Aim: Incarcerated gravid uterus is a rare obstetrical complication that leads to adverse outcomes, especially if the uterus remains incarcerated and the condition goes undiagnosed until delivery. However, there is no consensus regarding the optimal management of this complication because of its rarity. In this study, we aimed to elucidate the incidence of incarcerated gravid uterus, as well as its natural courses and perinatal outcomes. Methods: We retrospectively reviewed medical records of patients who had incarcerated gravid uterus and managed at Osaka City University Hospital between April 2011 and March 2021. Incarcerated gravid uterus was defined as a retroverted or retroflexed uterus after 16 weeks of gestation. Results: There were 14 incarcerated cases among 6958 pregnant women, and 13 of them had some kind of gynecological complication and/or history. Spontaneous resolution of incarcerated gravid uterus after 16 gestational weeks was observed in six cases before the late second trimester and five cases at the late second trimester to early third trimester. Three cases remained incarcerated at term or near-term. One case with adenomyosis had severe abdominal pain, although it was difficult to ascertain whether the cause of pain was triggered by adenomyosis and/or incarceration. One case was misdiagnosed as placenta previa, and the uterine cervix was subsequently injured during cesarean delivery, resulting in massive hemorrhaging. Conclusions: Approximately 1 in 2300 pregnancies continued to be in an incarcerated condition at term or near-term, and 78.5% of cases showed a spontaneous resolution after 16 weeks of gestation. Expectant management with careful attention to the incarcerated gravid uterus may be one option in situations where there are no severe symptoms related to the incarceration itself. Uterine retroversion or retroflex is observed in 15% of pregnant women during the first trimester, and a majority will spontaneously resolve before 14 weeks of gestation . ProposeSome authors suggest the use of manual reduction for the incarcerated uterus after 16 weeks of gestation. However, these procedures require hospitalization and invasive stress, including anesthesia and even laparotomy ,5,8. MorIn this study, we aimed to elucidate the incidence, natural courses, and perinatal outcomes for incarcerated gravid uterus.The medical records of pregnant women who had incarcerated gravid uterus and who delivered at Osaka City University Hospital between April 2011 and March 2021 were retrospectively reviewed. All patients gave their informed written consent, and the study protocol was approved by the institutional review board .Incarcerated gravid uterus was defined as a retroverted or retroflexed uterus after 16 weeks of gestation. We obtained medical information as follows: age, gravida/parity, mode of conception, gynecological complication and history, diagnosed week of incarceration, weeks of estimated resolution, history of characteristic pregnancy course, and delivery outcomes. The estimated gestational week of resolution was indicated by the duration between the gestational week of the last recognition of an incarcerated uterus and the gestational week of the confirmation of resolution. The resolution was confirmed by vaginal examination, MRI, and/or ultrasound evaluation.During the observational period, there were 6958 deliveries at Osaka City University Hospital, and no cases were referred to our hospital with the diagnosis of incarcerated gravid uterus. Incarcerated gravid uterus after 16 gestational weeks was diagnosed in 14 cases, and spontaneous resolution was recognized in 11 cases. The incidence of incarcerated gravid uterus after 16 gestational weeks and spontaneous resolution in the observed period were 0.2% (14/6958) and 78.5% (11/14), respectively. In all of the cases except for one, which was not diagnosed until cesarean delivery, the initial finding of suspected uterine incarceration was a non-palpable and non-visualized cervix upon vaginal examination.We describe three cases in detail, all of which showed characteristic findings and pregnancy courses due to incarceration. Case 2, who was complicated with adenomyosis, was transferred to our hospital due to severe abdominal pain with elevated inflammation signs at 20 weeks of gestation , and tramadol hydrochloride, acetaminophen, and pentazocine hydrochloride were needed to control her abdominal pain. The incarcerated uterus was identified by MRI, and was found to have an enlarged fundus with adenomyosis a. AntibiCase 13, conceived by assisted reproductive technology, was strongly suspected to have severe adhesion of the Douglas’s pouch as a result of a previous history of peritonitis, an operation for endometrial ovarian cysts, and a tubal pregnancy. MRI showed placenta previa at the cranioventrally stretched internal cervical ostium at 33 weeks of gestation a; howeveCase 14 had undergone cesarean delivery with a misdiagnosis of placental previa without the prior recognition of incarceration. As a result, the uterine cervix was incised by 3/4 of its total circumference, and the baby was born through the posterior uterine wall. Although the estimated blood loss amounted to 4.8 L, the amputated lesion of the cervix was successfully repaired by one-layer single knot suturing using 1-0 Vicryl, and the post-operative course was uneventful. This patient experienced two subsequent spontaneous pregnancies that resulted in uncomplicated pregnant courses, and cesarean deliveries were performed at term without incarceration.The other 11 cases did not experience any severe abdominal pain, although they did complain about the frequency of urination and abdominal discomfort, which were thought to be within physiological ranges and did not necessitate any medical treatment.Our study demonstrated that roughly one pregnancy in 2300 deliveries remained complicated with incarcerated uterus, at term or near term, if manual reduction was not performed. In addition, an antenatal diagnosis was correctly made in 92.8% of cases, and spontaneous resolution after 16 gestational weeks was observed in 78.5%. However, severe operative injury was experienced in one case misdiagnosed as placenta previa. As far as we know, our study is the first to include such a large number of patients and to report on the natural courses of incarcerated gravid uterus after 16 weeks of gestation without any manual reduction.Complications that arise from an incarcerated uterus are thought to result in adverse perinatal outcomes ,5,6,7,8.Four cases of spontaneous resolution in the third trimester have been reported so far ,14,15,16The limitations of this study are the retrospective nature of the study design and the fact that the number of patients was too small to elucidate concrete evidence. Furthermore, we did not validate the efficacy of manual and/or passive reduction of the incarcerated gravid uterus . HoweverIn conclusion, the first finding to suspect incarcerated gravid uterus is the difficulty in recognizing the uterine cervix by vaginal examination. For such cases, MRI and ultrasound should be undertaken to confirm the diagnosis. In cases where there are no severe symptoms, expectant management with careful monitoring might be an option. Our findings will provide helpful information for obstetricians in clinical practice.


A key goal of disease surveillance is to identify outbreaks of known or novel diseases in a timely manner. Such an outbreak occurred in the UK associated with acute vomiting in dogs between December 2019 and March 2020. We tracked this outbreak using the clinical free text component of anonymised electronic health records (EHRs) collected from a sentinel network of participating veterinary practices. We sourced the free text (narrative) component of each EHR supplemented with one of 10 practitioner-derived main presenting complaints (MPCs), with the ‘gastroenteric’ MPC identifying cases involved in the disease outbreak. Such clinician-derived annotation systems can suffer from poor compliance requiring retrospective, often manual, coding, thereby limiting real-time usability, especially where an outbreak of a novel disease might not present clinically as a currently recognised syndrome or MPC. Here, we investigate the use of an unsupervised method of EHR annotation using latent Dirichlet allocation topic-modelling to identify topics inherent within the clinical narrative component of EHRs. The model comprised 30 topics which were used to annotate EHRs spanning the natural disease outbreak and investigate whether any given topic might mirror the outbreak time-course. Narratives were annotated using the Gensim Library LdaModel module for the topic best representing the text within them. Counts for narratives labelled with one of the topics significantly matched the disease outbreak based on the practitioner-derived ‘gastroenteric’ MPC (Spearman correlation 0.978); no other topics showed a similar time course. Using artificially injected outbreaks, it was possible to see other topics that would match other MPCs including respiratory disease. The underlying topics were readily evaluated using simple word-cloud representations and using a freely available package (LDAVis) providing rapid insight into the clinical basis of each topic. This work clearly shows that unsupervised record annotation using topic modelling linked to simple text visualisations can provide an easily interrogable method to identify and characterise outbreaks and other anomalies of known and previously un-characterised diseases based on changes in clinical narratives. One of the aims of veterinary surveillance is to rapidly detect the emergence of new diseases. Such emerging diseases might be expected, relatively early in an outbreak, to be reflected in changes of clinical syndromes described in veterinary clinical narratives  and syndIn January 2020, the authors became aware of anecdotal reports of a potential increase in the numbers of dogs attending veterinary practices with an acute vomiting syndrome . Using eWhilst this surveillance approach provided a means to identify this outbreak, it was largely predicated on records having been previously annotated by the attending clinician for one of ten pre-determined syndromes with subsequent analysis of selected data. Other classification systems exist for annotation of veterinary clinical notes covering a much wider range of diagnoses and syndromes ,7 but maMethods to circumvent the need for manual clinical coding that are based on pattern-matching for specific key words and combinations of key words present in free-text narratives require careful management of and frequent phenomena of abbreviation, misspelling and negation ,12. AddiDeveloping supervised annotation systems to detect outbreaks can also be challenging where data from actual disease outbreaks is not available or where a new syndrome has emerged. Veterinary examples addressing this have included injecting datasets with virtual cases based on expert-derived clinical criteria  or basedA system that allows truly unsupervised generation of annotations of EHRs based on clinical narrative content could allow detection of outbreaks of both known and novel syndromes in a timelier manner than rule based and trained machine-learning solutions.Topic modelling is an unsupervised approach that assumes collections of documents can be categorised as having content with a probability of relating to specific topics where each topic is represented by the probability of any given word from the full corpus of text being present within that topic . This meThe Small Animal Veterinary Surveillance Network (SAVSNET) was established in 2010 to collect electronic health records (EHRs) at scale from a network of sentinel veterinary practices across the UK . Each EHWe analysed a corpus of SAVSNET clinical narratives for dogs only. Records were stored and manipulated using Python  Django  topic modelling and collocation analysis (n-gram discovery) were performed using the Gensim library .A training set of 200,000 narratives from EHRs dated between 1.3.2019 and 1.10.2019 was selected from the corpus. These narratives were tokenised at white space and non-word character boundaries and part-of speech tagged using NLTK, retaining noun, verb, adjective and number tokens. Common word collocations  were identified using the Gensim Phrases method and narratives were reduced to ‘bag of words’ documents. The Gensim Latent Dirichlet Model class can accept a topic count as a parameter prior to creating the topic model. This topic count was chosen on the basis of evaluating the ‘u_mass’ coherence property of the Gensim Coherence class using topic models created using between 2 and 100 topics.The best suited topic count was used to generate a topic model which was used to analyse all narratives in the corpus after 1st January 2016 (a time point after which the number of veterinary practices participating in SAVSNET was comparatively stable). The probability of each topic was estimated for each narrative. For surveillance-testing, narratives were finally annotated with a single topic where the model assigned a probability of over 0.5 for that topic (i.e. that topic was more likely than any of the others combined). Where no topics exceeded a probability of 0.5 for a narrative, the narrative was annotated as ‘not classified’. Topic counts were assessed to evaluate their degree of concordance with existing MPCs as recorded by participating practitioners. An adjusted mutual information score was calculated for each topic with each MPC using the SciKit Learn using the adjusted_mutual_info_score metric . All modTo evaluate the potential for the final model to detect outbreaks of other given syndromes, six simulated outbreaks lasting 60 days were created using existing narratives from EHR labelled by veterinary surgeons as having specific MPCs . For each day of each simulated outbreak a sample of 100 EHRs  with a given MPC was randomly selected from all dog consultations in the full SAVSNET database. These samples were inserted into a copy of the full database with timestamps adjusted to fit within the 60-day simulated outbreak for that MPC. All records from these simulated outbreaks database were then annotated using the topic model as described above and MPC counts were then visually compared with record counts for each topic.Daily counts for clinical narratives annotated with the gastroenteric MPC were plotted as 7-day rolling averages and visually compared to narrative counts annotated with topics from the topic model. Daily narrative counts labelled with gastroenteric MPC and each topic were compared with Spearman’s rank correlation both for one year preceding and during the outbreak period.Data for the topic best matching the outbreak was plotted with trend lines calculated using a Bayesian binomial generalised linear model trained on weekly prevalence between 2014 and 2019 , allowinIn order to infer topic meaning, topic word-content was evaluated using word clouds generated using the WordCloud module in python . For a mEvolution of the topic model in terms of token-weightings for each topic over time was assessed using dynamic topic modelling . A samplWhen evaluating the most appropriate topic count to use for this study, topic coherence score improved notably between 2 and 30 topics . Topic mUsing the 30-topic model developed on 200,000 records to annotate the 3,499,566 records in the dataset, only 982,333 (28.1%) were allocated a primary topic (where its topic probability exceeded 0.5) with individual topics labelling between 46 (0.001%) and 114034 (3.258%) narratives  When narFor simulated outbreaks, increased cases were clearly visible for the relevant MPCs but only elicited visibly detectable signals for topic_17 (correlating with injected gastroenteric narratives and topic_6 correlating with injected respiratory narratives .Only topic_17 counts showed a similar rise to gastroenteric MPC counts during the period of the outbreak . To compDaily narrative counts matching topic_17 and gastroenteric MPC were distributed similarly with a Spearman correlation of 0.927(95%CI: 0.911–0.940) prior to the outbreak  which roBased on word-cloud assessment, key words contributing to topic_17 included series of words describing gastrointestinal function including gastrointestinal clinical signs and their abbreviations  as well as words relating to gastrointestinal functions  and words relating to time intervals  . Using LTopic_6 was represented by words relating to cough and heart disease and topics 18 and 22, which were highly represented in pruritus MPC cases were characterised by words relating to ear problems (topic 18) and allergic skin disease , nail-overgrowth (topic_5), reproductive disease (topic_10), ocular disease (topic_11), body weight issues (topic_21), lameness (topic_26), dental disease (topic_28). In addition, there were topics that appeared to describe preventative health visits (topic_1) and routine clinical examination findings (topic_24). There were some topics that were not immediately interpretable .Topic evolution during the outbreak period, evaluated using dynamic topic modelling seeded with the initial topic model revealed an increasing priority of words relating to vomiting  within the gastroenteric topic . Other wTopic modelling has been used in the medical literature to identify syndromic features of clinical records , track dOn assessment of records annotated by clinicians for a limited set of MPCs, it was clear that specific MPCS were associated with varied distributions of topics. In the case of the gastroenteric MPC, topic_17 was the majority topic but other MPCs had also majority topics, thus respiratory, trauma and post-op MPCs were, in the majority annotated with topic_6, topic_26 and topic_13 respectively.Clearly the criterion for apportioning a topic were set rather rigorously leading to many narratives remaining unclassified with respects to topic. Additionally, most narratives were associated with additional topics, albeit with lower probabilities than that of the one with which was their majority topic. Considering these lower probability topics may well provide additional or complementary signals regarding presentation for multiple syndromes and will be evaluated in further studies. That said, even under the conditions set in the current study, the gastroenteric MPC was matched by topic_17, with most of the remaining being unclassified, suggesting a very distinct terminology used for this subset of gastroenteric MPC narratives. This is perhaps not surprising given that gastroenteric disease is most frequently associated with a limited combination of clinical signs (vomiting and diarrhoea). The limited cover of some MPCs by single majority topics may reflect the diversity of clinical syndromes associated with the MPC. For instance, with tumour MPC, varied clinical presentations (and presumably topics) would reflect the variety of sites affected by tumours with some common features  reflected in one of the topics only (topic_9). Likewise, the ‘other unwell’ MPC was inevitable to comprise many varied clinical syndromes and thus different topics.Only topic_17 showed any evidence of a change in daily record counts when records were screened over the period of the natural outbreak with daily topic_17 counts correlating significantly with gastroenteric MPC counts. Furthermore, topic_17 narrative count correlated more strongly with gastroenteric MPC count during the outbreak implying topic_17 was a closer match for narratives describing the outbreak-syndrome than for normal background gastroenteric disease. The smaller positive correlation identified between gastroenteric MPC and other topics probably reflected weekly variation of consultation counts (few on Saturdays and even fewer on Sundays) affecting all topics and MPCs.It was critical to see whether an outbreak-detection model would identify the outbreak in topic-annotated records as well as it could in MPC-annotated records. Using a Bayesian binomial generalised linear model previously used to identify outbreak-candidates  we were in-silico outbreaks, suggest this was not unique to gastroenteric disease (topic 17), but that outbreaks of respiratory (topic 6) and trauma/lameness (topic 26) might also be detectable with such a system. However, not all simulated MPC outbreaks were detected. For example, pruritus appeared to have two major topic annotations (topic 18 and topic_22) there was no obvious change in narrative counts for the injected records. This probably reflects the fact that pruritus narratives form a larger proportion of the SAVSNET corpus, were divided between two topics and have a marked seasonality peaking in spring/summer Please clarify whether this [conference proceeding or publication] was peer-reviewed and formally published. If this work was previously peer-reviewed and published, in the cover letter please provide the reason that this work does not constitute dual publication and should be included in the current manuscript.http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see In your revised cover letter, please address the following prompts:a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail  and who has imposed them . Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see We will update your Data Availability statement on your behalf to reflect the information you provide.4. Thank you for stating the following in the Acknowledgments Section of your manuscript:SAVSNET team members Beth Brant, Susan Bolanand Steven Smyth.]Additionally, because some of your funding information pertains to [commercial funding//patents], we ask you to provide an updated Competing Interests statement, declaring all sources of commercial funding.http://journals.plos.org/plosone/s/competing-interests.  If this statement is not true and your adherence to PLOS policies on sharing data and materials is altered, please explain how.In your Competing Interests statement, please confirm that your commercial funding does not alter your adherence to PLOS ONE Editorial policies and criteria by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” as detailed online in our guide for authors  Please include the updated Competing Interests Statement and Funding Statement in your cover letter. We will change the online submission form on your behalf.http://journals.plos.org/plosone/s/competing-interestsPlease know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/supporting-information.5. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: [Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Partly**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: I Don't Know**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The authors used topic model to mine text data to mine veterinary clinical narratives. They find that one of the topic mixture probabilities (topic 17) over time are indicative of gastroenteric presenting complaint (MPC). Using Bayesian binomial linear model, they confirm that the finding is statistically significant. The study show that it is possible to use topic model to detect outbreak of novel disease. Although there is no methodological innovations in topic modeling and the analyses are standard topic model analysis, it is a novel application and an interesting angle that the authors took in looking into the outbreak using topic models.Major comments:1. The authors were modeling temporal changes of the text data using LDA from the standard Gensim Library. Authors should use dynamic topic model instead to capture the changes of topics over time.2. Evaluating only on the topic coherence in choosing the topic number is not sufficient because it only evaluates each topic separately not across topics. You can have coherent topics but the topics can all look the same. A proper metric is called topic quality that combines topic coherent and topic diversity .3. Authors mention computational overhead caused by choosing more topics. This is possibly because they were using the full-batch LDA training on 3.5 million records in their data. LDA can be inferred by stochastic variational inference using minibatch of the records . This should be implemented in the Gensim Library.4. I am confused on whether the model was trained on real data and then applied to the simulated data or trained and applied directly on the simulated data. It seems that the former is true. I would argument that the latter is more realistic because in real world application, you can’t train on text in the absence of the outbreak at least not in the same time interval.5. Figure 2 and 3a are in very poor quality. A more compact display is needed. Otherwise, Figure 2 and 3a should be in supplementary.Minor comments:6. The flow and the format of the paper makes it sometimes hard to follow. In particular, in Results section, figure legends were inserted in the middle of the text with large margin around them .7. The authors call the veterinary clinical narratives of dogs as electronic health records (EHR). I wonder to what extent this is the case. There is no standardized data such lab tests LOINC or RxNorm prescription.Reference:D. Mimno, H. M.Wallach, E. Talley, M. Leenders, and A. McCallum. 2011. Optimizing semantic coherence in topic models. In Conference on Empirical Methods in Natural Language Processing.Reviewer #2: The objective of the study was well motivated as to the use of topic modelling to classify EHR into categories that would allow for surveillance. What was not well explained is the criteria and definition of disease outbreak. The point was made that the utility of labelling would be to facilitate detection of outbreaks. When in the development of the outbreak should the system be making the decision that an outbreak is present? If it waits until the outbreak is at its worst then obviously this would mean that there would be little utility for prevention or control. On lines 186-8, an outbreak is equated to an increase in gastroenteric MPC but that is a very vague definition and does not take into account many different sources of variation . These sources of variation are what makes syndromic surveillance so difficult because of the problem of false positives.It was also mentioned that there is a great deal of uncertainty in topic modelling with regards to negatives - this is indeed a problem and I did not clearly see any explanations for how this was mitigated in this study. The other large issue with natural language data sets is misspellings, short forms, etc. From my own experience with human hospital and veterinary clinic records points to a huge variation of spellings unless the doctor/vet is constrained or there is post-processing to correct spellings or expand abbreviations (which is only possible for a known set of abbreviation variations). I did not see where it was explained about the processing of the data from the EHR and since I am not familiar with the UK systems for this type of data collection I am confused as to whether this is actually an issue.I was also unclear as to what the effect was if the EHR was describing more than one condition of interest. It is also unclear if the reason that this topic modelling works well is because GI has mainly 2 symptoms (vomiting and diarrhoea). It was briefly discussed with respect to the overlap between cardiac and respiratory symptoms and diagnoses but it does leave the reader waiting for a subsequent study that looks at this question.I would caution against justifying the choice of topics (30) because of computational cost without putting this into perspective. In other words, what type of computational system was used and how long did it take to produce results.I did find the use of unsupervised methods appropriate and useful for this task and think that this study is an excellent first step in a more comprehensive use of this technique.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  18 Jul 2021Academic editor comments1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found athttps://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf andhttps://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.....Response:Apologies for incorrect formatting, we have reviewed the document and hope we have corrected any deviations from the requested format2. We noted in your submission details that a portion of your manuscript may have been presented or published elsewhere.Please clarify whether this [conference proceeding or publication] was peer-reviewed and formally published. If this work was previously peer-reviewed and published, in the cover letter please provide the reason that this work does not constitute dual publication and should be included in the current manuscript......Response:Figure 6c is very similar to a figure in a peer reviewed publication . In the current paper, this panel shows the trajectory of a disease outbreak which is described in the Radford et al paper. It is used as a comparison to the signal detected by topic modelling which is under discussion in the current paper. The Radford paper is primarily reporting the disease outbreak. In the current paper, we are illustrating how a novel method of automated record annotation could have mirrored the outbreak report in the Radford et al paper. We are not stating that we have identified the outbreak using the included figure, rather, that its inclusion clearly illustrates the utility of topic modelling to perform the same task.http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see In your revised cover letter, please address the following prompts:a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail  and who has imposed them . Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.savsnet@liverpool.ac.uk or via our web-based data-access portal (https://savsnetvet.liverpool.ac.uk/DAPP). Further details of the data user agreement completed though this portal can be supplied if required for review......Response: SAVSNET data is collected in as anonymised form as possible, tabulated owner and pet names are not collected, neither are tabulated addresses or telephone numbers. However, the clinical free text data may include versions of these information. SAVSNET has automated redaction of such data to create deidentified text in the vast majority of cases, however, no deidentification software is 100% and some identifiers may get past this step, particularly unusual pet names which might identify the owner and as such the free text narratives are considered sensitive and are only shared through a data application process that commits users to appropriate curation of any data shared. The data access process is straightforward and can be initiated through e-mail approach to http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see We will update your Data Availability statement on your behalf to reflect the information you provide.4. Thank you for stating the following in the Acknowledgments Section of your manuscript:We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:https://www.dogstrust.org.uk .....Response:We have removed mentions of funders from the Acknowledgments section and the funding statement remains the sameAdditionally, because some of your funding information pertains to [commercial funding//patents], we ask you to provide an updated Competing Interests statement, declaring all sources of commercial funding.http://journals.plos.org/plosone/s/competing-interests. If this statement is not true and your adherence to PLOS policies on sharing data and materials is altered, please explain how.In your Competing Interests statement, please confirm that your commercial funding does not alter your adherence to PLOS ONE Editorial policies and criteria by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” as detailed online in our guide for authors Competing Interests statement.....Response: We have not received commercial funding for this project. we presume the concern is that data contributors include commercial companies. In this case the companies include VetSolutions and Teleos whose practice management systems are modified to allow SAVSNET data collection and CVS who are corporate group of vet-practices from whom we collect data. None of these groups provide funding for the project or direct trajectory of research or publication and as such we have removed the word ‘support’ from the acknowledgement section. Please let us know if this requires further clarification.Please include the updated Competing Interests Statement and Funding Statement in your cover letter. We will change the online submission form on your behalf.http://journals.plos.org/plosone/s/competing-interestsPlease know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/supporting-information.5. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: .....Response:Figure 2 and Figure 3a have been converted to supporting information as advised by reviewer#1 and along with captions fro these captions for supporting information data-files have been appended to the manuscript.Reviewers Comments -Reviewer #1:The authors used topic model to mine text data to mine veterinary clinical narratives. They find that one of the topic mixture probabilities (topic 17) over time are indicative of gastroenteric presenting complaint (MPC). Using Bayesian binomial linear model, they confirm that the finding is statistically significant. The study show that it is possible to use topic model to detect outbreak of novel disease. Although there is no methodological innovations in topic modeling and the analyses are standard topic model analysis, it is a novel application and an interesting angle that the authors took in looking into the outbreak using topic models.Major comments:1. The authors were modeling temporal changes of the text data using LDA from the standard Gensim Library. Authors should use dynamic topic model instead to capture the changes of topics over time. .....Response:The main aim of our paper was to explore the feasibility of using topic modelling to identify a potential outbreak. For that, and as a first step, static models were considered a reasonable approach. Indeed, the signal identified using the ‘static’ model is demonstrated to be useful by its close mapping to the other outbreak metric (MPC). Still, following the reviewer’s comment, we have added to the paper how a dynamic topic model can be used to allow observers to infer potential evolution of the content of a given topic over time. We are currently evaluating a variety of other dynamic topic modelling approaches and topic modelling using tools such as BERTopic and Tomotopy, but we thought that a systematic evaluation of these is outside the scope of the current manuscript.2. Evaluating only on the topic coherence in choosing the topic number is not sufficient because it only evaluates each topic separately not across topics. You can have coherent topics but the topics can all look the same. A proper metric is called topic quality that combines topic coherent and topic diversity . .....Response:This is a fair comment. However, for the purpose of monitoring for emergence of a syndrome signalling an outbreak, review of the topic contents would quickly identify ‘vacuous’ topics (we have added mention of these to the manuscript) meaning that the model can err on the side of too many topics while still being useful (as it was in this case). 3. Authors mention computational overhead caused by choosing more topics. This is possibly because they were using the full-batch LDA training on 3.5 million records in their data. LDA can be inferred by stochastic variational inference using minibatch of the records . This should be implemented in the Gensim Library......Response:We have opted to use a smaller subset to experiment with the number of topics, which is now hopefully clearly explained in the manuscript. Computational overheads were not the main limiting factor in building the model given the number of topics.4. I am confused on whether the model was trained on real data and then applied to the simulated data or trained and applied directly on the simulated data. It seems that the former is true. I would argument that the latter is more realistic because in real world application, you can’t train on text in the absence of the outbreak at least not in the same time interval. .....Response:This is now clarified in the manuscript.5. Figure 2 and 3a are in very poor quality. A more compact display is needed. Otherwise, Figure 2 and 3a should be in supplementary. .....Response:Figure 2 has been removed with explanation in the text. Figure 3a has been replaced with a figure illustrating clustering of topics with MPCs which illustrates the topic-mpc relationship more helpfullyMinor comments:6. The flow and the format of the paper makes it sometimes hard to follow. In particular, in Results section, figure legends were inserted in the middle of the text with large margin around them . https://journals.plos.org/plosone/s/figures): .....Response:The authors accept that the placement of figure legends does disrupt the text but figure legends were placed in accordance with editorial guidelines. I wonder to what extent this is the case. There is no standardized data such lab tests LOINC or RxNorm prescription. .....Response: We indeed have access to EHR (or EPR), which contain some structured data , prescription data and clinical narrative. While the data comes from various providers and is not standardized to any particular standard, it still does represent EHR. However, we have made it clearer in text that we only use the narrative part.Reviewer comments - Reviewer #2: The objective of the study was well motivated as to the use of topic modelling to classify EHR into categories that would allow for surveillance. What was not well explained is the criteria and definition of disease outbreak. The point was made that the utility of labelling would be to facilitate detection of outbreaks. When in the development of the outbreak should the system be making the decision that an outbreak is present? If it waits until the outbreak is at its worst then obviously this would mean that there would be little utility for prevention or control. On lines 186-8, an outbreak is equated to an increase in gastroenteric MPC but that is a very vague definition and does not take into account many different sources of variation . These sources of variation are what makes syndromic surveillance so difficult because of the problem of false positives......Response:This paper seeks to illustrate that an unsupervised method can produce results comparable to supervised annotation of clinical records in the context of a disease outbreak. The exact mechanism for alerting the presence of an outbreak from this data remains to be decided and is being researched by the SAVSNET team. We have added a paragraph to the discussion alluding to this citing an elegant publication that offers a means to address this.It was also mentioned that there is a great deal of uncertainty in topic modelling with regards to negatives - this is indeed a problem and I did not clearly see any explanations for how this was mitigated in this study. .....Response:In a sense the problem of negation is ignored in the face of a signal that tracks gastroenteric disease regardless of how the topic model emerges from the data. We do not address this in the discussion because the topic model does allow identification of the outbreak regardless of how negation of those words occurs in the original textsThe other large issue with natural language data sets is misspellings, short forms, etc. From my own experience with human hospital and veterinary clinic records points to a huge variation of spellings unless the doctor/vet is constrained or there is post-processing to correct spellings or expand abbreviations (which is only possible for a known set of abbreviation variations). I did not see where it was explained about the processing of the data from the EHR and since I am not familiar with the UK systems for this type of data collection I am confused as to whether this is actually an issue......Response:The authors fully agree with this sentiment  but in effect, the topic modelling deals with this by treating all words/abbreviations/acronyms as tokens which comprise a topic agnostic of what those are. We have added detail to how tokens were generated in the methods.I was also unclear as to what the effect was if the EHR was describing more than one condition of interest. It is also unclear if the reason that this topic modelling works well is because GI has mainly 2 symptoms (vomiting and diarrhoea). .....Response:Most documents were given a greater than zero probability for more than one topic and this vector of topic probabilities will be studied in further work. For the purpose of this paper, the authors felt that the key message that an unsupervised annotation method could identify an outbreak scenario which succeeded while only looking at a single topic annotation using the topic for which a narrative had a >0.5 probability. We have added a note in the discussion regarding further, more comprehensive analysis of narrative-topic probabilities.It was briefly discussed with respect to the overlap between cardiac and respiratory symptoms and diagnoses but it does leave the reader waiting for a subsequent study that looks at this question......Response:That study is on the way alongside use of newer topic modelling techniques that articulate word-meaning more effectively and therefore create more meaningful topicsI would caution against justifying the choice of topics (30) because of computational cost without putting this into perspective. In other words, what type of computational system was used and how long did it take to produce results......Response:We have added detail regarding the modest computational capacity used for this study and hope that this spurs other investigators to consider this type of work even when high performance computing is not available.I did find the use of unsupervised methods appropriate and useful for this task and think that this study is an excellent first step in a more comprehensive use of this technique......Response:Many thanks, we feel this is very much a first step and, hopefully, one of manyAttachmentResponse to reviewers.docxSubmitted filename: Click here for additional data file. 10 Nov 2021Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs.PONE-D-21-01941R1Dear Dr. Noble,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Fernanda DóreaAcademic EditorPLOS ONEAdditional Editor Comments:I believe that this was enough to be able to track what has changed and the additions made, although as pointed out by one of the reviewers, in the future you may want to specify clearly the lines/sections where additions were made, and preferentially quote them in the response letter. Based on the acceptance recommendation from reviewer 2, plus my own judgement of how satisfactorily you answered the comments from reviewer 1, I have recommended acceptance of the paper. Although some comments remain, I deemed that another round of review would not likely cause further improvements in the current methods. I do urge you to read thoroughly through the reviewer 1 comments, whose pointers on methodological aspects of the papers can be an important consideration for future work. But I do agree with authors that for the purpose of early disease detection, the methods presented and the conclusions are sound, and therefore I recommended acceptance.Reviewers' comments:1.     We are all busy. It is difficult to find the revised content when the author simply asked that “it’s revised somewhere in the manuscript and go find it yourself”. I will appreciate if the authors write the revised part directly in their response to my comments AND indicate the page number where those revised parts appear in revised main text. Only this way can I properly and efficiently assess whether they have satisfactorily addressed my comments. This pertains to all my original comments. Please also do this in the next round of revision.2.     In answering my comment 2 about evaluating topic quality as the product of topic diversity and topic coherence rather than just topic coherence, authors did not give satisfactory answer. Please perform topic quality analysis.3.     The authors didn’t understand my comment 3. They said that they chose small subset of data to experiment with the number of topics, which IS ultimately due to the inefficient computational algorithm of the LDA they used because otherwise they don’t need to subset the data to experiment topic numbers. Therefore, I suggested using the online LDA to run on all their data not just subset.4.     For my comment 6, typically you put figures and figure legends on top or bottom of the page not in the middle of the page.5.     The revised pdf is merged with the PDF of the original submission. I only find figures from the original submission not the revised figures. 1 Dec 2021PONE-D-21-01941R1 Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs. Dear Dr. Noble:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofDr. Fernanda C. Dórea Academic EditorPLOS ONE


Current evidence indicates that more than half of all antimicrobials are used in the animal food-producing sector, which is considered a significant risk factor for the development, spread, and existence of antimicrobial resistance (AMR) pathogens in animals, humans, and the environment. Among other factors, clinical etiology and the level of knowledge, attitudes, and practices (KAP) of veterinarians are thought to be responsible for inappropriate prescriptions in the animal-source protein production sector in lower-resource settings like Bangladesh. We performed this cross-sectional study to assess factors associated with veterinarians’ antimicrobial prescription behavior and their KAP on antimicrobial use (AMU) and AMR in Bangladesh. Exploratory and multivariate logistic models were used to describe an association between knowledge, attitudes, and practices of AMU and AMR and demographic characteristics of veterinarians. The results demonstrated that when selecting an antimicrobial, there was no to minimal influence of culture and susceptibility tests and patients’ AMU history but moderate to high influence of the farmer’s economic condition and drug instructions among the veterinarians. The results also demonstrated that more than half of the veterinarians had correct KAP regarding AMU and AMR, while the rest had moderate or lower levels of KAP. The factor score analysis revealed that age, level of education, years of experience, gender, and previous training on AMU and AMR were the key influencing factors in their level of KAP. Adjusted logistic regression analysis showed that respondents’ age, current workplace, and previous training on AMU and AMR had a positive association with increased KAP. Considering the results, it is imperative to include AMR issues on vet curricula, and to provide post-education training, awareness campaigns, easy access to, and dissemination of AMR resources. Increasing the veterinary services to the outreach areas of the country and motivating veterinarians to follow the national AMR guidelines could be some other potential solutions to tackle the over-prescriptions of antimicrobials. E. coli, Salmonella spp., Enterobacter spp., Staphylococcus aureus, Pasteurella spp., Bacillus spp., and Campylobacter spp. have been isolated from Bangladeshi broilers, layers, day-old chicks, pigeons, frozen chickens, and the milk of mastitis-affected cows [Antimicrobial resistance (AMR) is a cross-disciplinary global public health threat for human, animal, and environmental health ,2,3,4,5.ted cows ,29,30,31ted cows . A studyted cows .In Bangladesh, inappropriate use of antimicrobials has led to the development of different pathogenic and zoonotic AMR microbes in the livestock sector . This crThis cross-sectional survey was carried out from April 2021 to May 2021 to investigate prescription behaviors regarding antibiotic use among vets from different areas in Bangladesh. Our target participants were livestock and poultry veterinarians who were actively engaged in veterinary practices during the study. We excluded pet practitioners, as we focused on antimicrobial resistance in food producing animals. A Google-Form-based self-administered questionnaire was designed, and a web link was distributed to veterinarians via different professional associations, personal email, university groups, social media sites, and websites.A questionnaire was developed based on a comprehensive review of the published literature in order to identify factors influencing antimicrobial prescribing behaviors and knowledge, attitudes, and practices (KAP) regarding AMU and AMR among veterinarians. The questionnaire was divided into six sections: (i) personal information; (ii) the sources of information on AMR and AMU; (iii) clinical etiological factors influencing antimicrobial selection; (iv) knowledge factors; (v) attitude factors; and (vi) practice factors regarding antimicrobial prescriptions. In the personal information section, we asked about the respondents’ age, gender, level of education, years of experience in practice, area of practice, nature of the workplace, and any training on AMR and AMU in the last year. The second section consisted of one multi-response question to capture the sources they used to obtain information on AMU and AMR. We asked ten questions (three negative and seven positive) to understand the factors that influence antimicrobial prescription decisions in the third section. Twelve questions were asked to assess the knowledge factors on AMR and AMU in the fourth section, and the measurement of each question was determined based on the self-reported responses from “good” to “no knowledge at all”. To assess the attitude factors, in the fifth section, we used a four-point Likert scale (from “strongly agree” to “strongly disagree”) and asked ten questions (three negative and seven positive). The final section consisted of twelve questions (six negative and six positive) to assess the practice factors on AMU and AMR.The preliminary draft of the questionnaire was reviewed by three expert researchers to identify ambiguity and assess content validity. After obtaining and incorporating expert feedback, the questionnaire was tested among ten respondents to check the language suitability and the appropriateness of the questions. Slight modifications of language were recorded during the pilot phase, and these modifications were addressed before data collection. The pilot responses were excluded from the current analysis.n = 5800) from the Bangladesh Veterinary Council. Similarly, to include the intern veterinarians, we collected the list of interns working in different veterinary hospitals in different Upazilas in Bangladesh. The study population included veterinarians who fulfilled the inclusion criteria of being a practitioner in either commercial poultry, livestock, or both sectors. The sample size was calculated using the Raosoft calculator (Raosoft: http://www.raosoft.com/samplesize.html?nosurvey accessed on 12 February 2021). A sample size of 377 was estimated based on a 50% response distribution, a 5% margin of error, and a 95% confidence interval. The expected response proportion of 50% was assumed because both responses and response rates were completely unknown since there are no similar previously published studies from Bangladesh. We invited 500 vets to participate in the current study and obtained a response from 436.Before inviting the veterinarians to participate in the study, we collected a list of veterinarians  EC/2019/126 (02), Date: 29 December 2019). The details of the participants were anonymous, and data confidentiality was properly maintained see . The nat® Office Excel 2010  was assigned to responses of “no influence” to “high influence” for factors influencing prescription decisions. Similar index values were used for responses “not at all” to “good” for knowledge questions, “strongly disagree” to “strongly agree” for attitudes questions, and “never” to “regularly” for practice questions. To analyze how individual participants performed overall in the knowledge, attitude, and practice categories, the sum of each participant’s answers for that particular section was calculated. Data were analyzed using the statistical software Stata/SE 16.1 . We used descriptive statistics such as frequencies and percentages. Relationships between independent samples were explored using the chi-square test to determine if there were differences among respondents’ characteristics with respect to the themes. Using the principal factor method described, we identified significant factors in the demographic characteristics and themes.p-value of <0.05 was used as the threshold for statistical significance.Furthermore, this factor score analysis was used as a part of the adjusted multivariable logistic regression analysis to determine the associations between the knowledge, attitudes, and practice themes and the respondents’ demographics. The outcome variables regarding knowledge, attitudes, and practices were categorized as “incorrect”, “moderate”, and “correct”; “unfavorable”, “moderate”, and “favorable”; and “bad”, “moderate”, and “good”, respectively. In doing so, we constructed a three-point index (composite score range: 0 to 2) and assigned values to responses for knowledge, attitude, and practice items. For knowledge questions, we assigned 2 for a correct response, 1 for moderate, and 0 for an incorrect value. Similarly, for attitude questions, we assigned 2 for favorable, 1 for moderate, and 0 for unfavorable attitudes. The same strategy was applied for practice questions, where the categories were good (2), moderate (1), and bad (0). Before categorizing, the negative items were reversed and calculated accordingly. These outcome variables were then correlated with the explanatory variables. The results were expressed as odds ratios (ORs) accompanied by 95% confidence intervals (95% CIs), and a n = 363) were male and 16.7% (n = 73) were female  of respondents were veterinary interns, 31% (n = 134) and 19% (n = 84) of respondents were with up to 3 years of work experience and 7 years or more experience, respectively. Most of the respondents (n = 235) were from the government sector (Department of Livestock Services), followed by the private sector (n = 136) and medicine/feed companies (n = 65). More than half of respondents  had not received any training on antimicrobial use and AMR at the time of the current study.While close to 40% (n = 350), senior colleagues (n = 348), the experience of managing similar problems (307), use of the Internet (n = 235), and national guidelines and protocols on AMR and AMU (n = 167).Selection of appropriate antimicrobials by a veterinary respondent was influenced mostly by disease type/organism  followed by clinical sign (61%) and patients’ previous history of AMU and the potential side effects of antimicrobials (59%) . Interesn = 175), choosing the correct antimicrobials , correct doses , correct routes for administering antimicrobials , duration of antimicrobial treatments , and causes of AMR . Almost half of all respondents had a medium level of knowledge on interpreting laboratory results , more than half (56%) reported knowledge on using a combination of different antimicrobials, and nearly half of respondents (48%) had knowledge on modifying or stopping the use antimicrobials . The majority of respondents had a medium-to-poor levels of knowledge of reserve groups of antibiotics (around 56%), knowledge of critically important antimicrobials (around 58%), and knowledge of the national action plan for AMR (around 66%).Overall, our results show that respondents had relatively good knowledge of AMR and AMU . In partn = 384) strongly agreed that there is a threat of antimicrobial resistance for livestock and poultry production (n = 170) and strongly agreed (n = 164) with the statement that “a single course of antibiotics can cause antimicrobial resistance” whereas 23% (n = 102) disagreed with this statement. Moreover, 61% (n = 265) of participants strongly agreed with the statement that “irrational antibiotic uses in animals lead to antibiotic resistance in humans”. More than 70% (n = 322) of participants also agreed that AMR is a natural as well as an anthropogenic phenomenon, while one quarter of them  disagreed with this statement.Our analysis indicates that most veterinary respondents (oduction . Most ofn = 428) strongly agreed that antimicrobial resistance will become more problematic in the near future. In contrast, most of the respondents  believed (agreed and strongly agreed) that new antimicrobials will be developed to tackle the AMR issue. However, almost 80% (n = 349) of all respondents agreed that they faced difficulties when selecting the correct antimicrobials and the same number of participants (n = 349) also agreed that they had enough sources of information on antimicrobials and their usage.More than 80% of participants (n = 352) of respondents agreed and strongly agreed with restricting priority antibiotics for human use only, almost 20% (n = 84) of all respondents either disagreed or strongly disagreed with the idea of imposing this restriction.Although 81% (n = 206), completing the full course of antimicrobials , and proper vaccination of animals to reduce the use of antimicrobials  (n = 49) or frequently .Most respondents indicated that they regularly give advice to their farmers about the withdrawal period of the antimicrobials they prescribed, keeping records of antimicrobials that are used  . Howevern = 115) of them never used the CS test.The highest number of respondents did not follow culture and susceptibility (CS) testing for selecting the right antibiotics, and 26.4% (p = 0.003), level of education (p = 0.031), years of experience in practice (p = 0.018), and previous training on AMU and AMR (p = 0.000) were significant factors affecting their knowledge (p = 0.016) and level of education (p = 0.027) were the factors affecting their practices.The analysis further revealed that respondents’ age (nowledge . In termp = 0.032) than veterinarians who worked in medicine/feed companies. Moreover, the analysis also found that respondents who received training on AMU and AMR were 1.92 times more likely to have higher AMU and AMR knowledge  compared to those who did not receive training.Our adjusted logistic regression analysis showed that respondents’ current workplaces and previous training on AMU and AMR were positively associated with increased levels of knowledge on AMU and AMR . Specifip = 0.043) compared to those who were 18–25 years of age. Further, the respondents who received training on AMU and AMR were 2.09 times more likely to have favorable attitudes  than those who had not received training.The analysis further revealed that the respondents’ age and previous training were positively associated with favorable attitudes towards AMU and AMR. The respondents who were 36–40 years of age were 0.24 times more likely to have favorable attitudes towards AMU and AMR  than those who had not received training.Like the knowledge and attitude themes, training was positively associated with prescription practices. The respondents who received training on AMU and AMR were 0.76 times more likely to perform well when writing a prescription  has become a burgeoning public health issue globally, including in Bangladesh. AMR is aggravated by many factors, largely due to the over-use of antimicrobials (AMU) and unregulated diverse health systems . The redOur study demonstrated that prescription of antimicrobials was influenced by several factors including diseases or organisms, history of clinical signs, and potential side effects of the antimicrobials, which were good practices. Overall, the factors associated with the selection of antimicrobials by the veterinarians were good. Previous reports also observed that experience through appropriate training, access to published literature, and availability of the treatment guidelines has a significant role in changing the prescription behavior of veterinarians ,44. GiviAlthough veterinarians had relatively good KAP on AMR and AMU, factors related to KAP have demonstrated important gaps in the KAP, which were also reported by a good proportion of vets in the current study. The findings of this study were in line with those of other researchers who showed that the veterinarians had good knowledge of AMU and AMR issues compared to other stakeholders such as poultry feed and drug sellers ,37,42,43The study further showed that veterinarians’ practices in providing regular advice to the farmers on withdrawal of antimicrobials, recording of the antimicrobials they use, and completion of the entire course of an antimicrobial. However, a good proportion of the veterinarians followed poor practices. Many of them did not use ASTs, there were frequent uses of more than one antibiotic in a single prescription, antimicrobials were prescribed based on the demands of the farmers and without clinical monitoring of the animals, and higher doses of antibiotics were prescribed for rapid recovery. Prescribing of antimicrobials based on the client demand without clinical observations of the animals was not avoided by a proportion of the Bangladeshi veterinarians, and this is considered a bad practice which may aggravate the AMR problem ,45. In BVeterinarians’ roles are crucial in changing the behavior of almost all the stakeholders involved in veterinary practices ,37,42,43This study demonstrated that a number of clinical etiological factors, such as the use of susceptibility tests or the inability to interpret such reports, influenced the selection of appropriate antimicrobials. Other factors such as the economic condition of the farmer, locally available antimicrobials, and drug instructions had a high-to-moderate influence when selecting an antimicrobial. The study further revealed that veterinarians’ socio-economic and demographic characteristics such as age, level of education, years of experience, and previous training, were the key factors in their knowledge, attitudes, and practices regarding AMU and AMR. Considering the results of our study, the indiscriminate use of AMU in Bangladesh can be alleviated by the inclusion of AMR in the veterinary curricula, continuous education, and awareness campaigns, with more training for practicing veterinarians and other stakeholders, easy access and dissemination, and implementation of AMR resources, for example, preparing a database of antimicrobial use and increasing the provision of veterinary services in hard-to-reach areas of the country.


The soluble epoxide hydrolase (sEH) enzyme is a major regulator of bioactive lipids. The enzyme is highly expressed in liver and kidney and modulates levels of endogenous epoxy-fatty acids, which have pleiotropic biological effects including limiting inflammation, neuroinflammation, and hypertension. It has been hypothesized that inhibiting sEH has beneficial effects on limiting obesity and metabolic disease as well. There is a body of literature published on these effects, but typically only male subjects have been included. Here, we investigate the role of sEH in both male and female mice and use a global sEH knockout mouse model to compare the effects of diet and diet-induced obesity. The results demonstrate that sEH activity in the liver is modulated by high-fat diets more in male than in female mice. In addition, we characterized the sEH activity in high fat content tissues and demonstrated the influence of diet on levels of bioactive epoxy-fatty acids. The sEH KO animals had generally increased epoxy-fatty acids compared to wild-type mice but gained less body weight on higher-fat diets. Generally, proinflammatory prostaglandins and triglycerides were also lower in livers of sEH KO mice fed HFD. Thus, sEH activity, prostaglandins, and triglycerides increase in male mice on high-fat diet but are all limited by sEH ablation. Additionally, these changes also occur in female mice though at a different magnitude and are also improved by knockout of the sEH enzyme. The soluble epoxide hydrolase (sEH) enzyme plays a role in physiology and pathophysiology by regulating several classes of bioactive lipids, particularly epoxy-fatty acids (EpFA), which are rapidly hydrolyzed by the sEH. There have been several indications that this enzyme has a role in metabolic disease and obesity . A high-via cytochrome P450 activity. It has been previously determined that EpFA metabolites are the most dramatically altered lipid metabolites in adipose tissue from male mice (α-LA) were significantly altered in inguinal, gonadal adipose, and interscapular tissue in HFD male mice  formed from long chain polyunsaturated fatty acids (LC-PUFA) ale mice . The epoale mice . Among tEarly investigations in male C57/B6 mice indicated that sEH expression in liver, kidney, and gonadal adipose as well as enzyme-specific activity did not alter between standard fat diet (SFD) and HFD fed animals . Howeverhttp://www.researchdiets.com/opensourcediets/stock-diets/dio-series-diets), Omega-3 DHA enriched diet , or standard chow . The DHA diet was produced from Solutex oils with added t-BHQ and was vacuum packed under nitrogen and stored at −20°C. Female and male WT mice and sEH KO mice fed with all four diets were assessed; weight gain and chow consumption (per cage) were measured over the course of the study  were allowed to acclimate and then administered one of the following diets for 8 weeks: HFD , control diet  (he study . Tissues3H]-trans-diphenylpropene oxide (tDPPO) as a substrate following published methods (The enzymatic activity of sEH was measured using . However, the sexual dimorphism in WT she activity in WAT was significant .In the gonadal WAT, there was no statistical difference in activity between the diets for females or males . There were no significant differences when comparing WT female to sEH KO female mice on any diet . Thus, the sexual dimorphism in body weight was the strongest relationship comparing all groups; however, significant increases with HFD in WT males compared to KO male mice demonstrated specifically the effect of sEH gene deletion.When comparing the WT to sEH KO male mice, the WT males demonstrated a significant increase in body weight on the HFD [two-way repeated measures ANOVA, Holm–Sidak post hoc, p ≤ 0.037, n = 4/group). Interestingly, the diets did not induce any change in sEH KO females . In WT males, the liver TG increased with the HFD compared to all other diets . However, like the WT males, the sEH KO males responded to the HFD with significantly increased triglycerides compared to the SFD and n3FD . Comparing the male to female TGs, WT males were significantly higher than WT females, but the sEH KO males were not significantly increased compared to the KO female groups . Importantly the KO males had significantly lower TG across diet groups compared to WT males . The female WT versus KO comparison was not significantly different with the same analysis (p = 0.380).In the WT females, the HFD increased triglycerides (TG) significantly compared to the SFD and n3FD . Female KO lacked significant difference when compared across diets . Similar to the TG results, the liver TC increased with the HFD in WT males compared to all diets . However, the TC levels in KO male mice lacked significant difference when compared across diets . Comparing the TC in WT to sEH KO male mice revealed significant differences in the HFD (p = 0.005) and n3FD groups (p = 0.012) . In WT females, the LFD (p = 0.006) and n3FD (p = 0.014) demonstrated significant increases in TC versus female KO . WT females on the LFD also had higher TC than males . In the KO mice, the SFD and n3FD demonstrated differences in TC with males lower than females .Total cholesterol (TC) in WT females varied from the TG results with the LFD demonstrating a significant increase compared to SFD . In KO females, the n3FD significantly lowered the liver concentrations of EET regioisomers and the HFD increased them . WT males, like the WT females, had reduced EETs on the n3FD . KO males on the n3FD also decreased the EET regioisomers compared to the SFD and LFD . This is remarkable because the n3FD retains the 6.2% corn oil and has more fat content  than the LFD (10%). This is consistent with the ω-olefin of EPA and DHA being excellent substrates for cytochromes P450s that oxidize polyunsaturated lipids . The same increases of EDPs occurred in the sEH KO females on the n3FD . The WT males on the n3FD had higher EDP levels compared to all other diets. The HFD in WT males also increased the EDPs compared to the SFD and LFD . In KO males the EDPs increased on the n3FD compared to the SFD and HFD . What is remarkable about the result is the difference in scale of EDPs in the liver between the female KO on the n3FD and the males. The total amount of EDPs in the female KO liver was 3-fold higher than the KO males while the WT were not significantly different between sexes . The KO females had increased EDPs on the n3FD and SFD compared to the corresponding WT of same sex and same diet . The KO males had increased EDPs on all diets different from WT males .The liver EDPs increased in WT females on the n3FD compared all other diets . KO females were higher than WT females overall and had the highest EET levels on the SFD . WT male demonstrated increases in EETs due to the HFD . Surprisingly, the KO males showed increases in EETs but were not significant although they showed significant increases with HFD .EETs in BAT  significp ≤ 0.002, n = 3–4/group) which was true for the KO female as well . The WT male  and sEH KO male both had higher EDPs on the n3FD as well .EDPs in WT females predictably increased on the n3FD . KO female had no significant change related to diet (p = 0.153). WT male had the highest levels on SFD . The KO male EETs were higher than all other groups and had significantly higher levels on the LFD .In WAT , the EETp ≤ 0.001, HFD vs. SFD and LFD, p ≤ 0.001, n = 4/group). In the KO female, the n3FD raised EDPs . The WT male also had elevated EDPs on the n3FD . However, the KO males had the largest increase in EDPs overall .The WAT EDPs were significantly higher on both the HFD and n3FD in WT female . The female KO mice responded with a seemingly large increase in EETs on the LFD, which was significant compared to only the n3FD . The WT male EETs increased on the HFD compared to both the n3FD and LFD, but overall, the levels were compared to the KO males . The changes in male sEH KO EETs were not significant among the diet groups  likely due to variability and the small n per group. However, these levels were nonetheless much higher than levels measured in WT animals.In the brain , EET levp = 0.132). The KO females, similar to the EETs results, had a large increase in EDPs on the LFD compared to other diets . The WT male EDPs increased in the HFD compared to both the n3FD and LFD . However, again the change in EDPs for WT males was still folds lower than levels in the sEH KO males. In the sEH KO males, EDPs increased in response to the n3FD compared to both the LFD and HFD  and the levels overall were much higher that WT animals and the KO females with the exception of the LFD effect in KO female. Numerical values for the averages ± SEM for individual regioisomers of the EpFA analyzed here are also reported in The WT female EDPs did not change with the different diets . This was not the case in KO mice where prostaglandins in both female and male increased on the LFD compared to WT, though the KO mice also had lower levels in the n3FD. Overall, these prostaglandins were low in BAT especially on the LFD and n3FD in all mice. However, the SFD displayed increases in PGD2 levels in KO mice . The inflammatory prostaglandins increased in BAT with HFD in all mice compared to LFD and n3FD. The WAT . For numerical values for the averages ±SEM for these prostaglandins from cyclooxygenase metabolism, see The depicted prostaglandins are recognized as two of the most proinflammatory endogenous lipid metabolites. In the liver of WT mice, both female and male PGE The WAT , showed  The WAT , there wSeveral studies have laid the groundwork for the role of sEH in obesity. Protein expression levels of the phospholipases that liberate PUFAs from cellular membranes, the CYP enzymes that generate the EpFA substrates of sEH, sEH itself, and other enzymes in arms of the ARA cascade have been measured and correlated with inflammatory markers. These experiments have provided the information that sEH has a role in modulating the regulation of EpFA in obesity to improve health. The current study has furthered this demonstration, moving beyond the expression to the activity of sEH as a lipid-regulating enzyme in tissues with a high lipid content. An important outcome of these experiments is the demonstration of relative sEH activity in the adipose tissues compared to the brain and liver. Importantly, it also addresses the differences for female compared to male animals in all the included analyses. The liver remains the tissue with the highest sEH expression and activity, and the liver may play a role in physiopathology including in CNS diseases such as Alzheimer’s disease . This diIt is important to note when interpreting the results that few of the several studies investigating the role of sEH with dietary interventions follow identical experimental design. Some studies have used HFD with 42–5% kcal from fat  comparedIncreased sEH expression has been correlated with inflammatory pathology in the CNS  and cardInterestingly, the results demonstrated that LFD decreased sEH activity in the liver in WT females but showed no change on the HFD while the WT males responded to the HFD as well as n3FD with higher activity in the liver . The femThe reduction in EpFA that is suggested to be due to lower expression of CYP enzymes  and incrThe approach of sEH inhibition in obesity was investigated by Lopez-Vicario et al. (2015) using the fat-1 transgenic murine model. The fat-1 mice have a transgenic expression of a desaturase for omega-3 and enrich tissues with omega-3 PUFA. In this model using male mice, sEHI expanded brown adipose volume and limited ER stress as well as limiting hepatic steatosis. This suggested that sEH inhibition in combination with omega-3 enrichment is successful in countering the metabolic dysfunctions in obesity. This is supported by the data from our experiments that show that the effects of greatly increased EDP metabolites in sEH KO animals coincided with lower weight than WT animals on the same diet.Overall, the body weights increased weight overtime as expected, with the greatest increased body weight on the HFD and a sexual dimorphism of males gaining more than females per genotype . As mentStudies have suggested that sEH inhibition limits obesity and metabolic disease  Yang et. In one α-linolenic acid (precursor for DHA synthesis in vivo) in the soybean oil of this diet. This suggests that the overall dietary alteration affects more than sEH expression and the metabolism of EpFA. Interestingly, the previously investigated changes in gonadal adipose revealed changes of reduced cytochrome P450 gene expression  measured by PCR rather than a significant increase in sEH or phospholipase expression  oxylipins from WT male mice on HFD reported lower levels of PGE and BAT . Our stuKO males . Moreovee effect . The core effect .The same 60% HFD used here was previously administered for a longer duration (5 and 10 months) to male mice, which both increased sEH protein and induced endoplasmic reticulum stress (ER stress) in the liver and adipose tissue . In our These experiments demonstrated the role of sEH in regulating EpFA and its response to alterations in dietary lipids. Despite the small number comprising the treatment groups and the inherent individual variability, significant changes resulted from the diet interventions in both male and female mice of both WT and sEH KO genetic backgrounds. This demonstrates the critical role of sEH in the regulation of lipid mediators and correlates with several health outcomes that have been investigated in other studies. Here, the impact of not only sEH inhibition but also diet supplementation is evident and demonstrates the potential for impacting health. It is important to consider that studies are conducted in humans and that both sexes are included, and we have demonstrated not only in absolute amount but also in changes in portions of metabolites that there are differences in the metabolism of lipid mediators between females and males not only related to the sEH enzyme.


Kaposi’s sarcoma (KS) is an uncommon, multifocal and angioproliferative lesion, which demonstrates a poor prognosis. The aim of the present research was to explore the association of HIV viral load, CD4+ and CD8+ counts and the CD4+/CD8+ ratio on the risk of oral Kaposi’s sarcoma (KS) development.P-value <0.05 was considered significant. A total of 62 patients were retrieved from March 2008 to October 2020 from the files of two oral pathology centres. Clinical, laboratory and follow-up data were retrieved from their medical files. Poisson regression was used to explore the role of history of immunosuppression and its association with oral KS development. A  Sixty-two patients were included in the present study . Patients with oral KS presented a mean age of 32.6 years, and male patients were more affected. The hard palate  was the main anatomical site affected. The lesions were mostly presented as swellings  and nodules . Systemic manifestations were also observed, including candidiasis , bacterial infection , tuberculosis , herpes simplex  and pneumonia . A significant correlation was observed between HIV viral load, CD4+ count and the CD4+/CD8+ ratio with oral KS development. HIV viral load, CD4+ count and the CD4+/CD8+ ratio are associated with oral KS development. Key words:Cancer, oral, Kaposi’s sarcoma, diagnostic. Kaposi’s sarcoma (KS) is an uncommon, multifocal, angioproliferative lesion initially described by Moritz Kaposi in 1872 ,4. KS waKS is recognized as an AIDS-defining cancer, along with non-Hodgkin’s lymphoma and invasive cervical cancer ,8,9. CliThe prognosis for people living with HIV/AIDS (PLWHA) improved with the initiation of highly active antiretroviral therapy (HAART) in the mid ‘90s -15. DespAccording to previous literature, the association of patients’ systemic condition and the development of oral KS has not been well established. Thus, the objective of this study is to evaluate the association of HVL, CD4L and CD8L and the CD4L/CD8L ratio with the development of oral KS.- Study design and ethical approvalThis research was developed on the files from two oral pathology centres of Brazil. Samples were retrieved from the centres over a period of 12 years (from March 2008 to October 2020). The diagnosis centres were João de Barros Barreto University Hospital, Federal University of Pará, Belém/Brazil and Instituto do Câncer do Estado de São Paulo (ICESP-FMUSP), São Paulo/Brazil. Expert oral pathologists from each centre evaluated the samples. The ethics committee of the João de Barros Barreto University Hospital approved this work (No. 3.952.288). The patients’ identities remained anonymous according to the Declaration of Helsinki.- SamplesPatients from both control and KS groups were retrieved based on the initial diagnosis of HIV/AIDS. KS in the oral cavity were recovered, and data regarding sex, age, location, clinical aspects, HIV/KS diagnosis and laboratory findings  were retrieved. Ranges of laboratory findings were classified following Taiwo & Hassan (2010), following: HIV viral load was ranged as <20, 20≤199, 200≤999 and >999 copies/mL; CD4+ as ≤200, 201-499 and ≥500 cells/mm3; CD8+ as ≤150, 150-1000 and >1000 cells/mm3; CD4+/CD8+ ratio was considered according to the mean values of all patients . In case- Data analysisMeans and percentages are presented as descriptive statistics. Poisson regression was used to explore the role of the prevalence of immunosuppression and the association of oral KS development, exploring HVL, CD4L, CD8L and CD4L/CD8L ratio. A P-value <0.05 was considered statistically significant. Data were analysed using IBM SPSS Statistics for Windows, version 23.0 .A total of 62 HIV-positive patients, including 32 patients with clinical presentation of oral KS and 30 patients with no KS lesions on the body were included in this research.Regarding patients with oral KS, a mean age of 32.6 years (range of 19–58 years old) was observed. Male patients were mostly affected, with a M:F ratio of 10.6:1. The hard palate  was the main location of the lesion, followed by the alveolar ridge , soft palate , tongue  and gums . The mandible , maxilla , lower lip  and upper lip  were less frequently affected. Lesions were presented as swellings , nodules , plaques  and spots . They showed purple (53.1%) and red colouration  , and male patients were more frequently affected than females, with a M:F ratio of 1.3:1. Oral manifestation was observed in 5 patients (16.6%), and candidiasis , oral herpes  and hairy leukoplakia  were the manifestations seen. Systemic comorbidities were observed in all cases, and tuberculosis , meningitis , neurotoxoplasmosis , bacterial infection , scabies , pneumopathy  and syphilis  were the main presentations.Laboratory findings of patients who presented oral KS evidenced a mean HVL of 149,487.6 copies/mL , mean CD4L count of 155.9 cells/mm3 (range of 2–837 cells/mm3), mean CD8L count of 944.8 cells/mm3 (range of 143–3056 cells/mm3) and mean CD4L/CD8L of 0.17 cells/mm3 (range of 0.01–0.70 cells/mm3). The control group showed a mean HVL of 592,295.6 copies/mL , mean CD4L count of 112.5 cells/mm3 (range of 10–540 cells/mm3), mean CD8L count of 996.6 cells/mm3 (range of 229–4557 cells/mm3) and mean CD4L/CD8L count of 0.16 cells/mm3 (range of 0.01–0.57 cells/mm3) .p<0.0001), CD4L  and CD4L/CD8L ratio  were significantly associated with oral KS development (Statistical analysis evidenced by the Poisson regression test for prevalence analysis that HVL (HR 95% CI: 1.6517 [1.4681–4.2033]; elopment .Clinical and pathological information regarding oral KS is still very limited due to the diverse clinical presentation and because lesions are mostly presented in late manifestation of HIV/AIDS ,11,19. TClinically, oral KS demonstrated a male predominance, similar to previous literature ,16. The The systemic affliction of HIV/AIDS patients generally causes, besides the oral cavity, development of KS in the skin, gastrointestinal and respiratory complex, consistent with the findings of the present study . SystemiMedical follow-ups of PLWHA generally involve a multidisciplinary assessment based on laboratory findings, including HVL, CD4L, CD8L and CD4L/CD8L, and other complementary exams when necessary ,24. Howeet al. (et al. (Thus, laboratory exams may be presented as a good option to evaluate patients’ systemic condition ,10,15. Tet al.  observedet al. ,27. In a (et al.  reportedMore recently, KS genomics has gained attention over the past decades due to its remarkable pathogenic mechanisms. The association of the HHV-8 genome and KS development has been explored worldwide . It has The present study showed a significant result of oral KS development and its association with HVL, CD4L count and the CD4L/CD8L ratio. Despite the limitations on the number of patients to validate the current results, this is the first study to explore laboratory findings and oral KS development as an alternative method to improve diagnostic accuracy. Additionally, knowledge of the influence of other etiologic factors is important to better establish the etiopathogenesis and pathogenesis of the disease, as well as to determine the gene alterations related to KS development.


Data presented in Figure 4 was misrepresented. This discrepancy was brought to our attention by the corresponding author.On this basis, the Editors formally retract this article from Molecular Vision.Sincerely,The Editors of Molecular Vision