Analysis of fecal microbiota using 16s rRNA gene taxonomic profiling revealed that each diet corresponded with a unique gut microbiota. The distribution of taxonomic classes was dynamic over the 6 week feeding period for each of the diets. At the end of the feeding periods, the distribution of taxa included statistically significant increases in members of the phylum Proteobacteria in OS-HA7 fed mice, while the Verrucomicrobia increased in HA7 fed mice over that of mice fed OS-HA7. At the class level, members of the class Bacilli decreased in the OS-HA7 fed group, and Actinobacteria, which includes the genus Bifidobacteria, was enriched in the HA7 fed group compared to the control diet. Behavioral analysis revealed that animals demonstrated profound anxiety-like behavior as observed by performance on the elevated-plus maze with time spent by the mice in the open arm  as well as entries in the open arm . Open-field behavior, a measure of general locomotion and exploration, revealed statistically significant differences between groups in locomotion as a measure of transitions across quadrant boundaries. Additionally, the open-field assay revealed decreased exploration as well as decreased rearing in HA7 and OS-HA7 fed mice demonstrating a consistent pattern of increased anxiety-like behavior among these groups. Critically, behavior was not correlated with weight. These results indicate that diets based on resistant starch can be utilized to produce quantifiable changes in the gut microbiota and should be useful to “dial-in” a specific microbiome that is unique to a particular starch composition. However, undesirable effects can also be associated with resistant starch, including lack of weight gain and increased anxiety-like behaviors. These observations warrant careful consideration when developing diets rich in resistant starch in humans and animal models.The increasing recognition that the gut microbiota plays a central role in behavior and cognition suggests that the manipulation of microbial taxa through diet may provide a means by which behavior may be altered in a reproducible and consistent manner in order to achieve a beneficial outcome for the host. Resistant starch continues to receive attention as a dietary intervention that can benefit the host through mechanisms that include altering the intestinal microbiota. Given the interest in dietary approaches to improve health, the aim of this study was to investigate whether the use of dietary resistant starch in mice to alter the gut microbiota also results in a change in behavior. Forty-eight 6 week-old male Swiss-Webster mice were randomly assigned to 3 treatment groups (n = 16 per group) and fed either a normal corn starch diet (NCS) or diets rich in resistant starches HA7 diet (HA7) or octenyl-succinate HA7 diet (OS-HA7) for 6 week and monitored for weight, behavior and fecal microbiota composition. Animals fed an HA7 diet displayed comparable weight gain over the feeding period to that recorded for NCS-fed animals while OS-HA7 displayed a lower weight gain as compared to either NCS or HA7 animals (ANOVA  Campylobacter jejuni, into mice resulted in the development of anxiety-like behavior in the absence of any detectable immune response [The role of the microbiota in gut-to-brain communication is increasingly being recognized as a major determinant of behavior. Research both in humans and animal models has demonstrated that specific bacterial taxa are associated with and can induce alterations in cognitive states including anxiety and anxiety-like behavior –4. For eresponse , 6. Thisresponse . Other sresponse , 9.The majority of studies to date that have addressed behavior through modulation of the microbiota, also referred to as the microbiota-gut-brain axis, have principally relied on the administration of specific bacteria  or through the complete transfer of the microbiome  . A more et al. [et al. [That dietary manipulations can affect neurological function was recently reported by Borre et al.  who show [et al.  reported [et al. .There continues to be interest in the health benefits of low-digestible carbohydrates have been termed “resistant starch” (RS) . RS contGiven the clear indication that gut bacteria can affect behavior and brain activity and the current interest in RS as a means to improve health, we sought to determine if diets rich in RS induced alterations in the composition of the microbiota that were also associated with changes in behavior. For this, we utilized a combination of culture-independent taxonomic profiling of the gut microbiota coupled with robust behavioral analyses of mice over a 6-week feeding period. The results of this study have implications for development of dietary regimens of RS in both human and animal models.® 5P14, St. Louis, MO, USA). All behavioral testing was done during the light phase (0800–1800 h) with a 24–48 hour rest period between behavioral testing for each group. During the first week, no behavioral testing was performed in order for the mice to habituate to their new surroundings. After the first week, the mice were randomly divided into three groups of 16 (4 cages per group) with each group being fed a specific diet . Within each cage, the diet was contained in a 4 oz feeding jar  with a stainless steel snap on cap with a 2.5 cm hole to allow access to the food. Mice were fed at 0800 daily and monitored for their health except if they were being used in behavioral testing that day, then they were fed at 1800 after the testing period to ensure there was no impact on the behavioral tests. Mice were weighed every other day at 0800 unless they were participating in a behavioral test that day, in which they were weighed after the testing was completed for the day.All experiments were approved by Texas Tech University Health Science Institutional Animal Care and Use Committee prior to initiation of the work. Four-week old male Swiss-Webster mice were obtained from Charles River Laboratories . Upon arrival to the testing facility, mice were randomized, ear tagged and housed in individually ventilated cages  at a density of 4 per cage. The cages were placed on a rack in two horizontal rows aligned next to each other to minimize variations in light and human traffic. All mice had access to food and water throughout the experiment ad libitum. Mice were housed in standard laboratory housing, including a plastic box, food, water bottles, and remained on a 12 hour light/12 hour dark cycle (LabDiet™) and high-amylose corn starch  were purchased from Cargill Inc. . 2-octenyl-1-succinic anhydride and other chemicals were purchased from Sigma-Aldrich Co.  and used without further treatments. Since the objective of this study was to compare the effect of starch resistance in altering both microbiota and behavior we selected the NCS control diet over a standard mouse chow diet. Moreover, a chow diet may contain numerous ingredients not present in the HA7 or octenyl succinic high-amylose (OS-HA7) diets that would have potentially introduced confounding factors in attributing changes in microbiota or behavior to the resistance of the starches. To prepare OS-HA7, HA7 was modified using 10%  OSA following the method of Zhang et al. [et al. [Normal corn starch  and an open field apparatus. Animals were tested on the days immediately prior to sacrifice with each test being performed on a separate day and EPM performed as the first behavioral test. Specifically, two days before sacrifice, mice were tested a single time on the EPM. 24 hours after completion of the EPM, mice were subjected a single time to the open field behavioral assay. The following day, mice were sacrificed. The EPM has been extensively employed to measure anxiety-related behaviors in rodents . The opeThe EPM consisted of a plus shaped apparatus with two arms closed by black Plexiglas walls and two arms left open to test for anxiety-like behavior in mice. The open and closed arms were 35.5cm in length and were elevated 62.5cm above the ground. The test mouse was placed in the center of the EPM facing a closed arm and to ensure that all mice were subjected to the same testing conditions, the same closed arm was used each time. The observer then moved to the corner of the room, out of sight of the test mouse, and manually scored the number of times the mouse groomed. The tracking program recorded the number of entries and time spent in the closed and open arms, which were used to determine changes in anxiety-like behavior among the groups. An entry into the arm was defined as the time when 80% of the mouse’s body was in the arm, which is equivalent to four paws in the arm. Behavioral testing lasted for 10 minutes. Fecal samples were collected at the end of each test by transferring the sample from the testing field into a sterile Eppendorf tube using sterile forceps. The forceps were cleaned with 70% ethanol after every use. The fecal samples were kept in a frozen Eppendorf tube holder in an ice chest until all experiments were finished for the day. They were then transported to a -84°C freezer. The EPM was cleaned with 70% ethanol between each test.The test mouse was placed in the center of the open-field apparatus. The open-field apparatus consisted of a transparent Plexiglas (40.7cm x 40.7cm) box on top of a plastic base that was covered by a solid black plastic sheet. The open field apparatus was virtually divided, using the tracking system, into four equal segments, titled Zone 1 (upper left quadrant), Zone 2 (upper right quadrant), Zone 3 (lower left quadrant), and Zone 4 (lower right quadrant). Behavioral testing was performed for 5 minutes. During this time, the observer, located in the corner of the room, manually scored the number of times the test mouse reared, groomed and defecated. Rearing was defined as the two front paws off the ground while the two hind paws remain on the ground. The tracking program recorded the entries and time spent in each zone as well as the total distance travelled to determine if there were any differences in the locomotor activity levels. The apparatus was cleaned with 70% ethanol between every test and all fecal specimens were removed.Immediately before sacrifice, mice were individually placed into an empty, clean cage and allowed to voluntarily discharge fecal pellets that were promptly collected, stored in an Eppendorf tube, and then frozen in a -20°C frozen block. All samples were transferred into a -84°C freezer for long-term storage until analysis. Although all mice were noted to have produced fecal pellets, only fecal samples from 10 mice demonstrating the most consistent behavioral changes were chosen for microbiota analysis.Mice were anesthetized using isoflurane and remained under anesthesia via a face mask throughout the procedure. Using an electric razor, the hair was shaved off the sides, backs and stomachs of the mice and placed into a vial. Hormonal analysis using hair samples was performed as previously described using a high-pressure liquid chromatography-triple quadrupole mass spectrometry technique which allowed for the simultaneous measurement of all hormones .Prior to genomic DNA isolation, fecal and cecal samples were stored at -80°C. Genomic DNA isolation was performed using the PowerSoil DNA Isolation Kit  on samples from ten mice in each group for each time point as well as cecal contents. The manufacturer’s protocol was followed with the exception that the initial vortex step was extended to 20 minutes to thoroughly homogenize the samples. The purified genomic DNA extracts were quantified using a Qubit 2.0 Fluorometer , and stored at -20°C in 10mM Tris buffer.PCR amplification of the V4 variable region of the 16S rRNA gene using V4 region specific primers (515F-816R) and amplicon sequencing were performed by Institute for Genomics & Systems Biology at the Argonne National Laboratory  on the Illumina MiSeq Platform. The sequences were analyzed using QIIME  . Brieflyp-value <0.05, the Bonferroni test was performed to determine significant differences between NCS and HA7, NCS and OS-HA7 and HA7 and OS-HA7. Statistical significance was set at p <0.05.Initial statistical analysis on behavioral testing, hormone levels and weight loss data was performed using an ANOVA test to determine any significant difference among the three diet groups. Following an ANOVA test with a p<0.0001; NCS:HA7 p = 0.244; HA7:OS-HA7 p<0.0001; NCS:OS-HA7 p<0.0001)  . The effA total of 6,140,396 amplicon reads passed quality filtering and were submitted to closed reference OTU picking at a 97% similarity to the Greengenes database. Reads that failed to match an OTU in Greengenes were removed. 5,204,391 reads corresponded to 3,956 OTUs, with a mean of 43,734±34,742 reads per sample post OTU picking. Of 120 total samples, one sample from the HA7 fed group from week 6 failed to amplify during library preparation.DNA sequences representing fecal samples from weeks 1, 3 and 6 were analyzed by QIIME and the results assessed to detect and compare the overall changes in relative abundance of the distinct taxonomic units found within the samples. The cecal contents were also recovered at the termination of the study and analyzed. As summarized in Bacteroidetes (p = 0.01457) and decreases in Firmicutes and Proteobacteria  over the 6 week period. Interestingly, during the same time the Bacteroidetes and Firmicutes were stable in the RS fed mice as the ratio of their relative abundances did not change significantly. While both RS diets altered the abundance of the Verrucomicrobia, the changes did not follow a single trend throughout the study, providing evidence that the relative abundance of taxa could be restored after initial diet-induced shifts. Specifically, members of the phyla were elevated at week 3 in mice fed HA7 and OS-HA7, which were restored to levels more similar to week 1 by week 6. OS-HA7 also changed the abundances of Actinobacteria  and Spirochaetes .We first observed that over the course of the 6- week study, the taxonomic shifts were dynamic and distinct phyla varied in abundance over time. Phyla with statistically significant changes in abundance  from weeks 1 through 6 were identified . In geneActinobacteria (p = 0.0056) and an increase in Firmicutes (p = 0.0056).Changes at the phylum level were observed in the cecal contents, but were limited to the OS-HA7 fed group (data not shown). Compared to the NCS diet, there were no significant changes in phyla in the HA7-fed group, while the OSHA7-fed group saw a decrease in Bacteroidia increased over from weeks 1 to 6 (p = 0.023), while Bacilli decreased during the same period (p = 0.0031). Consistent with the phylum-level data Actinobacteria increased in week 3 but by week 6 had decreased to levels observed at week 1 (p = 0.31). In the HA7 group, Bacilli and Gammaproteobacteria decreased  from week 1 to week 6 (p = 0.00098), while Betaproteobacteria and Alphaproteobacteria increased over the same time course .We also looked at the class and genus levels to identify members of the microbiota whose abundances changed over the 6 weeks for each diet (data not shown). In the NCS fed control mice, Bacteriodia or Gammaproteobacteria (p = 1.000 for both taxa). Bacilli saw a similar decrease by week 6 that was seen in the other two groups (p = 0.0015). Verrucomicrobia followed a similar trend of increasing by week 3, followed by a decrease by week 6 (p = 0.00015).The OSHA7-fed group remained relatively stable over the six-weeks, with no significant changes in Adlercreutzia (p = 0.018), Prevotela (p = 0.024), and Lactobacillus (p = 0.0045). In animals fed HA7, Bifidobacterium and Sutterella increased in HA7  and Lactobacillus decreased after week 1 .At the genus level, the NCS control diet animals showed an overall decrease in Bacteroidetes in the OS-HA7 group were Bacteroides and an unknown genus in the candidate family S24-7. In week 1, S24-7 was in greater abundance than Bacteroides, but after the first week this ratio was inverted so that Bacteroides was in greater abundance . As observed with the other two diets, Lactobacillus decreased from week 1 to week 6 (p = 0.011).The two dominant members in the phylum p-values  for these comparison are shown in Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Verrucomicrobia showed statistically significant (p< 0.05) changes in abundance in the feces between the treatment groups. Similar changes were observed in the cecum as the Actinobacteria, Bacteroidetes, Firmicutes, and Verrucomicrobia differed significantly.We next identified taxa that showed significant changes when abundance data from each diet were analyzed by pairwise comparisons. The Bacteroidetes and Firmicutes, representing the most prevalent phyla found in all diet groups, differed more substantially between mice fed control (NCS) and either HA7 or OS-HA7 than between mice fed the RS diets. Also, changes to the phyla occurred in week 1 indicating a near immediate impact of the diets on these major taxonomic groups.To more specifically identify how the diets affect the changes in taxa, pairwise comparisons between each of the diet groups were performed at each time point using Wilcoxon rank sum tests. As shown in Bacteroidetes (p = 0.02879) and the Firmicutes (p = 0.01655) between the NCS and HA7 diets , while OS-HA7 promoted a decrease in the same phylum when compared to the other two groups beginning at week 3. The OS-HA7 diet also presided over a decrease in Verrucomicrobia by week 6 (p = 0.00342 vs. HA7). Both RS diets promoted an increase in the Proteobacteria compared to the control diet group after week 1, but the changes in abundance were not significantly different between the two RS diets.Each diet also uniquely impacted other phyla, but these changes took longer to manifest. Members of the Firmicutes and Bacteroidetes, the Firmicutes dominated in the cecum when compared to the feces  and HA7 (p = 0.00254) diets  diets . In cont samples , no signhe cecum .p-values for the overall changes in abundance in feces (6A) and cecum (6B) that were considered significant by the Kruskal-Wallis test as well as pairwise comparisons by Wilcoxon Rank Sum tests. Comparing the different diets by weeks at the class level revealed that, with the exception of Alphaproteobacteria, no significant differences between the NCS control starch and the RS diets occurred in week 1. Consistent with the phylum-level results, members of the Actinobacteria, Alpha-, Beta- and Gamma-proteobacteria, and Verrucomicrobia showed significant differences in diet comparisons after week 1 in the feces , with HA7 having the highest and the OS-HA7 group having the lowest abundance. Betaproteobacteria followed the same pattern with all pairwise comparisons significantly different from each other and HA7 having the greatest abundance and OS-HA7 having the lowest . Also, Gammaproteobacteria was enriched in the OSHA7 group when compared to both the control and HA7 groups .To more specifically identify the taxa with altered abundance, we identified changes at the class level associated with the different diets. he feces . By weekAldercreutzia and Bacteroides were depleted in the HA7 group , while Sutterella (Phylum Proteobacteria), and Bifidobacterium showed significant increases . Inspection of Several genera whose abundances were altered by the diets after week 1 were also identified Figs  and 8. Cp = 0.066). Likewise, the diversity among the different diets within weeks 3 and 6 did not differ from each other. Inspection of number of OTUs discovered versus number of sequence reads revealed that the sequencing depth was sufficient to exclude discovery of new or rare OTUs  diversity metrics we used a nonparametric two-sample t-test using Monte Carlo permutations to determine the extent to which groups differed from each other. Comparing Shannon diversity values  for eachare OTUs . Nonparaare OTUs . Statistare OTUs  of Faithare OTUs  revealedp-value of 0.001 and an R-value of 0.836, which is close to 1.0, indicate dissimilarity among the groups. A p-value of 0.001 in the Adonis test also revealed that the clustering of the groups is significant and the groups were dissimilar in composition. An R2 value of 0.37712 signified that 37.712% of the variation in the groups can be explained by this clustering.QIIME was also used to generate PCoA plots of the unweighted distances obtained from the beta diversity workflow. p = 0.041; HA7:OS-HA7 p = 0.221) as well as the time spent in the open arm  with a subsequent increase in the time spent in the closed arm . In contrast, mice treated with NCS and OS-HA7 spent more time in the open arm and less time in the closed arm. No differences were observed between the mice treated with NCS and those treated with OS-HA7 in the number of entries into the open arm (NCS:OS-HA7 p = 1.000), time spent in the open arm (NCS:OS-HA7 p = 1.000) and time spent in the closed arm (NCS:OS-HA7 p = 1.000). HA7 fed mice spent a signficantly greater time grooming (p< 0.05) compared to NCS fed mice.Investigation of changes in anxiety-like behavior were observed through the EPM. In mice treated with the HA7 diet, there was a significant reduction in the number of entries into the open arm . There were statistically significant differences in the time spent in quadrant II . However, these results did not appear to be biologically significant because they did not represent differences in the overall locomotor behavior as a total measure of locomotion as quantified by total distance travelled and revealed no statistically significant differences between groups (p = 0.055).In addition to the elevated plus maze, the open field was used to test for differences in exploration. Overall, there were no significant differences in locomotor behavior in the open field apparatus, however there were statistically significant differences in exploration as demonstrated by transitions between quadrants. Mice treated with NCS transitioned between quadrants more than mice treated with HA7 or OS-HA7  with no significant differences between mice treated with HA7 and OS-HA7 (HA7:OS-HA7 p = 1.000). Furthermore, mice treated with NCS also demonstrated increased rearing compared to mice treated with HA7 and OS-HA7  with no statistically significant differences between mice treated with HA7 and OS-HA7 (HA7:OS-HA7 p = 1.000). As shown in p = 0.693; NCS:OS-HA7 p = 0.145; HA7:OS-HA7 p = 0.012) higher levels of corticosterone detected in NCS (0.028 ng/mg) and OS-HA7 (0.047 ng/mg) compared to HA7 (0.017 ng/mg).Hair samples revealed a significant difference in corticosterone levels, while all hormones showed no differences . Analysiet al. [The results presented demonstrate that an RS-supplemented diet can both alter the gut microbiota composition as well as influence brain function as reflected in an increase in anxiety-related behaviors. That the interplay between diet, microbiome and behavior is a complex one is amply illustrated by the study of Ohland et al.  who obseet al. .et al. [Studies continue to demonstrate in humans that the composition of the microbiota has a dramatic influence on the behavior of the individual. For example, the composition of the mucosal microbiota of cirrhotic patients was linked to poor cognition . Individet al.  demonstret al. , 43. Litet al. , 44.In vitro analysis of RS contents of the three starch varieties show that after boiling NCS displays 0.8% RS content, whereas HA7 and OS-HA7 display 24.1% and 20.9% RS, respectively [Starch is a major energy source in human and animal diets. ectively . After tectively .Bifidobacterium species in HA7-fed mice  and pathway(s) by which RS-induced alterations in the microbiome influence the brain? Each diet induced specific changes in the gut microbiota. The simplest explanation is that specific microorganisms that produce metabolites, including neurochemicals, that affect brain function are altered in response to RS. The change in concentration of these metabolites consequently has a direct effect on brain activity. Our results suggest more complicated mechanisms are in play. Specifically, we observed an increase in fed mice . This geame diet . The resype 2 RS . A reducsruption . HA7 fedria Figs . It is kbacteria –50. The on of RS . It is con of RS .Actinobacteria increased in week 3 before decreasing in week 6 in the NCS and HA7 groups. Verrucomicrobia increased in week 3 then decreased again in all groups. Bacilli decreased in all groups throughout the study while Clostridia increased in the HA7 and OS-HA7 groups.In addition to changes in abundance among specific bacterial taxa at the end of the study, we observed that the gut microbiota were dynamically altered throughout the feeding regimens. For example In addition to changes in the gut microbiota, we along with others, observed that RS also alters the physiological function in the rodent cecum, as evidenced by enlarged ceca (data not shown), which is indicative of enhanced fermentation activity , 51, 52.Modulation of the microbiome represents an emerging therapeutic modality by which behavior may be addressed to improve quality of life . The useS1 Fig(DOCX)Click here for additional data file.S1 TableValues are given for each sample where samples with an “R” represents mice fed the control starch, “B” mice fed HA7, and “G” mice fed OS-HA7.(XLSX)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


Internet of Things (IoT) is regarded as a remarkable development of the modern information technology. There is abundant digital products data on the IoT, linking with multiple types of objects/entities. Those associated entities carry rich information and usually in the form of query records. Therefore, constructing high quality topic hierarchies that can capture the term distribution of each product record enables us to better understand users' search intent and benefits tasks such as taxonomy construction, recommendation systems, and other communications solutions for the future IoT. In this paper, we propose a novel record entity topic model (RETM) for IoT environment that is associated with a set of entities and records and a Gibbs sampling-based algorithm is proposed to learn the model. We conduct extensive experiments on real-world datasets and compare our approach with existing methods to demonstrate the advantage of our approach. Internet of Things (IoT) is a novel paradigm that is rapidly developing in the scenario of modern wireless telecommunications and the information age. The ubiquitous of IoT technology especially in embedded devices has led to smart systems that affect people's daily life. The concept behind IoT is that a variety of objects around us can interact and work with each other to pursue common goals [Theon goals .There are several popular services among IoT such as online shopping or goods recommendation systems. An ideal e-commerce website should correctly understand user's query intent and return satisfactory searching results as fast as possible; a favorite recommendation system should exactly predict user's individual preference, meaning the application must be cognizant of the topics behind every piece of product. The fact is tens of thousands of digital products/records within IoT constantly update and new records are generating every day. How to manage those data, how to define right records categories, those two questions will bring fresh challenges to the IoT industry.A variety of existing works are dedicated to constructing topic or concept hierarchies from text data in the Internet. One innovative approach is to learn a topic model based on probability statistics. Traditional topic models treat each document as a bag of words and predict the topic through the word distributions. It has been widely used in fields such as taxonomy construction , conceptAlthough these models perform well in certain domains, they are not appropriate in our case for two reasons. First, most of the records consist of short text like tweets, so it is sometimes difficult to discover the topic through only a few tokens. But unlike tweets and other short texts, these records exist behind the query interface of certain websites and can only be obtained through keywords querying. Records from the same keyword query have some connections between each other and together they represent common topics. In other words, the word distribution of a single record can be regarded as a mixture latent topic distribution of current record and its “neighbor” records (records extracted from the same keyword queries), and the overall query records list might finally determine the topic of one record. Second, one product record usually is associated with plenty of attributes that describe the detailed features. For example, a book record has attributes like author and publisher; a movie record contains attributes like casts and director; a research paper record is associated with authors and publication. The truth is that almost any record is associated with some set of real-world entities, which is the foundation of IoT. Despite the fact that previous works have involved one or two types of entity relations in their topic models, like author relationship in ATM, they can only deal with certain domain documents. While our records associate with multiple objects, our topic model should be more general to conduct the topic analysis in diverse domains.z, e, w denote a topic, an entity, and a word, respectively; our goal is to design a topic model that can solve the problem like P(w∣z), P(w∣e), and P.To further explain our goal, we need to know the term distributions for each entity or topic-entity pair. Specifically, let P(w∣Data  Mining); we could know a specific author A's research interest in data mining area by analyzing the word distribution of  P; we can further compare his data mining related work with other researchers like B in the same field by comparing P with P.The dependencies among topic, entity, and word could help the system to gain a better understanding of the model. For example, in a collection of computer science research papers, we could know the basic concept of data mining through the word distribution of  P but directly assume that either P = P(w∣e) or P = P(w∣z) by introducing different types of conditional dependency relations among topics, entities, and words. For instance, both LDA and Link-LDA believe that P equals to P(w∣z); ATM, on the other hand, assumes that P = P(w∣e). However, such “seems reasonable” assumptions may not always be correct in many cases. Recall the previous example, if P = P(w∣e)  holds, we can obtain that P = P, but this equation does not hold since authors seldom use the same terms in papers from different topics. Meanwhile, if P = P(w∣z)  holds, means P  is equal to P, but obviously different authors use different terms due to writing habits even doing the same research topic. To this point, it is really necessary for us to model P directly to find the correlation of words between a pair of an entity and a topic.In addition, topic model that involves entity distributions can be more accurate since it might avoid some mistakes caused by traditional models. In most previous works, they do not care for the distribution of  record entity topic model (RETM). This model is a promotion of LDA model and argues that each record can be identified as a word distribution over a set of entity-topic pairs. Furthermore, it points that “neighbor” records should have some impact on the topic distribution of one record, since they come from the same query list so that they have great topical similarities. In this case, these improvements make the model more flexible and specific.To trickle the above challenges, we propose a novel topic model to analyze the topics of querying records in IoT environment namedThe main contributions of our work are as follows. (1) We studied an important practical problem of modeling the topics for IoT industry using the latent relationships among querying records. To the best of our knowledge, this is the first work to introduce such issue. (2) We improve our model by adding entity relative dependency and emphasize the correlation of entity-term and topic-term distributions. We also adopt Gibbs-sampling-based algorithm to learn the model. (3) We conduct complex experiments on real-world dataset and compare with some state-of-the-art topic models. Results show that our method performs well in certain aspect and has some advantages.The rest of this paper is organized as follows. We begin by reviewing the related works in the next section. After that, we introduce the overall model by giving the problem statements and describing the generation process as well as how to inference and learning the model in Latent topic modeling has become very prevalent as a completely unsupervised technique for topic discovery. PLSA   and LDA The original purpose of topic models is to process plain text of documents. Recently, more attention has been paid in respect of topic discovery with hypertexts or citation information. Link-LDA  is desigP = P(w∣z), which is usually not the case.In addition to review the hyperlinks between the documents, some researchers proposed models that concentrate on the relations of author. For instance, Mccallum  intends P. However, besides the previous explanations we made to illustrate the particular characteristics of our case, ETM has paid great attentions on determining the shared asymmetric Dirichlet priors. Conversely, our method tries to balance between entity distributions with topic distribution obtained from local topic or overall topics, so we decide to adopt symmetric Dirichlet priors, which is enough in our case. In addition, the two models have entirely different generative process.Some works pay attention to model short text documents like records in our case. For example, PatentMiner  is propoIn this section, we firstly give the definition of RETM and then explain the generation process and finally provide a Gibbs-sampling-based learning algorithm to infer the model. director and production company in Records we mentioned are obtained from keywords querying over the Internet. They are dynamic, highly qualified, and exist in the hidden databases. Each record consists of several attributes that describe all the associated features of one unique object. Most records involve multiple entities in the attributes, such as the attributesr is associated with a term vector, where each wd,i is selected from a vocabulary database W and an entity vector  Ed, which is chosen from a set of entity of size E. Let a collection of R records (r ∈ R) is determined by R = {〈w1, E1〉, 〈w2, E2〉,…, 〈wR, ER〉}.Each record z and entity e to get P, which also satisfies a multinomial distribution with parameter φe,z. The notation of the whole paper is present in Notation section. Note that the entity we used in our model is gained from some well-known corpus such as DBpedia [δd, which are not generated but can be easily calculated with the help of modern knowledge base.The goal of this paper is to identify word patterns for each pair of an entity and a topic, that is, to find the precise word distribution over topic  DBpedia  or Proba DBpedia . Unlike Book domain, but he is often identified as the director of movie Tiny Time in the Movie domain. In other words,  P ≠ P if em ≠ en  and P ≠ P if  zm ≠ zn. Secondly, the topics of one record could be determined based on the current record itself or together with its “neighbor” records. For example, in  local topics; one record and its “neighbor” records from the identical query list together produce some topics and we name them background topics. They all originate in the same vocabulary source and there are Kc local topics and Kb background topics, respectively. Therefore, for each record d, multinomial distributions θd  and θd′ over topics can be drawn from a Dirichlet prior with α0. Suppose that the probability of choosing local topics is pz and the probability of choosing background topics has to be 1 − pz. By observations, we find that once the value of attributes consists of short tokens, record d's topic mostly depends on the distribution of local topics. On the contrary, if the record contains long texts such as abstract information of a paper or the reviews of a product, d largely relies on the background topics. For convenience, we define a flag variable t ∈ {0,1}, where t = 1 means the multinomial distribution θd of a word  zi is determined by local topics whereas t = 0 means θd′  is selected. At the same time, multinomial distribution δd over entity set Ed can be drawn from a Dirichlet prior with  α1. Unlike other topic models which usually select an entity directly from the entity sets, we construct our model that depends on a record-specific multinomial distribution  δd. This stems from the fact that each entity tends to have different weights in generating a record. For example, casts and the director dedicate differently to a movie record; if a research paper has multiple authors, the lead author possibly makes more effort than the others. Next, to generate each word in records, a topic zd,i is drawn from the determined θd or  θd′, and an entity ed,i is drawn from δd. After that, a word wd,i can be generated through Gibbs sampling based on an entity and topic specific multinomial distribution φed,i,zd,i that has a Dirichlet prior β. In a word, each term is related to a pair of entity and topic and the generative process is the result of their joint actions. Here, the values of wd,i  and Ed can be derived from observations and parameters like α0, α1, and β can also be obtained from empirical statistics. Others parameters like θd, δd, zd,i, ed,i and φed,i,zd,i  are all unknown latent variables that needs to infer.Now we can infer the topic of querying records through probability statistics based on previously known data and the generative process. Researchers usually employ approximate techniques to estimate the LDA parameters such as Variation Expectation Maximization , ExpectaGibbs sampling is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution. It generates a Markov chain of samples, each of which is correlated with adjacent samples. The output parameters can be estimated iteratively until convergence. Z, ε) along with the priors parameters. At this point, the conditional posterior of assignment  to the ith word wd,i  in record d isd” denotes a quantity excluding data from position i in record d in order to eliminate the influence of current position word tokens.Depending upon this process, we could repeatedly sample the entity-topic pair for each word, in case of the assignment of all the rest words   is also assumed to be a symmetric Dirichlet with concentration parameter α1. Thus, given corresponding entity assignments ε = {ed}d=1R in |Ed|  entities vocabulary set, the conditional posterior of one main topic k of certain record d can therefore be written in the formNk∣d = nd  denotes frequency of occurrence of topic k to all topics associated with record d and  Nd = ∑kNk∣d. Note that each record can contain a few duplicated topics, but the main topics cannot be repeated.Formula  is compred,i  at current position is equal to total probability divided by the probability of excluding the word at ith position and  ed,i = k, which we represent as pdi−, wherepi of ed,i  isNed,i∣dd,i∖  is the number of word tokens assigned with entity ed,i  except ith token in record d. In addition, as defined in Dirichlet distribution, there isV stands for the size of vocabulary set and meanwhile, we have ndi = ndi,−i + 1 according to our definition. At this point, we can infer . Since word wi is generated from local topic zd,i  if t = 1, according to Kc topics Z = {z1, z2,…, zkc},  we havet = 0, word wi is generated from background topic  zd,i′. Since there are Kb topics Z′ = {z1′, z2′,…, zkb′}, we obtainNzd,i∣dd,i∖ or Nzd,i′∣dd,i∖ is the number of word tokens assigned with topic zd,ior  zd,i′  except ith token in record d. Meanwhile, we take the same methods for determining P as term 3.For the second term in , as mentK topic entity pairs whose distribution φe,z is a multinomial distribution with a Dirichlet prior β, the word distribution probability that not include the word at position i and associated pair <zi, ei > = k is in the form ofnk,−i stands for the number of tokens assigned with the pair 〈zi, ei〉 other than the word wi. Next, the probability of 〈zi, ei〉 = k can be written in the form ofnk is the number of word tokens that are assigned to the kth entity topic pairs.We now determine the first term in the objective formula. Note that the distribution of words in every record is regarded as a mixture of topic-entity pair distributions. Given Finally, the expression of first term in  takes thφe,z. Then we can estimate the parameters like θd, θd′, and δd  accordingly to get the distribution of each record over entity topic pairs to ultimately find the most possible topic for each record through analysis.So far, we have obtained three terms in , which a BOOK, and all the records are crawled from Soochow University library bibliographic query system (http://lib.suda.edu.cn) through LAN. We pick up 2000 nonrepeating records of computer science books manually and each record has attributes that include book name, author name, ISBN, press, price, and overview. Owing to the demand of constructing background topics, we keep the URI information about records in the same query lists in the form of RDF. Another dataset is from ACM research paper data source, namely, PAPER. It contains 38469 published papers about information system retrieved in 2002–2011 years in 2012 September according to the classic category (download from: http://www.datatang.com/datares/go.aspx?dataid=619787). Each metadata consists of the corresponding citation network, keywords, title, date of publication, journals, and abstract. In order to facilitate the evaluation, we pick up the top 19235 records in our experiment, which is perfect to test our model, since it contains the associated keywords data. However, it does not contain the information about querying so it is not suitable for testing the background topic part.We make use of two large-scale datasets for the evaluation of our model, both of which are extracted from real-world data sources. One dataset is namedTo testify the impact of entity distribution on the main model, we use DBpedia Soptligh  to preprThe objective of this paper is to verify two factor distributions impacts on overall topic distribution: the entity distribution and the background topic distribution. Since the datasets are composed of discrete records, we need to choose the baseline methods in the experiments for different purposes.Firstly, we choose LDA, Link-LDA, AM, and ATM as the baselines in our experiment of testing entity distribution impact. We claim that word distributions should depend on associated entities besides the topics. From  BOOK, we set K = 20, α0 = α1 = 0.1, and β = 0.1. The fact is that one record tends to choose the local topics once this record contains attributes like abstract, overview, review, and so forth, which usually involves long text. Therefore, we say that one record has long text if |Nd | >120 and pz = 0.48 through statistical calculations. For PAPER, we set K = 50, α0 = α1 = 0.1, and β = 0.1 and when |Nd | >60, we define that this record has long text; in this case, pz = 0.65. Above hypermeters are applicable for LDA, Link-LDA, and AM. ATM's hypermeters are set as α0 = α1 = 50/T and β = 0.01 according to [Forrding to 's suggesP(Φ | Dtrain)  under samples from  P(Dtest∣Φ). Since we already known a set of entities, we can getIn addition, we perform perplexity analysis to examine the performance of each model. Perplexity evaluates how well a probability distribution or probability model predicts a sample. The lower a trained model's perplexity is, the better the topic model is, the more flexibility one model will get. The definition of perplexity is hereby given as follows:el, thenP. It is obvious that all three authors have published many papers on machine learning area but in different research approaches. For example, Pedro Domingo is specialized in the research of Markov logic networks whereas Judea Pearl is credited for inventing Bayesian networks and several inference methods in the models; Andrew Ng is Michael I. Jordan's student, who mainly focuses on researches about deep learning recently. Although three authors study very distinct approaches under the same research topic, which causes totally different word distributions, this difference could be measured through analysis of P based on RETM. Now we can get the conclusion that topic model that is associated with entity distribution could be more detailed and distinguishable in topic category subdivision process. In addition, it provides intuitive and understandable comparisons through P, which is impossible if we are just modeling P(w∣z)  or  P(w∣e).Take Professor Michael I. Jordan as an example for the first case study, who is a leading researcher in machine learning and artificial intelligence. He applies Bayesian networks into machine learning and makes outstanding contributions on optimization problems in likelihood estimation.  PAPER, so RETM and RETM-self are considered to be the same. According to , this term will not be generally accepted unless such kind of research topics become popular or famous. From We also need to analyze the perplexity value of RETM compared to the baseline models: LDA, Link-LDA, AM, and ATM. Recall that there is no background topics information inrding to , we rand BOOK in that this dataset contains detailed linking information about records crawled from the data sources. In this case, we could easily summarize the background topic from one record as well as its neighbor records. This time, we compare RETM with LDA, ATM, and RETM-self. Since AM does not involve entity or background topics in its model, there is certainly no change in its perplexity values as the topic number grows; thus, it has no comparison value. Furthermore, LDA and Link-LDA perform very alike under these situations so we elect to select LDA as the representative model for simplicity. Other hyperparameters or experimental settings are kept the same as the previous one. Unlike PAPER, we need to preprocess the data in BOOK with DBpedia knowledge base. As a result, relatively more words that associated with entities are chosen for the corpus.In this task, we prefer to use PAPER dataset. First of all, ATM gives almost the same performance as in BOOK. It only needs to estimate a few hyperparameters and can make use of the extra entity distributions prior informatio;, its perplexity values have been decreasing as more topics added. Secondly, both RETM-self and RETM's performances are better than LDA, which further indicates that with the help of entity distributions, our model can be more accurate and convenient to categorize the given topics. This effect is rather obvious when the number of topics is no less than 20. Finally, we can find that REMT gets the lowest perplexity values, comparing RETM with RETM-self, especially when the number of topics is less than 10. No doubt RETM can take advantage of the related background topics information, which is the only difference between the two models. Unfortunately, RETM has to estimate more parameters when picking the background topics distributions, which bring a large amount of calculation and lead to enormous complexity in each sampling iteration. Consequently, its perplexity values grow very fast, limiting its generalization performance, and get worse when the number of topics is larger than 100. BOOK as set 1,and then pick up 2000 records that do not have any overview information about this book manually as set 2. In this case, set 2 is considered to contain short text only. We now extract the topics of each record from two sets, respectively, and compare the accuracy with ATM and LDA. The results can be found in Next, we will discuss to what extent the background topic distributions can affect the general topic. Recall that all the above experiments are conducted under the assumption that the record chooses to use the local topics when this record has long described text in its attributes, meanwhile, it decide to choose the background topics which generated from current record and neighbor records when the text is consist of short tokens. Now to prove the accuracy of hypothesis, we randomly pick up 2000 records that contain different lengths text from theThis paper studies a particular topic model construction method for the infrastructure of the information network for IoT. Based on the fact that almost every record extracted from the query result lists of IoT involves several entities, it proves that the entity distributions have some substantial impact on the word distributions within records. That is, once we add the entity distributions as priors into the topic model, the model can produce meticulous category as well as increase its distinguishability, which helps the users to understand the record content easily. In addition, our model particularly pays attention to the way each record is extracted. We classify the records gathered after querying the same keywords and then claim that the word distribution in every record should associate with topics that is generated from either its own topic distributions or the background topic distributions. These two arguments are accepted through the experiments on real-world datasets. From the analysis of experimental results, we find that our model is more suitable for extract topics from records compared to other traditional models. Furthermore, this approach can extract more accurate topics that can exactly describe the content of the records. So our work has some advanced and realistic significance to the further work of IoT.


Many of the exciting new developments in solid tumor molecular cytogenetics impact classical and molecular pathology. Fluorescence in situ hybridization to identify specific DNA target sequences in nuclei of non-dividing cells in solid neoplasms has contributed to the integration of molecular cytogenetics into cytology in spite of the remarkable promiscuity of cancer genes. Indeed, although it is a low-throughput assay, fluorescence in situ hybridization enables the direct disclosure and localization of genetic markers in single nuclei. Gene fusions are among the most prominent genetic alterations in cancer, providing markers that may be determinant in needle biopsies that are negative or suspicious for malignancy, and may contribute to the correct classification of the tumors. In view of the expanding use of fluorescence in situ hybridization in cytology, future challenges include automated sample evaluation and the specification of common criteria for interpreting and reporting results. The. Thein schniques . Some ofEWS/FLI1, th, th14], Many of the exciting new developments of molecular cytogenetics are having a profound impact on classical and molecular cytology. The growing demand for cytological FISH tests highlights the need for the specification of common criteria for interpreting and reporting FISH results, for quality control and quality assurance policies, and for possible implementation of automated FISH evaluation.The authors declare that they have no competing interests.PC and RV participated in commentary design and wrote the manuscript. They read and approved the final manuscript.


Identification of novel brominated contaminants in the environment, especially the derivatives and byproducts of brominated flame retardants (BFRs), has become a wide concern because of their adverse effects on human health. Herein, we qualitatively and quantitatively identified three byproducts of tetrabromobisphenol-S bis (TBBPS-BDBPE), including TBBPS mono (TBBPS-MAE), TBBPS mono (TBBPS-MBAE) and TBBPS mono (TBBPS-MDBPE) as novel brominated contaminants. Meanwhile, the mass spectra and analytical method for determination of TBBPS-BDBPE byproducts were presented for the first time. The detectable concentrations (dry weight) of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were in the ranges 28–394 μg/g in technical TBBPS-BDBPE and 0.1–4.1 ng/g in mollusks collected from the Chinese Bohai Sea. The detection frequencies in mollusk samples were 5%, 39%, 95% for TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE, respectively, indicating their prevailing in the environment. The results showed that they could be co-produced and leaked into the environment with production process, and might be more bioaccumulative and toxic than TBBPS-BDBPE. Therefore, the production and use of TBBPS derivatives lead to unexpected contamination to the surrounding environment. This study also provided an effective approach for identification of novel contaminants in the environment with synthesized standards and Orbitrap high resolution mass spectrometry. Recently, increasing studies have been carried out to identify novel brominated contaminants in the environment, especially the derivatives, byproducts and degradation products of brominated flame retardants (BFRs)122246As important alternatives of TBBPA, the most widely used BFR, tetrabromobisphenol-S (TBBPS) and TBBPS bis (TBBPS-BDBPE) are extensively produced and applied in electronic devices, plastics, rubber and textilesThe lack of analytical methods is another main obstacle for identifying novel contaminants. Because of the thermolability of TBBPA, TBBPS and their derivatives, gas chromatography mass spectrometry (GC-MS) is not applicable for direct analysis of these compounds11381010141516The aim of this study was to identify three potential byproducts of TBBPS-BDBPE as novel brominated contaminants. The standards of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were synthesized with high purity. A sensitive and accurate method for simultaneous determination of these novel TBBPS derivatives was developed with UHPLC-Orbitrap HRMS. Their distribution in mollusk samples collected from the Chinese Bohai Sea and potential risks were discussed in detail. The strategy used in this work could also be an effective approach for identifying other novel brominated pollutants related to BFRs.1HNMR spectra of these compounds are provided in The standards of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were self-synthesized with purities of 99%, 98% and 96%, respectively. The synthesis schemes and m/z values of [M-H]− for TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were 604.69189, 684.60022/682.60248, and 764.52643, respectively , TBBPS-MBAE (678.60681) and TBBPS-MDBPE (758.53296) were calculated with Orbitrap Xcalibur software to present the molecular composition of [C15H9Br4O4S]−, [C15H8Br5O4S]− and [C15H9Br6O4S]−, respectively. The precursor ions of TBBPS-MAE (m/z 604.69), TBBPS-MBAE (m/z 682.60) and TBBPS-MDBPE (764.53) generated the same fragment ion clusters at m/z 563.65, 499.69, 484.73, 419.77/417.77, 297.81, 265.84, and 249.85, which were calculated with Xcalibur software to be [C12H4O4Br4S]−, [C12H4O2Br4]−, [C12H4O4Br3S]−, [C12H3O2Br3]−, [C6H2O2Br2S]−, [C6H2O2Br2]− and [C6H2OBr2]−, respectively , was 101% ± 7% at the spiking amount of 10 ng (n = 7). The recoveries of ISDBP from the real samples ranged from 81% to 104% with a mean recovery of 91% and SD of 6% (n = 38). The matrix effects ranged from 0.86 to 1.05  method at the spiking amounts of 10 ng in 0.5 g Neverita didyma (Nev) samples n = 7, . The rec to 1.05  at threeThe technical product of TBBPS-BDBPE purchased from a BFRs factory (purity >90%) was dissolved in methanol at a concentration of 100 μg/mL and determined by Orbitrap Fusion HRMS. The concentrations of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE in this technical TBBPS-BDBPE were 28 μg/g, 87 μg/g and 394 μg/g, respectively.The concentrations of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE in total 38 mollusk samples collected from Bohai Sea during 2009 to 2013 were also analyzed with an external standard method . TBBPS-MKow values of TBBPS and the derivatives ranged from 5.21 to 9.52, log Koa values ranged from 16.83 to 21.83, log Koc values ranged from 4.16 to 6.33, and log Kaw values were all lower than −8.81. The bioconcentration factor (BCF) values of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were 10730, 13200 and 8829, respectively, which were significantly higher than those of TBBPS (1266), TBBPS bis (TBBPS-BAE) (4207) and TBBPS-BDBPE (775).The physical-chemical properties of TBBPS, TBBPS derivatives and other well concerned contaminants were calculated by US EPA EPI Suite V4.1, which has been widely employed for screening of potentially persistent and bioaccumulative contaminants20212223242550 of TBBPS, TBBPS-MAE, TBBPA-MBAE and TBBPS-MDBPE were 0.45, 0.19, 0.20 and 0.17 μM, respectively. The IC50 of TBBPS-BAE and TBBPS-BDBPE were 13.1 and 11.2 μM. TBBPS and the three derivatives with phenol groups, TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE, inhabited 50% of the cell viability at a much lower concentration than TBBPS-BAE and TBBPS-BDBPE.In addition, the potential toxicity of TBBPS-BDBPE, TBBPS-BAE, TBBPS, TBBPS-MAE, TBBPA-MBAE and TBBPS-MDBPE were also estimated with the primary cerebellum granule cells (CGCs) as the model, which were usually used for neurotoxicity studies13271HNMR, UHPLC-Orbitrap Fusion HRMS  and HPLC-UV. The results indicated the successful synthesis with high purity (>96%) of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE. These compounds could be used as the standards for the further analysis.Since the standards of TBBPS-BDBPE byproducts were not commercially available, TBBPS-MAE, TBBPS-MDBPE and TBBPS-MBAE were self-synthesized and further characterized by In order to identify the target compounds in samples, an accurate and sensitive method was developed. By using the highly sensitive Orbitrap Fusion HRMS, the IDLs for TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were in the range 0.06–0.1 pg which were lower than those acquired with HPLC-ESI-MS/MS. The target compounds could be identified according to the accurate m/z values of precursor ions within a mass tolerance of 5 ppm. Meanwhile, in the full scan mode, the isotope information was positively observed with the quantification process. As for optimizing the extraction method, the ultrasound method showed slightly higher recoveries and lower SDs which meant it was a stable and reliable extraction method. Meanwhile, the matrix effects were all close to 1.0 which indicated the interference from the matrix could be ignored. ENVI-Carb SPE cartridges could effectively eliminate the interference and concentrate the target compounds. The pretreatment method was reliable and repeatable for the identification of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE in mollusk samples. Meanwhile, ISDBP was selected as an appropriate internal standard for the recovery monitor of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE from the mollusk samples. The recoveries of ISDBP were all higher than 80% in all the samples, indicated the recoveries of target compounds from real samples were reliable.With the proposed method, the existence of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE in technical TBBPS-BDBPE and mollusk samples from the Chinese Bohai Sea was studied in detail. In the sampling area of this work, several BFRs factories produce TBBPS and TBBPS-BDBPE on a large scale. TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were detectable in technical TBBPS-BDBPE of the BFRs factory with the concentrations ranged from 28 to 394 μg/g. Consequently, in mollusk samples, TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were detectable at a level of ng/g dw. Therefore, the BFRs factories might be the point sources of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE. They were probably produced with the manufacture process, and leaked into the environment through the production and application process. The production process of TBBPS-BDBPE might influence the concentration and detection frequency of the byproducts. TBBPS-BDBPE is synthesized from TBBPS-BAE, and TBBPS-BAE is synthesized from TBBPS. Therefore, TBBPS-MDBPE, which has the most similar structure with TBBPS-BDBPE, is the main byproduct of TBBPS-BDBPE. As a result, TBBPS-MDBPE was detected at the highest concentration and detection frequency. While the technical TBBPS-BAE is produced as intermediate of TBBPS-BDBPE, its structure related byproduct, TBBPS-MAE, showed the lowest concentration and detection frequency. TBBPS-MAE and TBBPS-MBAE were detected in the mollusk samples at the similar concentration level with previously reported for TBBPA derivatives, TBBPA-MAE and TBBPA-MDBPE2929Kow values of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were close to TBBPA (7.20)Koa values of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE indicated low respiratory elimination rate and high bioaccumulation ability in respiratory organisms. Meanwhile, the low Kaw values implied that large amount of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE would participate in water rather than the air at the boundary exchange process. The comparable Koc values with TBBPA (5.24) and TBC (4.92) indicated TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE could be absorbed by the sediment and soil with a considerable amount. Usually, the chemicals with log Kow > 5 and BCF > 5000 are considered to be bioaccumulative50 of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were all lower than 0.2 μM, suggesting that they were more toxic than TBBPS-BDBPE and TBBPS-BAE with IC50 higher than 11 μM  the isotope ratio is different for compounds contained different number of Br. In this study, some untargeted brominated organics also showed up in the samples. Their spectra are shown in 6H2OBr3]−, [C12H5O4Br4S]− and [C6H2O3NBr2]−, respectively. They might be three kinds of bromophenols. These three untargeted compounds were further analyzed with Orbitrap Fusion HRMS with reference to the standards, including TBBPS, 2,6-dibromo-4-nitrophenol (DBNP) and four kinds of tribromophenol  m/z value of the decimal part decreases with the number increase of mophenol . The untmophenol  showed smophenol  had the enol 3334 presenteMost BFRs, such as poly brominated diphenyl ether (PBDE), TBBPA and TBBPS derivatives, usually share the ether bond linked structure3839402343442In conclusion, TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were identified as three novel brominated contaminants, which showed higher bioaccumulation properties and potential severe toxicity compared with TBBPS-BDBPE. They could be co-produced and leaked into the environment along with production process of TBBPS-BDBPE. The occurrence of the mono-modified byproducts or degradation products of the extensively used brominated products might be a widespread problem. This work could promote the further study of the environmental fate and risks of widely used TBBPS and TBBPS-BDBPE. The strategy used in this work, integrating the synthesis of standards and Orbitrap HRMS identification, could also be an effective approach for identifying other novel brominated pollutants related to BFRs.TBBPS (98%) was purchased from Beijing Apisi biotechnology co. ltd., and was used without further purification. Ammonium hydroxide (50%) was purchased from Sigma-Aldrich. Methanol, acetone, hexane and methylene dichloride (DCM) were all HPLC grade. Ultra-pure water was generated by a Milli-Q advantage A10 system. TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE were synthesized and purified in our lab. The synthesis procedures were described in From 2009 to 2013, in August of each year, 11 species of mollusks were collected from one coastal city — Shouguang, Shandong Province. These 11 selected species of mollusks were Rapana venosa , Crassostrea talienwhanensis (Ost), Scapharca subcrenata (Sca), Cyclina sinensis (Cyc), Mya arenaria (Mya), Mactra veneriformis (Mac), Chlamys farreri (Chl), Neverita didyma (Nev) and Meretix meretrix  . After s2SO4; spiked with 10 ng 13C labeled 3,5-dibromophenol (ISDBP); extracted with 10 mL DCM/hexane  for three times by sonication (30 minutes per time). After centrifugation, the extraction solution was collected and the solvent was removed with rotary evaporator and re-dissolved in 3 mL DCM/hexane  before SPE process.Mollusk (0.5 g) samples were mixed with 2 g anhydrous NaTM ENVI-CarbTM, 0.5 g, 6 mL) were first conditioned by 5 mL acetone, 5 mL DCM and 10 mL hexane and then the samples were loaded. Then the cartridges were cleaned by 5 mL hexane and 5 mL DCM/hexane . Finally, the cartridges were eluted with 10 mL acetone (containing 0.5% NH3·H2O) and the elution were collected and blown to dryness by gentle nitrogen gas flow. The residue was solvent-exchanged to 1 mL methanol and analyzed by UHPLC-Orbitrap Fusion HRMS.The SPE cartridges  higher than 0.99 (2SO4 added), and analyzed with methanol as solvent blank to make sure no cross contamination. The DLs were determined by the lowest mass value of the target compounds that Orbitrap Fusion HRMS detected. The IDLs were determined for five times within 20% relative standard deviation for the signals. The MDLs were based on replicate analysis (n = 10) of Nev sample spiked at a mass concentration of 5 times of the IDLs and calculated with the method previously used for HRMS13C labeled 3,5-dibromophenol (ISDBP) was used to monitor the pretreatment process and not used for the concentration calculation. The detailed procedures for the SPE optimization and results were described in 431HNMR and MS2 spectra of TBBPS-MAE, TBBPS-MBAE and TBBPS-MDBPE, the 1HNMR data, instrumental analysis information of Orbitrap Fusion HRMS, HPLC-UV and HPLC-ESI-MS/MS, the optimization of pretreatment method, the concentration of every mollusk sample, the cell information and cytotoxicity test method, the cytotoxicity of TBBPS and its derivatives, the HRMS chromatograms and spectra of different brominated phenols are provided in the All calibration standards and spiking solutions were prepared by serial dilution in methanol. A linear calibration curve with seven points ranged from 0.05 to 100 ng/mL was used to quantify the target compounds with a determination coefficient .


Klinefelter syndrome (KS) is the most common chromosomal aneuploidy in males. It is very difficult to diagnose this disorder in childhood due to absence of significant manifestations before puberty. These patients usually present with tall stature. We report a case of KS with short stature due to growth hormone deficiency. The boy’s height was below the 3rd centile with significant delay in bone age. He responded well to growth hormone injections. In view of mental subnormality karyotyping was done, which revealed KS (47XXY).  Klinefelter syndrome (KS) is the most common chromosomal aneuploidy in males. Also, it is the most common genetic cause of azoospermia . It is cWe report a 3-year-old male child who was referred by his pediatrician for short stature . He was The boy had delayed motor and language milestones. There was no history of recurrent infections or chronic systemic diseases. His height was 76 cm . His body proportions were normal for his age. He had no midline facial defects, dysmorphic facies or bony defects. His external genitalia revealed microphallus  with normal external urethral meatus, well-formed scrotum, and palpable prepubertal testes. Other systems were normal. Bone age was delayed by 2 years . The basThe boy was started on recombinant human GH injections subcutaneously. There were no local or general side effects. After 1 year of treatment, his height increased to 84 cm and height SDS improved from -3.7 to -2.The patient is still receiving recombinant human GH with regular follow-up every 3 months for physical and auxological evaluation.Tall stature is one of the characteristic features of KS. The clinical phenotype has traditionally been described as tall, with sparse body hair, gynecomastia, small testes and impaired verbal intelligence . It is nThe association between KS and GH deficiency has been described in a small number of case reports, but the reason for such an association is not clearly known. Our patient was short due to GH deficiency which was thought to be due to pituitary hypoplasia. Pituitary imaging (MRI) was suggestive of anterior pituitary gland hypoplasia 1.7 mm). Other pituitary functions at this juncture were normal. The association of short stature with delayed bone age, hypoplastic pituitary gland and poor increase in GH level on stimulation tests is suggestive of an isolated GH deficiency. Richer et al  reported mm. OtheIn conclusion, by reporting the findings on this patient, we wish to emphasize the importance of GH testing in pediatric patients with KS, short stature, and delayed bone age.


Cardiac dysfunction following IR injury was associated with decreased activity of the mitochondrial electron transport chain (ETC) and increased mitochondrial ROS and PTP opening. Administration of A-769662 or SfA individually upon reperfusion improved cardiac function, reduced infarction size, and inhibited ROS production and PTP opening. However, simultaneous administration of SfA and A-769662 did not provide synergistic improvement of postischemic recovery of cardiac and mitochondrial function, though both compounds disrupted IR-induced interaction between PPARα and CyP-D. In conclusion, A-769662 or SfA prevents PPARα interaction with CyP-D, improving cardiac outcomes and increasing mitochondrial function, and simultaneous administration of the drugs does not provide synergistic effects. Activated AMPK protects the heart from cardiac ischemia-reperfusion (IR) injury and is associated with inhibition of mitochondrial permeability transition pore (PTP) opening. On the other hand, pharmacological inhibition of the PTP reduces infarct size and improves cardiac function. However, it is unclear whether beneficial effects of AMPK are mediated through the PTP and, if they are not, whether simultaneous activation of AMPK and inhibition of the PTP exert synergistic protective effects against cardiac IR injury. Here, we examined the effects of the AMPK activator, A-769662 in combination with the PTP inhibitor, sanglifehrin A (SfA) on In the heart, AMPK has been shown to regulate cellular uptake and subsequent entry of fatty acids into the mitochondria to increase fatty acid oxidation . Also, Arylation  or inhibrylation . Active rylation –8. Previafter IR , 10, wheafter IR .β-subunit of AMPK and, thereby, allosterically stimulates AMPK [Based on the potential therapeutic benefits observed in animal models, extensive studies have been performed to develop pharmacological activators of AMPK. Early studies determined that biguanides, including metformin, increased the phosphorylation and activation of AMPK, thereby protecting the heart against IR injury . Yet, thtes AMPK . A-76966tes AMPK .The cardioprotective effects of AMPK activation are associated with inhibition of the mitochondrial permeability transition pores (PTP) –20. The  in vivo cardiac IR. To avoid the undesired AMPK-independent effects of metformin, we used A-769662 in this study to activate AMPK. Since AMPK mediates cardioprotection by inhibiting PTP opening, we hypothesized that combined treatment with SfA and A-769662 would not provide synergistic effects. Our experiments revealed that treatment with SfA and/or A-769662 protects cardiac function and mitochondria without affecting AMPK phosphorylation. Both individual treatments reduced mitochondrial ROS (mitROS) levels, improved the activities of ETC complexes, and prevented IR-induced PPARα-CyP-D interaction and PTP opening. The combination of SfA and A-769662 did not provide synergistic cardioprotective effects on cardiac IR.In this study, we examined whether simultaneous PTP inhibition and AMPK activation provided synergistic cardioprotection against ad libitum. All experiments were performed according to protocols approved by the University Animal Care and Use Committee and conformed to the National Research Council Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health .Male Sprague-Dawley rats  were housed in individual cages in a temperature controlled room under a regular light-dark cycle. Water and food were provided™  heating pad with needle ECG leads. For the Sham procedures the ligatures were placed in an identical fashion but not tied. The resulting coronary artery ligations (CAL) were maintained for 30 min, after which the sutures were removed and followed by reperfusion for 24 h. The animals were randomly divided into the following five groups: Sham , IR (n = 8), IR + SfA (n = 4), IR + A-769662 , and IR + SfA + A-769662 . Animals having no ST-segment elevation on the ECG following CAL were excluded from IR groups with or without treatment due to a lack of myocardial infarction. SfA (25 mg/kg), A-769662 (10 mg/kg), or their combination was administered by intravenous bolus immediately before reperfusion. The doses for SfA and A-769662 were based on previous studies that demonstrated that SfA treatment [ in vivo IR.Animals were anesthetized with an anesthetic cocktail containing  xylazine 4.2, ketamine 87.5, and acepromazine 0.88 and artificially ventilated with room air using a small-animal ventilator . The respiration rate was maintained at 65 to 70 breaths per minute, and body temperature was maintained at 37°C by placing the animals on a homeothermic surgery table . Lateralion. SfA  mg/kg, Areatment  had card∗HR)/1000, and EF = ((LVEDV − LVESV)/LVEDV)∗100, respectively.Echocardiographic measurements were performed as described previously . Briefly2HPO4 and 0.1 M NaH2PO4, pH 7.4 at 37°C) containing 10 mg/mL tetrazolium chloride (TTC). The heart sections were fixed in 10% formaldehyde overnight and then photographed. Digital images of heart sections were analyzed for infarct size (TTC negative) using the NIH ImageJ software. The infarction size was calculated as a percentage of the entire left ventricle.Rats were sacrificed, the hearts were excised, and blood was washed for 10 min by retrograde perfusion with Krebs-Henseleit solution . Then, t2+ induced swelling of isolated mitochondria, measured as a reduction in light scattering at 520 nm, as previously described [μg of protein were incubated at 25°C in 200 μL buffer containing 150 mM KSCN, 20 mM MOPS, 10 mM Tris, and 2 mM nitrilotriacetic acid, supplemented with 0.5 μM rotenone, 0.5 μM antimycin, and 2 μM A23187. Swelling of mitochondria was initiated by progressive additions of CaCl2 , and rates of swelling were determined by monitoring the decrease in light scattering at 525 nm, quantified using a Spectramax M3 plate reader .Opening of the mitochondrial pore was determined by Caescribed . Mitocho2PO4, 5 mM MgCl2, and 0.5 mg/mL BSA), supplemented with saponin (0.55 mg/mL). To access the ETC complexes embedded in the inner mitochondrial membrane, the mitochondria were disrupted three times by freeze-thawing and, then, incubated for 30 min at 4°C. All measurements were recorded at the Thermo Scientific GENESYS™ 10S UV-Vis spectrophotometer at 30°C. Activities of all ETC complexes were normalized to citrate synthase activity.Enzymatic activities of ETC complexes were determined in isolated cardiac mitochondria, as previously described . BrieflyCitrate synthase activity was determined by measuring coenzyme A formation at the Thermo Scientific GENESYS™ 10S UV-Vis spectrophotometer and was expressed as nmol oxaloacetate/min per mg protein [ protein .2O2 to produce the highly fluorescent molecule, resorufin, was used for measurement of ROS levels in isolated mitochondria. Mitochondria were incubated with 100 μM Amplex Red for 15 min, and the fluorescence intensity was quantified using a Spectramax M3 plate reader  at an excitation of 460 nm and emission of 490 nm.Amplex Red , a dye that reacts with Hμg/well) of protein were loaded onto 10% SDS-PAGE gels, run, and transferred onto Amersham Hybond ECL nitrocellulose membranes . The membranes were immunoblotted with AMPK, P-AMPKα1Thr172 , PPARα, and P-PPARαSer21 . The signals were visualized using Thermo Scientific Pierce ECL Western Blotting Detection reagents  at the VersaDoc 3000 Gel Imaging System .Protein concentration in homogenate and mitochondria was determined by the Bradford assay . Equal amounts . The immunoprecipitated complexes were washed and, then, subjected to SDS-PAGE, followed by immunoblotting using antibodies for CyP-D  or PPARα.Protein samples were incubated with anti-PPAR t-tests. Differences were considered to be statistically significant when P < 0.05.Data are presented as means ± SE. Differences among groups were compared by two-tailed Student'sP < 0.05) in the IR group compared to Sham-operated rats. Treatment with A-769662 and/or SfA significantly prevented the IR-induced increase of the HW/BW ratio (The heart-to-body weight ratio (HW/BW) was increased by 24% (BW ratio .P < 0.01), 33% (P < 0.05), and 49% (P < 0.05) less in IR + A-769662, IR + SfA, and IR + SfA + A groups, respectively, compared to the IR group. Interestingly, SfA alone did not reduce infarct size as much as the other two treatments (A-769662 and SfA + A-769662). Analysis of cardiac function demonstrated that rats subjected to IR had a 51% and 55% (P < 0.01 for both) lower cardiac output and ejection fraction, respectively, than the Sham-operated counterparts  increase in P-AMPKThr172 levels in IR hearts. Neither treatment with A-769662 nor treatment with SfA had any effects on IR-induced AMPK phosphorylation. However, simultaneous treatment with SfA and A-769662 returned the expression of P-AMPKThr172 to the level shown in Sham-operated hearts  in IR, IR + A-769662, IR + SfA, and IR + SfA + A, respectively, compared to the Sham group  increase of mitROS levels compared to the Sham group, and treatment with A-769662 and/or SfA at reperfusion blocked the IR-induced increase of mitROS levels (P < 0.01 versus Sham) increase in Ca2+-induced mitochondrial swelling (a marker of PTP opening), which was significantly attenuated in all three treatment groups . Altogether, these data demonstrate that treatment with A-769662 and/or SfA decreases mitROS levels and inhibits PTP opening.In the next set of experiments, we evaluated the effects of A-769662, SfA, or the combination on mitROS production in cardiac IR. We measured HS levels . Since eP < 0.05 for all), respectively, compared to Sham-operated animals (P < 0.05) higher, respectively, compared to the IR group. Likewise, the activities of complexes I and IV in SfA-treated hearts were 38% and 47% (P < 0.05 for both) higher, respectively, than that in untreated hearts. The combination of SfA with A-769662 did not exert additional effects on the activity of the ETC complexes. Likewise, neither treatment with SfA, A-769662 nor the combination improved IR-induced suppression of complex III activity , when compared with the Sham group. However, treatment with A-769662 and/or SfA ameliorated this interaction  in vivo cardiac IR increased phosphorylation of AMPK, which was not affected by treatments with A-769662; (iii) SfA, A-769662, or their combination reduced IR-induced mitROS levels and PTP opening in cardiac mitochondria; (iv) in vivo cardiac IR induced an interaction between PPARα and CyP-D which was attenuated by SfA, A-769662, or their combination; and (v) IR-induced decrease in ETC activity was abrogated by SfA, A-769662, or their combination. These data, for the first time, provide evidence that although both AMPK activation and PTP opening exert cardioprotective effects against in vivo IR, the simultaneous application of both therapeutic approaches (SfA + A-769662) has no synergistic effects.This study demonstrated that (i) SfA, A-769662, or their combination attenuated cardiac dysfunction and infarct size induced byActivation of AMPK by A-769662 has been previously shown to protect endothelial , neurona172 in the Langendorff-perfused mouse heart subjected to ex vivo IR [172 site of the alpha subunit; it acts through the regulatory β-subunit to allosterically activate AMPK and its downstream targets [Thr172 levels in the hearts pretreated with A-769662.Previous studies found that pretreatment with A-769662 did not stimulate phosphorylation of AMPK at Thr vivo IR . However vivo IR . It has  targets . Consist ex vivo IR, in Langendorff-perfused hearts [ in vivo cardiac IR. CyP-D is a key regulator of the PTP and has emerged as an important target for PTP inhibition [2+-activated phosphatase, calcineurin [It has been suggested that the cardioprotective effects of AMPK activation are mediated mainly through the mitochondria. Mitochondria isolated from mouse hearts expressing kinase-dead (KD) AMPK demonstrated increased hydrogen peroxide production and decreased resistance to PTP opening compared to WT counterparts . Conversd hearts  and oxidd hearts . Consisthibition , 36. Thehibition , 37–39.  ex vivo IR injury [Notably, PTP opening occurs at reperfusion, but not during ischemia, and reaches a maximum within 10–15 min of reperfusion , 40. CarR injury . LikewisR injury . In lineR injury .α, since the PPARα inhibitor GW6471 prevented cardioprotective effects of metformin against IR in rat hearts [α is one of central mediators involved in the mitochondrial transcriptional network that regulates cardiac mitochondrial metabolism and biogenesis under both physiological and pathological conditions [α seems to be a downstream target for AMPK that could modulate PTP formation. Indeed, our studies with cultured H9c2 cells demonstrated that H2O2-induced oxidative stress promoted protein-protein interactions between PPARα and CyP-D that were associated with PTP opening. Conversely, activation of AMPK prevented this interaction, suggesting that AMPK was indirectly involved in regulating pore formation by diminishing the interaction of PPARα with CyP-D [ in vivo cardiac IR induces protein-protein interactions between PPARα and CyP-D ( in vitro model of oxidative stress.Although we and others have established that the beneficial effects of AMPK activation against cardiac IR are mediated through PTP formation, the specific mechanisms associated with AMPK-induced inhibition of the PTP are still unclear. One potential mechanism may involve the indirect modulation of CyP-D. We have previously shown that the beneficial effects of metformin on mitochondria are mediated through PPARt hearts . PPARα inditions , 43. PPAth CyP-D . Likewisnd CyP-D , and preα. Inhibition of the PTP might be due to phosphorylation of GSK-3β, a downstream target of AMPK activation. Recent studies demonstrate that A-769662 increased the phosphorylation of GSK-3β, inhibiting PTP formation [Our data also indicate that the mechanism underlying the protective action of A-769662 is not associated with phosphorylation of PPARormation  and reduormation  in cardiormation , 45 can ormation . Recent ormation . Howeverormation .In summary, combination of A-769662 and SfA exerted no additional protective effects on cardiac function, mitochondrial ETC activity, PTP opening, or mitROS levels compared to individual treatments. On the other hand, it is difficult to make conclusion on the synergistic effect of A-769662 and SfA as treatment with each compound returned the changes observed in IR to the Sham level for most parameters. Further studies are needed to elucidate the synergistic effect of AMPK activation and PTP inhibition and understand the molecular mechanisms of cardioprotection induced by the AMPK/PTP pathway.


JMP will be open access, therefore complying with the open access policies of funders including the Howard Hughes Medical Institute [It is my pleasure to welcome you to the new Journal of Molecular Psychiatry – JMP! Molecular Psychiatry is a rapidly expanding field and there are high hopes that its findings will improve the condition of patients suffering from psychiatric disorders in terms of diagnosis, prognosis and therapy. There is only a limited number of journals specialising in this exciting area, and we believe that a modern internet-based electronic journal fully dedicated to the open-access principle with a thorough and efficient peer-review process and without space restrictions, will serve well the communication and publication needs of the scientific community. All articles published in stitute , NIH [2stitute .JMP is authored by Eric Nestler [We are proud that one of the first publications in Nestler , who - tWhile the term “molecular psychiatry” is widely used, surprisingly little has been published about its meaning and conceptualisation. Many seem to use the term as a more contemporary synonym for “biological psychiatry”. However, “biological psychiatry” usually represents a quite reductionist view of mental health and psychiatric disorders as phenomena which can and should exclusively be understood and explained in a mechanistic way based on neuroscience and pathophysiology. Thus, human behaviour is interpreted as the result or simple metaphenomenon of processes occurring on the cellular, genetic and molecular level. Unfortunately, this does not reflect the reality of clinical practice and the humanistic roots of psychiatry which are equally important as its biological aspects. It is one of the great achievements of molecular psychiatry to unravel the oversimplification of many theories in biological psychiatry and to open our eyes to fundamental processes such as gene-environment interaction which enable us to integrate even psychotherapeutic and social concepts of mental health into a new holistic and integrative psychiatry. Therefore, we are planning to not only publish high-quality research based on molecular neuroscience, but also reviews of mental health research in the context of Molecular Psychiatry.JMP and are proud of what we have achieved. The following publications prove that JMP already is a great success.I am very grateful to the editorial board  consisti


Electron-phonon coupling is a fundamental inelastic interaction in condensed matter and in molecules. Here we probe phonon excitations using quantum interference in electron transport occurring in short chains of anthraquinone based molecular junctions. By studying the dependence of molecular junction’s conductance as a function of bias voltage and temperature, we show that inelastic scattering of electrons by phonons can be detected as features in conductance resulting from quenching of quantum interference. Our results are in agreement with density functional theory calculations and are well described by a generic two-site model in the framework of non-equilibrium Green’s functions formalism. The importance of the observed inelastic contribution to the current opens up new ways for exploring coherent electron transport through molecular devices. Interaction between electrons and phonons (el-ph) is an ubiquitous process with fundamental as well as practical importance in systems ranging from superconductors to power dissipation in electronic devices. Molecular junctions are ideal test systems for studying el-ph interaction, since the influence from individual vibrational modes with well-defined energies can be observed in the current running through the device. However the inelastic signal from el-ph interaction is usually small compared to the elastic (non-interacting) contribution to the current. In certain molecules, the elastic current is dramatically suppressed due to destructive quantum interference, as recently demonstrated experimentally and theoretically for e.g. anthraquinone (AQ) based molecular junctions12345678101112133151617In this work we present measurements of short chains of anthraquinone based molecular layers, showing QI effect, embedded in solid-state devices. We realize highly controlled current and conductance measurements of such junctions in a large voltage range and with temperatures varying from 10 to 300 K. We are hereby able to use the QI effect in the AQ layer to study the el-ph interaction by measuring very large inelastic signals, in agreement with theoretical predictions15152012I and the differential conductance V using a low noise current amplifier and a standard homodyne detection at different temperatures ranging from 8.5 K to 275 K. A two probes measurement setup is used, the junction resistance (~MΩ) being much higher than the characteristic impedance of the connection lines (~50Ω). We present here results obtained on three different samples, hereafter referred to as A, B and C.Junctions were made in a cross-bar geometry by embedding a ~8 nm-thick AQ grafted molecular layer between two metallic electrodes made of a Ti(2 nm)/Au(50 nm) bilayer8T curves show an almost parabolic behavior.π and σ-contributions to the transport. Transport calculations using a fully atomistic description of the electrodes support the use of the simple wide-band model  calculations on AQ chains. odel see .π-type states (red curves), the transmission function shows a clear reduction over several orders of magnitude, signature of the destructive QI effect. By adding the σ-states  for a chain of 4-AQs (a) is essentially the same as the transmission obtained for a 8-AQ chain (b). Similar correspondence is found when the σ coupling is included. This indicates that the electron transport across the AQ layer is relatively insensitive to the exact number of AQ molecules in the chain.We calculate the Hamiltonian and overlap matrices for an isolated molecule using the ATK packageγ to the right and left electrodes, while site 2 of energy t to the first site. The model well reproduces a node in the electronic transmission functionThe simplest model capturing the quantum interference effect in molecular junctions is a “two-site” model introduced in refs In The total current for an interacting electron system is calculated using the Meir-Wingreen formula15wherewith Each time the voltage t and γ parameters affect the shape of the conductance curve acting mostly on the width of the anti-resonance in the transmission function. The phonon excitation modes t and γ and for the set t = −2.4 eV  and γ = 0.4 eV  and scaling factors of 125, 72 and 158 respectively. On average we introduce phonon modes in the energy range 5 meV–200 meV for each sample. A complete list of mode energies and respective couplings for the three samples is given in the On the basis of the described approach we fit simultaneously the T data are nicely reproduced in the temperature range of interest as well as the The The quality of the fit at low voltage is confirmed by the very good agreement between experiment and theory at higher temperatures as shown in −1), 10 meV (83 cm−1), 21 meV (167 cm−1), 51 meV (408 cm−1), 60 meV (486 cm−1), 77 meV (620 cm−1), 102 meV (820 cm−1), 110 meV (885 cm−1), 131 meV (1054 cm−1), 180 meV (1454 cm−1) and 183 meV (1474 cm−1)3 based molecular junctions with a similar cross-bar geometryThe common phonon modes listed in In conclusion, we have demonstrated that quantum interference effect can probe phonon excitations in short chains of anthraquinone based planar junctions. We show that the opening of inelastic transport channels by phonon excitations is visible in the conductance of the molecular junctions due to the reduction of the elastic current by quantum interference. A quantitative analysis based on a two-site model allows to unravel clear signatures of el-ph interaction in electronic transport whose energies are consistent with previously reported values. The dominant role of inelastic contributions to the current opens the way towards new spectroscopic methods for molecular conductors taking advantage of the coherent transport of electrons and towards molecular devices driven by external inelastic signals such as photonic excitations.μm2. The bottom and top electrodes are made of a 2 nm Ti/50 nm Au bilayer. The Ti layer improves Au adhesion on the Si/SiO2 substrate and reduces Au diffusion through the molecular layer. The base electrode is obtained by UV-lithography followed by e-beam evaporation in a base pressure of ~10−8 mbar. The AQ layer is then grafted by the method of electroreduction of the corresponding diazonium salt8−8 mbar. Such procedure makes sure that the molecular layer is not exposed to any chemical treatment after its grafting, preserving its quality and avoiding contaminations.Junctions were made using conventional micro-fabrication techniques in cross-bar geometry8−3 M in ACN solution with 0.1 M of −1. After the first cycle characterized by an irreversible wave corresponding to the reduction of diazonium salt, the subsequent scans do not exhibit this behavior indicating the covalent grafting of gold with other aryl diazonium compounds3436G) of AQ was determined by the charge integration under the cyclic voltammetry (CV) peaks Q is the amount of charge consumed, n is the number of electron involved F is the faraday constant and A is the area of electrode). The estimated surface coverage of AQ was around 1.5 × 10−9 mol cm−2 for Fe(CN)63-/4- redox couple by cyclic voltammetry. For an effective electron transfer process, Fe(CN)63- ions should interact with gold electrodeK3[Fe(CN)6] solution shows that for 20th cycles the CV response of redox probe is completely suppressed.The electroreduction method adopted to graft the AQ layer on the base electrode of the molecular junctions32How to cite this article: Bessis, C. et al. Probing electron-phonon excitations in molecular junctions by quantum interference. Sci. Rep. 6, 20899; doi: 10.1038/srep20899 (2016).