMUST00000169194 (Fig. 4; Table S4).

    Figure 4: LncRNA–mRNA regulatory network (ENSMUST0000140351 and ENSMUST00000169194). Squares represent lncRNAs, circles represent mRNAs; red indicates up-regulated expression and blue indicates down-regulated expression. The solid line is positively correlated and the dotted line is negatively correlated. LncRNA–mRNA regulatory network was constructed using Cytoscape v2.8.2 software. Functional analysis of DEmRNAs

    We performed GO and KEGG enrichment analysis to determine the functional significance of DEmRNAs in the EP-S/EP-M group. GO enrichment analysis showed that up-regulated mRNA was enriched in 13 BP, 5 CC, and 2 MF, while down-regulated mRNA was enriched in 89 BP, 24 CC, and 35 MF (Fig. 5; Table S5). The most highly enriched up-regulated GO terms were “brown fat cell differentiation (biological process),” “integral component of membrane (CC),” and “ligase activity (MF),” while the most highly enriched down-regulated GO terms were “immune system process (BP),” “extracellular region (CC),” and “chemokine activity (MF).”

    Figure 5: GO analysis. (A) up-regulated and (B) down-regulated of DEmRNAs. Using GO database (http://www.geneontology.org) analysis the GO enrichment of the DEmRNAs, based on three aspects: biological processes (BP), cellular components (CC), and molecular functions (MF). The log 10 values (p-value) denote enrichment scores and represent the significance of the GO term enrichment among the DEmRNAs.

    KEGG pathway analysis showed that differentially expressed mRNAs were enriched in 14 pathways associated with obesity (p < 0.05). The most highly enriched pathways were “insulin resistance” and “IL-17 signaling pathway.” Notably, they also identified mRNAs involved in the regulation of these pathways, which may provide targets for Sal B as a potential drug to prevent HFD-induced obesity (Table 3). Moreover, a number of metabolic-related pathways were screened, including the “NF-κB signaling pathway” and the “B-cell receptor signaling pathway.” KEGG pathway analysis suggests the possibility that Sal B exerts its weight reduction effect through the regulation of adipose metabolism via insulin resistance and IL-17 signaling in HFD induced-obesity mice.

    Table 3:

    KEGG pathway analysis.

    ID Term Count Genes mmu04931 Insulin resistance 2 Slc27a1, Slc2a4 mmu04657 IL-17 signaling pathway 6 Ccl12, Ccl7, Cxcl1, Fosl1, S100a8, S100a9 mmu04145 Phagosome 7 Atp6v0d2, Comp, Cybb, Fcgr1, Fcgr4, Msr1, Rab7b mmu05323 Rheumatoid arthritis 5 Atp6v0d2, Ccl12, Ccl3, Cd86, Il18 mmu04064 NF-kappa B signaling pathway 5 Bcl2a1a, Bcl2a1b, Bcl2a1d, Btk, Card11 mmu04380 Osteoclast differentiation 5 Btk, Fcgr1, Fcgr4, Fosl1, Lilra5 mmu04662 B cell receptor signaling pathway 4 Btk, Card11, Cd72, Rasgrp3 mmu04620 Toll-like receptor signaling pathway 4 Ccl3, Cd86, Tlr1, Tlr8 mmu04060 Cytokine-cytokine receptor interaction 6 Ccl12, Ccl3, Ccl7, Cxcl1, Cxcl16, Il18 mmu04062 Chemokine signaling pathway 5 Ccl12, Ccl3, Ccl7, Cxcl1, Cxcl16 mmu04621 NOD-like receptor signaling pathway 4 Ccl12, Cxcl1, Cybb, Il18 mmu04668 TNF signaling pathway 3 Ccl12, Cxcl1, Gm5431 mmu04210 Apoptosis 3 Bcl2a1a, Bcl2a1b, Bcl2a1d mmu04933 AGE–RAGE signaling pathway 2 Ccl12, Cybb Discussion

    Epigenetic alteration refers to a heritable change in gene expression under conditions in which the genomic DNA sequence does not change, resulting in an altered phenotype. This includes changes in the expression of non-coding RNA (Takada, Kouzmenko & Kato, 2009). Studies have shown that epigenetic modification plays an important role in the occurrence and development of obesity (Kasinska, Drzewoski & Sliwinska, 2016; Huang et al., 2018). With the advancement of RNA sequencing technology, more and more non-coding RNAs related to energy metabolism are recognized as involved in obesity and related metabolic diseases. WAT is mainly distributed in the subcutaneous tissue, omentum and mesentery of mice, with epididymis white fat (EP) as the most commonly used WAT in adipose studies. They studied the effects of Sal B on the expression of mRNAs, lncRNAs, and circRNAs in EP of HFD induced obesity mice from an epigenetic level, and explored the anti-obesity effect of Sal B.

    Obesity is an inflammatory state that occurs in adipose tissue, and therefore constitutes a chronic inflammatory disease accompanied by activation of inflammatory signaling pathways in adipose tissue cells, release of inflammatory cytokines, and infiltration of immune cells (Nteeba et al., 2013; Mathieu, Lemieux & Després, 2010). Therefore, research on the treatment of obesity inflammation and new target exploitation will provide novel targets for the treatment of obesity and its related metabolic diseases. In the present study, they found that the expression of many inflammation-associated mRNAs was affected by Sal B treatment, including Sfrp5 and Saa3. Secreted frizzled-related protein-5 (Sfrp5), known as an anti-inflammatory adipokine, is much more abundant in adipose tissue than other tissues, and negatively affects obesity and obesity-related metabolic disorders (Hu et al., 2013). Previous studies have shown that in the adipose tissue of Sfrp5 knockout mice, the number of macrophages is significantly increased, and the expression of factors related to cellular inflammatory activity, such as TNF-a and IL-6, are significantly increased (Ouchi et al., 2010). Sfrp5 exerts anti-inflammatory effects by binding to Wnt5a to inhibit the activation of the downstream target JNK of the Wnt pathway and reduce the secretion of inflammatory factors in obese mice (Catalán et al., 2014) as well as in 3T3-L1 cells (Shadid & Jensen, 2003). Consistent with previous research, they found that Sfrp5 is up-regulated 1.9-fold under Sal B treatment. Therefore, they hypothesize that Sal B may exert anti-obesity effects by regulating the expression of inflammation-related mRNA in adipose tissue. In addition, Sfrp5 can be used as a candidate target for studying the anti-obesity mechanism of Sal B, and its specific mechanism should be the emphasis of future research.

    Another inflammation-related mRNA, Saa3, was found to be expressed at half the control rate under Sal B treatment, consistent with previous studies. The serum amyloid A family is a class of proteins released during acute inflammatory response and is closely related to the pathogenesis of chronic inflammatory diseases such as obesity (Van Dielen et al., 2001). The expression of Saa3 is significantly increased under a promoted adipocyte inflammatory response by saturated fatty acids and glucose. In addition, Saa3 is highly expressed in the adipose tissue of obese mice, which may be related to the induction of adipose tissue inflammation (Den Hartigh et al., 2014). In this study, they found that the expression of Saa3 was significantly down-regulated in EP-S, suggesting that Sal B can reduce the inflammatory response induced by Saa3.

    In the EP-M group, they found some abnormal expression of mRNA associated with adipose transformation, with Sal B intervention reversing these changes. Adipoietin (Adig), also known as small adipocytokines 1, plays a significant role in the differentiation of adipocytes (Ren et al., 2016). Their results showed that the expression Adig in the Sal B treatment group was significantly higher than in the obese model group. This is in line with the previous findings that Adig can promote the differentiation of adipocytes by activating the expression of PPARγ, Srebp-1, and Fas genes (Mei, Zhang & Fu, 2016). Therefore, they speculate that Sal B can up-regulate the expression level of Adig to activate the adipose transcription factor and promote the differentiation of adipocytes.

    We identified 234 DElncRNAs, including 87 up-regulations and 147 down-regulations. Several differentially expressed lncRNAs might participate in lipid metabolism and glucose metabolism. For example, Rora and Dnm2 were predicted to be involved in “oxidative phosphorylation” and “glycine, serine, and threonine metabolism.” This is consistent with previous studies showing that Rora regulates lipid metabolism (Kim et al., 2017). Therefore, the differential expression profiles obtained indicate that Sal B can exert a potential regulatory function in fat deposition and metabolism in obese mice by modulating the expression of lncRNAs.

    Gene Ontology and KEGG pathway analyses were performed to predict the possible functions of DEmRNAs. Their results indicated that the up-regulated expression of mRNAs involved in BP is primarily associated with brown adipocyte differentiation (Adig and Slc2a4), lipid metabolic process (Aacs, Fdx1, and Slc27a1), and metabolic process (Aacs and Slc27a1). The down-regulated mRNAs might be related to inflammatory response (Ccl12, Ccl3, Ccl7, Cd180, Cxcl1, Cybb, Il18, Ly86, S100a8, S100a9, Tlr1, and Tlr8). KEGG pathway analysis showed that two DEmRNAs, Slc27a1 and Slc2a4, were involved in the insulin resistance signaling pathway, which is closely related to obesity (Yu, Kim & Lee, 2017). The inflammatory signaling, IL-17 signaling, and NF-kappa B signaling pathways were also subjected to KEGG annotation prediction analysis (Tanti et al., 2012, Tarantino et al., 2014). Their results indicate that Sal B may exert anti-obesity effects by modulating the expression of mRNAs in lipid metabolism and inflammation-related signaling pathways.

    Among all RNAs, circRNAs are the least understood, but appear to have complex regulatory effects in the development of obesity. They identified 9 up-regulated and 10 down-regulated circRNAs under Sal B treatment. Among them, the expression changes of chr14:103252408–103276518:- and chr14:103282597–103291362:- were the most obvious, with an approximate 30-fold upregulation. Therefore, these circRNAs may serve as targets for the design of therapeutic drugs for obesity, pending study of their specific mechanisms.

    Conclusions

    This study is the first comprehensive analysis of mRNA, lncRNA, and circRNA expression in EP of HFD-induced obese mice. They found that Sal B regulates the expression of mRNAs and lncRNAs associated with adipocyte differentiation, lipid metabolism, and inflammation, as well as the insulin resistance and IL-17 signaling pathways. These findings suggest that Sal B plays an important role in inhibiting obesity by regulating anti-inflammatory related factors and signaling pathways. Their research provides valuable insights into the molecular mechanism of Sal B in anti-obesity effects and contributes therapeutic markers for pharmaceutical design in the prevention and treatment of obesity. In the future, the corresponding roles and molecular mechanisms of non-coding RNAs should be further elucidated. In addition, differential expression at the RNA level does not necessarily indicate that the expression of related proteins is also significantly different. They aim to correlate RNA and protein analysis to more fully investigate the anti-obesity mechanism of Sal B.



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    References :


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