Dianlovirus and has only been detected in China. In this article, we report the detection of filoviruses in bats captured in Vietnam. We studied 248 bats of 15 species caught in the provinces of Lai Chau and Son La in northern Vietnam and in the province of Dong Thap in the southern part of the country. Filovirus RNA was found in four Rousettus leschenaultii and one Rousettus amplexicaudatus from Lai Chau Province. Phylogenetic analysis of the polymerase gene fragment showed that three positive samples belong to Dianlovirus, and two samples form a separate clade closer to Orthomarburgvirus. An enzyme-linked immunosorbent assay showed that 9% of Rousettus, 13% of Eonycteris, and 10% of Cynopterus bats had antibodies to the glycoprotein of marburgviruses.A new filovirus named Měnglà virus was found in bats in southern China in 2015. This species has been assigned to the new genus  Filoviridae includes eight genera, Orthomarburgvirus, Orthoebolavirus, Cuevavirus, Oblavirus, Striavirus, Thamnovirus, Tapjovirus, and Dianlovirus, covering 15 species [Orthomarburgvirus marburgense , Orthoebolavirus zairense , Orthoebolavirus sudanense , and Orthoebolavirus bundibugyoense . The other viruses of the family are either not highly pathogenic to humans or their pathogenicity has not yet been determined. All filovirus disease outbreaks occurred in Africa, with the exception of imported cases in Europe and the United States [The family d States .Rousettus aegyptiacus [Miniopterus schreibersii and causes epizootics in the colonies of this bat species [Mops condylurus [For a long time, it was believed that bats are a natural reservoir of filoviruses . Antibodyptiacus ,9,10,11.yptiacus . At the  species ,14. Bombndylurus ,16,17.Rousettus leschenaultii and Eonycteris spelaea fruit bats caught in Yunnan Province in southern China [Orthomarburgvirus than Orthoebolavirus and Cuevavirus. According to the pairwise sequence comparison (PASC) analysis, MLAV fulfils the criteria of a type of virus with a separate genus in Filoviridae, and the authors proposed the new genus name Dianlovirus [In 2009–2015, new filoviruses were discovered in rn China ,19. The R. leschenaultii is widely distributed throughout South and Southeast Asia. Its range extends from Pakistan and India in the west to southern China and Vietnam in the east [E. spelaea includes nearly all of Southeast Asia and southern China and extends west through both northwestern and southern Asia [the east . The ranern Asia . In Vietern Asia .In this work, we aimed to find genetic and serological evidence of filovirus infection in bats in Vietnam.The procedures used in this study adhered to the Declaration of Helsinki. Approval was obtained from the ethics committee of the Joint Russia–Vietnam Tropical Science and Technology Research Center .Three provinces of Vietnam were selected for fieldwork: Lai Chau and Son La Provinces, located in the north of the country in a mountainous landscape in close proximity to the border with China, and Dong Thap in the south of the country in the Mekong Delta, in a flat area without caves.The bats were trapped from December 2020 to January 2021 using mist nets (4 m × 20 m). The nets were set in places of potential flight of animals (above streams and in clearings) near caves and abandoned buildings. Standard methods were used for the safe handling and sampling of small mammals that were potentially infected with pathogens . The trag at room temperature. All samples obtained were stored in liquid nitrogen during fieldwork and at minus 70 °C in the laboratory.Immediately after euthanasia, blood was sampled through cardiac puncture into sterile tubes with 0.5 M EDTA. Oral and rectal swabs were collected in 0.5 mL of 0.15 M NaCl solution. Sections of the brain, liver, spleen, kidney, lung, and intestine were obtained through sterile necropsy. For collection of plasma and cell fractions, blood samples were centrifuged for 5 min at 10,000× The brain and intestines were tested separately; internal organs from each animal  were pooled and tested in pools. Bat tissues were homogenized with TissueLyser LT  in 0.5 mL of 0.15 M NaCl solution. Thereafter, total RNA was extracted from 100 µL of 10% suspension by the phenol/chloroform method using a Ribo-Zol kit  according to the manufacturer’s instructions.Isolated RNA was reverse transcribed using a REVERTA-L kit  according to the manufacturer’s instructions. Amplification of the filovirus polymerase gene fragment was performed with the following primers: FV-F1, FV-R1; FV-F2, FV-R2 ; Filo-MoImmunoglobulin G (IgG) antibodies to filoviruses were detected by an enzyme-linked immunosorbent assay (ELISA) using a Human Anti-Marburg (Angola) glycoprotein (GP) IgG ELISA kit  and Human Anti-Zaire+Sudan+Reston+Bundibugyo Glycoproteins combo IgG . The kits were customized for bat IgG detection as follows. Bat plasma was tested at a dilution of 1:250. Goat anti-bat IgG antibodies  and peroxidase-labeled rabbit anti-goat IgG antibodies  were used at a dilution of 1:10,000 to detect binding of bat IgG with filovirus antigens sorbed on the bottom of ELISA plates. The following steps of the assay were performed according to the manufacturer’s instructions. Optical density (OD) was measured at 450 nm with baseline correction at 620 nm. Goat anti-bat IgG was preliminarily tested for its ability to bind with IgG of all bat species used during this study.The Mega X package was used for phylogenetic analyses. A phylogenetic tree was constructed using the maximum likelihood method with the General Time-Reversible Model  and the For customized antifilovirus ELISA cutoff determination, we assumed the presence of a mixture of at least two latent populations for each bat species . We inteR. leschenaultii and in a single R. amplexicaudatus  analysis showed that obtained sequences are most similar to the filoviruses found in China. Phylogenetic analysis revealed that two filovirus sequences Vietnam-R.leschenaultii-119-2020 and Vietnam-R.leschenaultii-122-2020 clustered into a group with the Měnglà virus from in China . The thinlovirus . The seqnlovirus , which iRousettus, Eonycteris, and Cynopterus contained more than one latent population, and as a result, we found IgG-positive animals only for these species. The other bat species had a homogeneous low signal without strong peaks, outliers, or change points, and therefore, we considered them seronegative.The change point analysis showed that only the data of Dianlovirus are closer to the genus Orthomarburgvirus than to Orthoebolavirus. Therefore, we used the results of the ELISA with the Marburgvirus antigen for the seroprevalence estimation.Specific IgG antibodies to filoviruses were detected in 12 fruit bats using the customized Human Anti-Marburg (Angola) glycoprotein (GP) IgG ELISA kit and in 8 fruit bats using the customized Human Anti-Zaire+Sudan+Reston+Bundibugyo Glycoproteins combo IgG kit . A totalR. leschenaultii bats and 13.3%  of E. speleae bats were seropositive for IgG to filoviruses. The other tested bat species from Lai Chau Province were seronegative, including Cynopterus fruit bats. In Son La Province, we trapped only one fruit bat (R. amplexicaudatus), and it was seronegative. In contrast, in Dong Thap Province, 10.0%  of C. sphinx fruit bats were seropositive for IgG antibodies against filoviruses , and it was seronegative. In addition to fruit bats, we also tested insectivorous bats of nine species, and all of them were seronegative  95%, 3.1–20.7%) of oviruses . We had negative .Our findings of filoviruses in a northern province of Vietnam extend the previously published evidence of filovirus presence in China. Indeed, we detected filoviral RNA in fruit bats trapped approximately 200 km from the closest sites in Yunnan Province, China, where filoviruses were detected by He et al. and Yang et al. ,18.Orthomarburgvirus, Orthoebolavirus, Cuevavirus, and Dianlovirus genera). Filoviral RNA was found only in samples from R. leschenaultii and R. amplexicaudatus. Similar results were obtained by Chinese researchers during their studies in China: they found filovirus RNA only in Rousettus sp. and E. spelaea bats [R. aegyptiacus is a reservoir host for the virus [M. schreibersii [M. condylurus, but their role as a reservoir or incidental host is either debatable or requires additional study [Rousettus fruit bats contributes to the suggestion that R. leschenaultii and the closely related R. amplexicaudatus are reservoirs for dianloviruses. Additional studies of filovirus infection in these bat species will finally clarify the issue.In our work, we studied 248 bats and detected filoviral RNA only with primers designed by He et al. . These paea bats ,18,19. The virus ,10. Thereibersii ,14, as wal study . Our finR. aegyptiacus [R. aegyptiacus bats [We found filovirus RNA only in the internal organs of bats . The viral RNA was not detected in brain and intestine tissues, oral and rectal swabs for all studied animals. Yang et al.  detectedyptiacus , and addcus bats . Ebola vcus bats , and Bomcus bats ,17. Llovcus bats ,14. The Dianlovirus and one of them is very close to the Měnglà virus. However, two samples formed a separate clade in an intermediate position between the genera Dianlovirus and Orthomarburgvirus. We sequenced only a short fragment of the RdRp gene (309 bp), which does not allow us to use the PASC tool [Phylogenetic analysis has shown that three of the five filoviruses found in northern Vietnam belong to the genus ASC tool  to identdRp gene 9 bp, whiRousettus sp. and E. spelaea had specific antibodies. In the southern province of Vietnam, we caught only C. sphinx fruit bats and 10% of them were seropositive to filoviruses. There were no caves in Dong Thap Province, and as a result, there were no cave-dwelling bats (Rousettus and Eonycteris); therefore, we assume that a filovirus in this province formed a separate focus that consists of forest-dwelling bats (Cynopterus) only.Our data about the seroprevalence of antibodies to filoviruses in bats in Vietnam showed that the populations of cave-dwelling fruit bats in the Northern Province had been exposed to filoviruses; approximately 9–13% of R. leschenaultii was 61% [E. spelaea and 13% of R. leschenaultii being seropositive to filovirus antigens. Serological screening of bat sera samples indicated circulation of several filoviruses [E. spelaea [Serological confirmation of bat’s contact with filoviruses was also obtained in China, India, and Singapore. Especially in China, the proportion of seropositive bats reached 56% , and the was 61% . In Indioviruses . Similar spelaea . In all E. spelaea and R. leschenaultii bats provides evidence for prior exposure of bat hunters to filoviruses. However, cases of acute hemorrhagic fever with Marburg virus-like or Ebola virus-like symptoms have not yet been described in China, India, or northern Vietnam. Apparently, dianloviruses are nonpathogenic to humans or cause mild infection.The pathogenicity of dianloviruses to humans is not yet known. However, there are data on the detection of antibodies in the blood of people who hunt bats in northeast India . Thus, tRousettus play a role in the circulation of filoviruses in Asia. Further studies of filoviruses in Asia are needed to prevent the possibility of new, emerging filovirus-related diseases.Our finding provides additional evidence that bat filoviruses described in China are more widely distributed than previously suspected. We also have proof that fruit bats of the genus


The accelerating pace of biomedical publication has made it impractical to manually, systematically identify papers containing specific information and extract this information. This is especially challenging when the information itself resides beyond titles or abstracts. For emerging science, with a limited set of known papers of interest and an incomplete information model, this is of pressing concern. A timely example in retrospect is the identification of immune signatures (coherent sets of biomarkers) driving differential SARS-CoV-2 infection outcomes.We built a classifier to identify papers containing domain-specific information from the document embeddings of the title and abstract. To train this classifier with limited data, we developed an iterative process leveraging pre-trained SPECTER document embeddings, SVM classifiers and web-enabled expert review to iteratively augment the training set. This training set was then used to create a classifier to identify papers containing domain-specific information. Finally, information was extracted from these papers through a semi-automated system that directly solicited the paper authors to respond via a web-based form.We demonstrate a classifier that retrieves papers with human COVID-19 immune signatures with a positive predictive value of 86%. The type of immune signature  was also identified with a positive predictive value of 74%. Semi-automated queries to the corresponding authors of these publications requesting signature information achieved a 31% response rate.Our results demonstrate the efficacy of using a SVM classifier with document embeddings of the title and abstract, to retrieve papers with domain-specific information, even when that information is rarely present in the abstract. Targeted author engagement based on classifier predictions offers a promising pathway to build a semi-structured representation of such information. Through this approach, partially automated literature mining can help rapidly create semi-structured knowledge repositories for automatic analysis of emerging health threats.The online version contains supplementary material available at 10.1186/s12859-023-05397-8. The rapid growth in scientific publications  presentsOnce relevant sources have been retrieved, information has to be obtained from the text. For some domains, machine consumable structures make specific data types trivial to extract, e.g. genes  and protimmune signature for the disease. For some diseases , disease severity (e.g. mild vs severe), etc, with each pattern of effects constituting an l cancer ), immuneWe developed a semi-automated pipeline Fig. , which uWe developed a general purpose online literature review, author solicitation, and information sharing. The platform is powered by the Django web framework  for tempThe pipeline is powered by Django, a web framework that handles templating and user management, and MongoDB, a database backend for efficient data storage. Front-end components, such as Bootstrap and jQuery, enhance the user interface and facilitate streamlined scripting. The architecture includes modules for triage and solicitation, which are crucial components of the system. The modular architecture of the pipeline project enables flexibility, maintainability, and scalability.The triage module focuses on effectively managing the document triaging process. It incorporates features such as document queues, review stages, and status tracking. By leveraging MongoDB, the module ensures access to document information and supports efficient retrieval and updating of metadata. The solicitation module enables communication and feedback collection from authors. It provides a form with a unique URL for each entry in the database, allowing authors to submit details of immune signatures in their papers. The solicitation module ensures secure and accountable data entry, with the entered data stored in the database and logged for auditing purposes.To adapt the generic platform for COVID-19 immune signatures, a JSON-encoded configuration file was used to specify database details, paper categories, explanatory text, data solicitation forms, email templates, etc  . CORD-19CORD-19 is regularly updated (often weekly); we use these updates to add new papers to our pipeline. The results presented here are base on the 8th November 2021 release of CORD-19.PubMed papers with “Comment”, “Review”, “Editorial”, or “News” article type.Papers from journals whose journal title includes “rev” as a whole word or as the start of a word to avoid review journals.Papers published before December 1, 2019.Papers that do not explicitly mention “COVID” or a related term (e.g. “2019-nCoV”) in the paper title or abstract.Duplicate and near duplicate papers frequently end up in the corpus due to the presence of papers released on preprint services before their formal publication in a journal. The CORD-19 Unique Identifier is linked to a conceptual document, which may include multiple versions of the manuscript. Using the SPECTER embedding, we identified near-duplicate papers by grouping documents within a certain proximity. By experimenting with a 30-unit threshold in the SPECTER embedding space, we effectively excluded most duplicates while retaining distinct articles. For each group of papers, only the most recently released paper was used for further analysis. It is worth noting that some near duplicates may have missing metadata for one duplicate, resulting in discrepancies in processing. For this reason, we also remove entries with near duplicates in our excluded set.To ensure the quality and relevance of the dataset for COVID-19 immune signatures, we performed extensive pre-processing by applying filters and removing duplicates. To focus on primary sources that could contain COVID-19 immune signatures, we filtered this dataset to exclude:We developed a two-stage Support Vector Machine (SVM) based classifier to determine the presence and then the type of immune signature for the filtered CORD-19 literature. For the first stage, the SVM model  simply seeks to determine if a paper contains an immune signature or not; this SVM was trained by grouping the three immune signature classes into one super class (signature present) and the “review article” and “no signature” classes into another super class (signature not present). A second SVM model , trained on only the papers confirmed by our expert reviewers to contain a COVID-19 immune signature, was used to predict the type of immune signature that would be present for those papers predicted by the first classifier to contain an immune signature. Probabilities were obtained from the SVM classifiers using Platt scaling . FeatureExpert review was performed using the aforementioned platform Fig. . A limitOnce papers containing COVID-19 immune signatures have been identified, either manually or automatically, we contacted the corresponding author(s) to request details of the immune signatures in the paper, corresponding to our data model Fig. .Fig. 2ImOur platform provides a form with a unique URL for each entry in the database. This form identifies two classes of data—one that is global and applies to the entire form—and one that pertains to a specific fact about the paper , of which there can be many. The field names are configurable via the JSON configuration file, but for this project, the form asks for global data identifying the paper and contributor , and specific instance data about each immune signature .The process of providing details of an immune signature from a paper involves generating a customized email with field data, enabling recipients to access a paper-specific page for data entry and storage, ensuring security and accountability. The email recipients receive a link to a page for just their specific paper, which does not require a login. Each field on the form has associated help text and examples. All fields are editable by the email recipient except for the paper reference. An arbitrary number of immune signatures may be entered for each paper. When the contributors press the “submit” button, the entered data is stored in the database and logged in a separate file, allowing administrators to revert to a previous version in the case of accidental or malicious changes after initial data entry. A typical data entry form is shown in Fig. To allow third-party manual solicitations, a “submit your immune signatures” button on the  homepageThe contributor-entered details of the immune signatures are stored in a MongoDB database and are made available via  in both Python Data Analysis Library |pandas| 0.24.2  was used|) 0.4.6  was used|) 0.4.6  was used|) 0.4.6  for toke|) 0.4.6  was used|) 0.4.6  to perfo|) 0.4.6  with 100Our overall workflow involved the development of a training set of papers containing COVID-19 immune signatures, SPECTER and SVM-powered identification of papers likely to have these immune signatures, expert review of a subset of papers, data solicitation from the authors, and then data dissemination on the covid-signatures.org site   to obtaion (AIC) . Almost 06) Fig. .Fig. 3UnThis significant sub-clustering suggests that the SPECTER embedding effectively preserves information on whether or not a paper contains an immune signature. These results suggest that we can use the SPECTER embedding as the basis to construct a classifier to identify papers with COVID-19 immune signatures.We built a classifier to determine if the SPECTER embedding could be used to predict which papers contained COVID-19 immune signatures. To create the classifier we iteratively built a training set, consisting of papers with a label indicating whether they contained immune signatures. We took advantage of the close grouping of immune signature papers in the SPECTER embedding by starting with five initial papers with COVID-19 signatures  based on Leave-One-Out Cross Validations (LOOCV) with one fewer paper was 0.10 Using a SVM classifier trained on these 401 papers, we selected an additional 91 papers based on predicted probability  area under the curve (AUC) was 0.916 Fig. A.With aAfter the iterative construction of the training set was complete, we evaluated whether the SPECTER embedding was essential for achieving ongoing high performance of the classifier. We compared the SVM classifier using the SPECTER embeddings to the widely used approach of Term Frequency–Inverse Document Frequency (TF–IDF)  of the tWe next sought to determine if the SPECTER embedding of titles and abstracts contained sufficient information to distinguish between papers describing different types of COVID-19 immune signatures. We divided the COVID-19 immune signatures into three types: (A) Type A papers contained gene expression signatures, (B) Type B papers included signatures involving proteins, metabolites and/or cell types, and (C) Type C papers included all other COVID-19 immune signatures.To verify that the different signature types were meaningful and distinct, two experts reviewed a set of 100 papers. Papers where reviewers agreed on the type of immune signature (38 of 46) were added to the training set for the second stage classifier. The classes of immune signatures were well recognized by our reviewers, with substantial .C only Next we consider which features may be driving the “second stage” classifier in assigning different signature types. We chose a random sample of 500 papers most likely to contain a particular immune signature type  submitted a single immune signature, while 2 signatures were specified in 5 of the responses, 3 signatures were specified in 2 responses, and one contributor each specified 4, 12, 14, and 27 signatures for a single paper. While the submission form did not have any required fields, all of the responses included a free-text description of the signature, the comparison underlying the signature, and the source of the signature in the paper . However, only 35% (11 or 31 responses) provided a list of the immune response components  that comprise the signature. Thus, while the overall response rate to direct solicitation was reasonable, follow-up is needed to obtain signature details.We next sought to determine if there were differences between the papers the led to successful solicitations compared with those that did not. The likelihood of obtaining an authors response for the 63 papers selected with our classifiers was not correlated with the predicted probability of the paper containing an immune signature . NonethA high response rate is only useful if the responses are of sufficient quality to be reusable. A key challenge is balancing the need to minimize the burden on the contributor with the desire for structured information. In our case, we provided structured fields and examples, and requested authors report information as it appeared in the paper rather than attempting to translate terms to a standardized form  . Thus, sWe focused the machine learning and natural language processing on the paper titles and abstracts, but there is more information available in the full text and, in particular, the COVID-19 immune signatures are themselves expressed in the body of the paper . However, the structured full-text is only available for about a quarter of the CORD-19 dataset and there is lower signal-to-noise ratio in the full-texts than in abstracts . NonetheMore sophisticated language models facilitate higher performance on information extraction tasks, e.g. SciBERT (which underlies SPECTER) has shown success in retrieving Population Intervention Comparator Outcome (PICO) elements in the randomized controlled trial literature . The PICcommunity.covid-signatures.org, utilizing the signatures retrieved by this pipeline.Crowd-sourcing further curation offers a potential mechanism for reducing variability and providing consistently annotated human COVID-19 immune signatures similar to those made available through the HIPC Dashboard . A portaIdentifying papers containing COVID-19 immune signatures and collecting data and contextual information (metadata) regarding the signatures can help speed scientific progress in this area. As has been seen with vaccination  and inflThis paper describes the development of a pipeline to retrieve papers containing COVID-19 immune signatures and for their semi-automated curation. Within this pipeline, we iteratively built a training set and incorporated machine learning to classify papers from an existing repository (CORD-19). We found that SPECTER embedding provides a good reduced representation of a paper and its relatedness to other papers that can be adopted for the purpose of identifying scientifically salient features of the paper (in this case immune signatures). However, SPECTER was not a necessary component, as TF–IDF with logistic regression has similar performance to the SPECTER approach. Thirty-one percent of authors of papers with immune signatures voluntarily provided semi-structured representations in response to a request from our team, regardless of the immune signature type.Given its start as a neuroinformatics tool, the successful application to COVID-19 demonstrates that this pipeline approach is readily adaptable for other fields to identify papers containing scientifically relevant features, which can be further processed—by data solicitation, manual curation, or automated means-to extract the relevant data for presentation in a unified knowledge base or dashboard.Additional file 1. A copy of the generic pipeline  that has been adapted for COVID-19 immune signatures.Additional file 2. Python code use to query the pipeline, build and compare the classifiers.Additional file 3. Supplementary tables of the tags and key words used in the pipeline, and the words frequency that differ between classes.


The COVID-19 pandemic has focused attention on the use of immunization information systems (IIS) to record and consolidate immunization records from a variety of sources to generate comprehensive patient immunization histories. Operationalization of IIS in the United States is decentralized, and as such, there are over 60 different IIS with wide variations in enabling policies and functionalities. As such, the policies that inform the development and operation of those sub-national IIS exist at the state and sometimes city levels. A targeted literature review was conducted to identify IIS policies and functionalities and assess their impact. The authors identified articles published from 2012 to 2022 that discussed or evaluated IIS policies and functionalities and screened titles, abstracts, and full text for inclusion. When selected for inclusion, authors extracted IIS policy/functionality characteristics and qualitative or quantitative outcomes of their implementation, where applicable. The search terms yielded 86 articles, of which 39 were included in the analysis. The articles were heterogeneous with respect to study design, interventions, outcomes, and effect measures. Out of the 17 IIS policies and functional components identified in the targeted literature review, the most commonly evaluated were provider-based patient reminder/recall, IIS-based centralized reminder/recall, and clinical decision support. Patient reminder/recall had the most published research and was associated with increased vaccination rates and vaccine knowledge. Despite the lack of quantitative evidence, there is a consensus that immunization data interoperability is critical to supporting IIS data quality, access, and exchange. Significant evidence gaps remain about the effectiveness of IIS functionalities and policies. Future research should evaluate the impact of policies and functionalities to guide improved utilization of IIS, increase national interoperability and standardization, and ultimately improve vaccination coverage and population health.  Immunization information systems (IIS) are confidential databases designed to record and consolidate vaccine doses administered by participating providers within a geographic area, to create comprehensive patient immunization records . There aThe COVID-19 pandemic has reinforced the critical importance of robust data systems to ensure the availability of timely, consolidated, and up-to-date patient immunization data to guide public health decisions and support vaccination efforts. The pandemic also exposed that many jurisdictions have capacity constraints to utilize and expand their state IIS to respond to public health emergencies given current policy frameworks .Since IIS are maintained separately by different states or jurisdictions, there is considerable variation between IIS policies (such as mandated reporting) as well as IIS functional components . This variation presents challenges to maintaining complete and high-quality patient data. However, the variability also provides an opportunity to understand the specific impact of different IIS policies and functionalities on vaccination rates, population health efforts, and provider reporting of vaccinations to the IIS.To understand the available evidence in this area, we conducted a targeted literature review to identify key policy and technical components of IIS. The objectives of our review were to (1) identify the various documented functional and policy components of an IIS and (2) understand the real-world impact of the functional components and policies.(“vaccin*”[MAJR] OR “Immuniz*”[MAJR]) AND .We used PubMed to identify literature published between January 2012 and January 2022. All countries and methodologies, including commentaries, were included. Non-English publications were excluded. The search string used was Reviewers screened abstracts and full texts, with at least two reviewers independently screening each. Due to the small number of articles retrieved, title screening was not applied as part of the review.Reviewers applied inclusion and exclusion criteria to screen abstracts and full text articles. We included all articles that discussed or evaluated components that could be included in an IIS. This included IIS functional components that were evaluated as electronic health record (EHR) components, such as clinical decision support and patient reminders. Articles were excluded if they discussed strategies to increase vaccination rates unrelated to IIS, reviewed the one-time creation of vaccine databases or registries for a specific initiative, health system, or pilot program, or were specific to vaccine adverse event monitoring. Discrepancies between inclusion and exclusion decisions were resolved through discussion to reach a consensus among researchers.Three researchers independently extracted the following information: article characteristics, including title, authors, data, region, and study design; study population ; IIS policy and/or functional component, such as centralized reminder/recall and bidirectional interoperability; and, where applicable, outcomes or direct impact of IIS policies and functional components, such as vaccination rates and vaccine data quality. Researchers extracted statistical outcomes  from observational and experimental articles. Only the original results of systematic literature reviews (SLRs) were extracted; any secondary research results referenced in the SLRs had their original sources cited. Extraction conflicts were resolved through review and consensus discussions.Following extraction, researchers used thematic analysis to identify and categorize IIS policies and functional components found throughout the published literature. A frequency analysis was conducted to understand the percent of extracted statistical outcomes that were significant for each identified policy or functionality theme. Non-statistical impacts and outcomes were evaluated qualitatively.The search string resulted in a total of 86 articles. After an abstract and full text review, 39 articles were included in the final analysis. The articles were heterogeneous with respect to study design, interventions, outcomes, and effect measures. The characteristics of the articles included in the review are listed in A total of 17 distinct IIS policies and functional components were identified across the 39 articles , with maOnly 45 (38.1%) of all 118 extractions included an evaluation of statistical significance, while 33 (28.0%) extractions cited the impacts of policies and functional components on real-world outcomes but did not statistically evaluate them. In this case, non-statistical impacts were extracted from all sections of the articles, but most commonly the results and conclusions sections. For example, the impacts of clinical decision support were extracted from the evidence synthesis section of Patel et al.’s Economic Review of Immunization Information Systems to Increase Vaccination Rates: A Community Guide Systematic Review . Table 3Out of the 17 IIS policies and functional components identified in our targeted literature review, patient reminder/recall was discussed the most in the published research and was associated with increased vaccination rates and vaccine knowledge ,38. ThisAnother key functional component with evidence of positive impact that could support vaccination coverage across the life course was clinical decision support. Clinical decision support systems aid providers in administering accurate and timely vaccinations in accordance with Advisory Committee on Immunization Practices (ACIP) recommendations. Four articles demonstrated that implementation of a clinical decision support functional component, such as forecasting and prompting recommended vaccinations for patients, reduced the administration of unnecessary vaccinations and increased vaccination rates ,22,23,24Despite the lack of studies that lend themselves to statistical analysis in published literature, it is a well-established belief that immunization data interoperability is critical to supporting IIS data quality, information availability and access across provider types and sites of care, and cross-jurisdictional exchange of data ,42,43. AWe identified relatively few articles in our review evaluating the impact of different IIS policies and functional components on the adult population, as most articles focused on pediatric vaccinations and outcomes. The limited amount of research evaluating the outcomes of IIS policies and functional components is surprising, given that many state IIS have been operational since the 1990s . This deWhile the US continues to work toward optimizing the vaccine ecosystem, other countries offer useful insights into promising IIS practices and lessons learned. For instance, Australia has been recognized for its advanced IIS policies , which iAlthough the CDC maintains IIS functional standards and core data elements , they arFunding from the CDC and other national initiatives are driving momentum to improve IIS infrastructure and broader data modernization, which provides a window of opportunity to implement evidence-based policies and technical improvements. The CDC received funding from the 2021 American Rescue Plan to support state and local-level COVID-19 vaccination efforts, including for health information technology and data system enhancements to facilitate immunization data sharing and vaccination efforts among underserved groups [There are several limitations to our research. First, our search was restricted to articles in English, and most articles focused on the US as well as the pediatric population. Consequently, an in-depth evaluation between countries or age groups was not able to be performed, so results may not be generalizable to non-US countries or across all age groups pediatric populations. Second, to comprehensively review the limited available literature, we grouped results from articles with different levels of evidence, populations, and study designs and included editorials and opinion pieces, limiting the strength of our conclusions. Third, the majority of study designs used in identified articles did not lend themselves to statistical analysis of IIS impacts, limiting our ability to draw conclusions about the impacts  of many IIS policy and functional components, such as protection of health information and alternative site participation. We relied on article findings and did not independently validate the content within the articles captured in this review .Through a targeted review of the literature, patient reminder/recall, centralized reminder/recall, and clinical support had the most published research to suggest their implementation improves real-world outcomes. However, additional research is needed to guide states toward prioritizing and implementing the most impactful IIS policies and functional components. Additional research can further demonstrate the value of robust IIS and support efforts to ensure sustainable IIS funding. There is a need to robustly assess the impact of policies and functional components to guide the development of best practices for IIS, support a more standardized and interoperable national IIS landscape, and ultimately improve vaccination coverage and population health.


Average QRS duration was 152.6 ms at baseline and 119.3 ms at follow‐up . LBBAP could significantly reduce QRS duration and improve systolic function in a patient with LVEF between 35% and 50%. Application of LBBAP as a CRT strategy for HFmrEF may be a viable option.Cardiac resynchronization therapy (CRT) strategy for heart failure with mildly reduced ejection fraction (HFmrEF) is controversial. Left bundle branch area pacing (LBBAP) is an emerging pacing modality and an alternative option to CRT. This analysis aimed to perform a systematic review of the literature and meta‐analysis on the impact of the LBBAP strategy in HFmrEF, with left ventricular ejection fraction (LVEF) between 35% and 50%. PubMed, Embase, and Cochrane Library were searched for full‐text articles on LBBAP from inception to July 17, 2022. The outcomes of interest were QRS duration and LVEF at baseline and follow‐up in mid‐range heart failure. Data were extracted and summarized. A random‐effect model incorporating the potential heterogeneity was used to synthesize the results. Out of 1065 articles, 8 met the inclusion criteria for 211 mid‐range heart failure patients with an implant LBBAP across the 16 centers. The average implant success rate with lumenless pacing lead use was 91.3%, and 19 complications were reported among all 211 enrolled patients. During the average follow‐up of 9.1 months, the average LVEF was 39.8% at baseline and 50.5% at follow‐up  from implant to follow‐up for baseline LVEF between 35% and 50% versus LVEF <35%.▪ Left bundle branch area pacing (LBBAP) was found to significantly shorten QRS duration and improve systolic cardiac function in patients with a LVEF of 35%−50%.▪ In patients with heart failure with mildly reduced ejection fraction, LBBAP resulted in a significant increase in ejection fraction. Among studies satisfying the above criteria, a pooled analysis of patients with a baseline LVEF of 35%−50% was used. Editorials, review articles, case reports/letters, and abstracts were excluded. The quality of the literature was evaluated by the above two researchers using the Newcastle−Ottawa scale criteria.2.3I2; I2 > 50% was considered to indicate significant heterogeneity.p for bias was >.05, it was judged that there was no publication bias.p < .05 were considered to be statistically significant. Statistical analyses were performed using R programming version 4.0.3 .To evaluate the change in LVEF and QRS duration over time, means, standard deviations, and sample sizes were extracted from articles to estimate the overall average values and confidence intervals (CIs). Statistical heterogeneity was conducted by calculating Higgins 33.1In total, 694 articles were retrieved after excluding duplicates. The title and abstract of the articles were screened, and 566 were excluded due to being editorials/review articles, case reports/letters, having no relevant outcome, and not being in English. The remaining 128 articles underwent full‐text review, and 120 were excluded for not meeting the inclusion criteria; finally, eight studiesn = 211; 95% CI: 58.4−71.8), and 52.4%  of patients were male. The average baseline QRS duration and LVEF were 153 ms  and 40% , respectively. The average follow‐up period was 9.1 ± 3.8 months. Regarding quality assessment, the Newcastle−Ottawa scale criteria were used to evaluate the quality of observational studies  the only criterion used in all seven studies was paced QRS morphology, presented with a right bundle branch block morphology pattern in lead V1; (2) abrupt shortening of Stim‐LVAT (stimulus to a peak of the R wave) in leads V5 and V6 was used in four studies; (3) observed left bundle branch potential in pacing leads was used in four studies; and (4) demonstration of the transition from nonselective LBBP to selective LBBP was used in two studies. Only one study used contrast to ensure the location of the lead in the interventricular septum.3.3p < .01, I2 = 92%; Figure n = 42, 95% CI: 133.48−171.62 ms) at baseline, to 119.3 ± 10.9 ms  after LBBAP.Five studies presented both the baseline and follow‐up QRS durations, with means and standard deviations. Pooled analysis with a random effects model showed that LBBAP was related to a significantly reduced QRS duration , and 50.5 ± 3.9% at follow‐up (n = 132). During the average follow‐up of 9.1 ± 3.8 months, LVEF significantly improved  and 3.9% for HF with preserved ejection fraction .Seven studies presented both preimplant and postimplant LVEF values, with means and standard deviations Table . The ave3.4Among all studies, total complications related to the LBBAP procedure included 19 cases: 11 cases of repositioning to another location in the left bundle branch area due to septal perforation during the procedure, 3 cases of pneumothorax, 3 cases of pocket infection requiring incision and drainage, and 2 cases of pocket hematoma requiring evacuation. During the follow‐up period, 5 cases of lead dislodgements were observed.p < .01). One study reported hospitalization for HF after LBBAP in patients with HFmrEF; in this study, the HF hospitalization rate was 17.6% during a mean follow‐up of 6.0 months after LBBAP.One study reported both preimplant and postimplant New York Heart Association (NYHA) functional classes before and after LBBAP in patients with HFmrEF. In that study, during a mean follow‐up of 10.4 months, NYHA functional status in patients with HFmrEF who underwent LBBAP improved from 2.5 ± 0.5 at baseline, to 1.7 ± 0.8 at follow‐up .All studies included in this meta‐analysis performed LBBAP using lumenless pacing leads, with an average acute success rate of 91.3%. In 1 case series wherein LBBAP was performed in patients with HFmrEF using stylet‐driven leads, the success rate was 100% (4.2p < .01). The mean LVEF increase was 10.9% , and the NYHA functional status improvement was −0.8 . This suggests that LBBAP is clinically beneficial for resynchronization therapy in the treatment of HFmrEF.In this meta‐analysis, during the average follow‐up of 9.1 ± 3.8 months, the mean decrease in QRS duration after LBBAP in patients with HFmrEF was −34.51 ms  included in the analysis. Third, there was no long‐term follow‐up data. Fourth, in all studies included in the analysis, the pacing lead used for the procedure was a lumenless lead; therefore, there were no results for stylet‐driven leads. Finally, only one study reported clinical outcomes, including HF hospitalization and mortality. Thus, large‐scale randomized controlled trials with long‐term observations are needed.5In all studies included in this meta‐analysis, LBBAP in patients with HFmrEF was feasible and safe. In the pooled analysis, LBBAP was found to significantly shorten the QRS duration and improve systolic cardiac function in patients with an LVEF of 35%−50%. This suggests that the application of LBBAP as a resynchronization strategy for patients with HFmrEF could be an acceptable option, especially in patients with both HFmrEF and dyssynchrony, where a decrease in LVEF is anticipated. A randomized, prospective study is warranted to evaluate the effect of LBBAP‐CRT on patients with HF and an LVEF >35% and ≤35%.Ga‐In Yu and Tae‐Hoon Kim contributed to the conception of the study, searched the articles, independently reviewed all identifed articles for eligibility, performed the data analyses, and wrote the manuscript. Yun‐Ho Cho, Jae‐Seok Bae, Jong‐Hwa Ahn, and Jeong Yoon Jang assisted in data acquisition and review literature. Choong Hwan Kwak helped perform the analysis with constructive discussions. All authors reviewed the manuscript.The authors declare no conflict of interest.Supporting information.Click here for additional data file.


Mantidactylus pauliani is a locally endemic amphibian species restricted to mountain streams on the Ankaratra Massif, in the central highlands of Madagascar. This species has a highly restricted distribution, which makes it vulnerable to habitat destruction and, consequently, M. pauliani is considered one of the most threatened frog species in Madagascar. Therefore, having information concerning M. pauliani and its habitat is necessary for effective conservation. Our study aimed to examine the population status of M. pauliani by verifying its geographic distribution and elevational range, exploring habitat use, and assessing threats. M. pauliani occurs from 1900 m to 2378 m a.s.l. and is most abundant at an altitude between 1993 and 2166 m. Adults, juveniles, and tadpoles were associated with different levels of stream depth, speed, and width. We found that human activities are contributing to habitat losses, which is modifying its environment and threatening the species’ survival. The data collected on the occurrence and habitat use of M. pauliani serve as an “environmental alert dashboard” to promote sustainable conservation.M. pauliani, a typically aquatic and critically endangered amphibian found on the Ankaratra Massif. This species inhabits high elevations with a limited distribution range. Our study aimed to present new data on the distribution and elevational range, habitat use, and threats to M. pauliani and its occurrence according to habitat changes. To achieve this, annual monitoring was carried out from 2018 to 2021. Nine 100 m transects were established along streams at elevations ranging from 1762 to 2378 m a.s.l. along which we conducted visual encounter surveys. Data analysis was performed using a χ2 test and Factor Correspondence Analysis. We found that M. pauliani occupies elevations between 1900 and 2378 m a.s.l. within humid forests and savannah habitats. The results showed a fluctuation in the number of animals observed and a higher occurrence at higher elevations throughout the years according to the season, stream quality, and water volume. Ongoing habitat alteration makes M. pauliani vulnerable to population decline, with annual bushfires likely having a negative impact on habitat. Mountain summits in Madagascar generally have species with specific habitat requirements, providing a home to a unique and locally endemic herpetofauna. Among them is  Mantidactylus pauliani [M. pauliani is a typically aquatic species [The Ankaratra forest, one of the biodiversity hotspots in Madagascar, is home to the locally endemic and Critically Endangered amphibian, pauliani ,2. This pauliani ,4,5, and species , its dis species ,7,8.However, in the last few decades, the forest  and its M. pauliani and its highly dependent behavior on streams, it is likely to be sensitive to habitat change [M. pauliani population.Considering the limited distribution of t change , making t change . Long-teM. pauliani within a spatiotemporal approach. Based on previous research [M. pauliani population. More specifically, this study explored the relationship between this species and their occurrence by focusing on their spatio-altitudinal distribution and ecological parameters, once the knowledge on habitat use and threats has been identified. The new information gathered during this research can help us understand the ecological guilds and abundance variation of this critically endangered frog. While M. pauliani reproduces during both humid and dry seasons, the humid season represents the seasonality in months, and the variability is significant. These data are needed to produce an effective and sustainable conservation action plan.The aim of this study was to present the new data on the spatial distribution and occurrence, habitat use, and threats to research ,12,14 anThe study was conducted within the New Protected Area (NPA) of Ankaratra, which is one of the few remaining forests in the central highlands of Madagascar, covering about 8130 hectares . It exteM. pauliani according to the season (dry and humid) and the different habitats. The different types of ecological guilds, the presence of permanent rock formations in the streams, and elevation levels were taken into account when selecting the study sites. The sites cover the entire mountain range  and differ in terms of habitat characteristics and degree of degradation. Six sites were selected in 2018 and 2019, and three additional sites were included in 2020 and 2021, namely Maharavana, Analafohy, and Ambohimirandrana  was used to confirm whether the elevational distribution of M. pauliani for each developmental stage was significantly different according to the study season. It was also performed to determine if the numbers of this species by developmental stage vary by season. In addition, a multivariate analysis was carried out using correspondence factor analysis, which is a method for analyzing data when the variables to be studied are quantitative measures. We used correspondence factor analysis to evaluate the habitat use of the individuals for each developmental stage and their characteristics according to the physical parameters of the streams. It consisted of projecting the individuals  and the variables, such as water speed ranges , stream width , slopes , microhabitat , and stream substrates , which can influence the distribution of M. pauliani on a factorial plan. Data analysis was performed using Microsoft Excel. A Chi-square test . For all developmental stages, the number of individuals encountered varied significantly by season . Adults were more abundant than juveniles and tadpoles in the dry seasons , while tadpoles outnumbered adults and juveniles in the humid seasons . During the dry season (2021), more juveniles than tadpoles were observed (101 vs. 48).M. pauliani were recorded at an altitude between 1900 m and 2373 m. However, we observed most individuals at an altitude between 1993 and 2200 m, and the species was particularly numerous at 1993 m altitude during the years 2018 and 2019. Depending on season and altitude, the number of individuals encountered gradually decreased over time. This finding was particularly evident at the 2167 m altitude, where 1 adult, 2 juveniles, and 22 tadpoles were counted during the dry season (2018) and only 26 tadpoles during the humid season (2019). No individuals were observed here in 2020 and 2021. Generally speaking, their distribution along the mountain stream varied significantly for all developmental stages depending on the survey seasons .In terms of altitudinal distribution , M. paulFor all years and seasons, we observed more individuals along the forest transect than the savannah transect, with the exception of the 2020 humid season, when more tadpoles were observed in the savannah than in the forest . We alsoWe found adults, juveniles, and tadpoles to be associated with different habitat variables . In the We observed six threats types, most of which are related to human activities: bush fires, charcoal production, logging, grazing fires, trampling of waterways by cattle, and the expansion of agricultural areas on slopes. These threats lead directly or indirectly to the degradation of the habitat of this species see .However, the intensity of these different threat pressures varied depending on the type of formation and its proximity to the watercourse. The intensity of the threat was greatest in the open area where the pressure index was high, PI ≥ 0.5 , we observed more adults than juveniles and tadpoles , but there were more tadpoles during the reproduction period  than during the other periods . This indicates that the juveniles could reach maturity . It was noted that the number of tadpoles decreased quickly between the humid season (297/2020) and the dry season (48/2021); this might be possibly due to the fast-flowing streams between both periods and their impact on the speed of tadpole metamorphosis .The majority of the recorded individuals were found at the mid-slope (1900 m and 2200 m), where the forests are stable, and where there is a variety of refuges available in the form of rocks, fine sand, and gravel . In addiRegarding the habitat preferences of males and females across the survey periods, a higher number of males were found in forested areas at low elevations than in open and savannah habitats at high elevations, confirming the findings of previous studies ,26. TherM. pauliani was more abundant during the cold and dry seasons and decreased during the rainy season. This observation is similar to that observed by reference [M. pauliani throughout the year. However, the authors of reference [Regarding seasonal distribution, eference . Furthereference . This exeference  explaineeference . This isM. pauliani, where their presence and abundance correlate with the rock presence and also the water depth, degree of slope, water velocity, and stream flow. According to reference , the numAlthough forest degradation is a threat to the biodiversity of Ankaratra, this study showed that both savannah and forest represent important environments for this species to ensure its viability, a result similar to those previously put forward by the authors of reference . MoreoveWe recommend strengthening monitoring through habitat patrols by forest rangers, especially in the savannah habitat which may be important for breeding. The establishment of a firebreak system around the forest is also essential to minimize the damage caused by bushfires. Environmental education, awareness-raising, and consciousness-raising within the village community must also be undertaken. This will allow them to understand the importance of the forest and make them aware that biodiversity conservation will benefit them in the long term. Finally, the livelihoods of the local population should be ameliorated through the provision of water from Ankaratra.M. pauliani to habitat degradation and provided an assessment of the population status. The species is found at altitudes between 1900 and 2378 m, and adults and juveniles were more abundant in forests than in savannahs, while tadpoles preferred the savannah habitat. Our results also showed how the number of individuals encountered in surveys varies across seasons and years. During the study, we noticed a decrease in the number of individuals encountered for each age class at the most degraded site, Manotongana. The viability of M. pauliani depends on the quality and quantity of its habitat on the Massif, specifically the stream, and its degradation has a direct impact on the survival of the population. To effectively manage and conserve M. pauliani, information is needed about their habitat preference, population number, distribution across altitudes, and the threats they face. Our study provides some of this critical baseline data. We hope decision-makers can use our results as a tool in the development of a conservation strategy with proactive measures to prevent the irreversible loss of one of the emblematic species of the Ankaratra Massif.Overall, this study highlighted the vulnerability of


Objective and Impact Statement. We propose an automated method of predicting Normal Pressure Hydrocephalus (NPH) from CT scans. A deep convolutional network segments regions of interest from the scans. These regions are then combined with MRI information to predict NPH. To our knowledge, this is the first method which automatically predicts NPH from CT scans and incorporates diffusion tractography information for prediction. Introduction. Due to their low cost and high versatility, CT scans are often used in NPH diagnosis. No well-defined and effective protocol currently exists for analysis of CT scans for NPH. Evans’ index, an approximation of the ventricle to brain volume using one 2D image slice, has been proposed but is not robust. The proposed approach is an effective way to quantify regions of interest and offers a computational method for predicting NPH. Methods. We propose a novel method to predict NPH by combining regions of interest segmented from CT scans with connectome data to compute features which capture the impact of enlarged ventricles by excluding fiber tracts passing through these regions. The segmentation and network features are used to train a model for NPH prediction. Results. Our method outperforms the current state-of-the-art by 9 precision points and 29 recall points. Our segmentation model outperforms the current state-of-the-art in segmenting the ventricle, gray-white matter, and subarachnoid space in CT scans. Conclusion. Our experimental results demonstrate that fast and accurate volumetric segmentation of CT brain scans can help improve the NPH diagnosis process, and network properties can increase NPH prediction accuracy. This paper describes a novel and robust method for segmenting Computed Tomography (CT) scans of the brain and predicting possible Normal Pressure Hydrocephalus (NPH) from the segmentation. More than an estimated 700,000 Americans have NPH, but due to the presence of confounding comorbidities and the lack of a rigorous diagnosis protocol, the majority of cases are under- or misdiagnosed  as otherNPH afflicts mainly elderly patients, often with comorbid factors such as Parkinson’s or Alzheimer’s disease, and is commonly accompanied by symptoms of dementia. More specifically, cognitive dysfunction, changes in gait, and urinary incontinence are major symptoms indicating the presence of NPH . CurrentSometimes, Evans’ index, a 2D manually computed ratio illustrated in Figure Current guidelines define ventricular enlargement with an Evan’s index of greater than 0.3 [A 3-dimensional multiclass volumetric method of measuring the relevant regions of the brain could help to mitigate these challenges and holds promise for improving NPH differential diagnosis . Manual An automated method of computing Evan’s ratio from CT is presented in , but thiTo our knowledge, our proposed method is the first to predict NPH by first fully segmenting the subarachnoid space, lateral ventricles, and gray-white matter of the brain from a CT scan. An automated method of segmenting all of the relevant regions in the brain from a CT scan would greatly aid in the discovery and treatment of patients with NPH. Moreover, changes in brain connectivity due to the enlarged lateral ventricles may be modeled from this segmentation and its effects used to aid in NPH prediction.The connectome is a map of the white tissue structures connecting different regions in the brain, which consist of axonal bundles that neurons use to communicate with one another. These white tissue structures can be seen using diffusion MRI, an imaging method which allows us to see the diffusion properties of water through the matter being imaged. Since water travels in a directed pattern through axonal bundles, they are visible through this method. Diffusion orientation computation methods and fiber tracking . Since patient-specific diffusion imaging is not gathered in a typical NPH clinical workflow, we propose an inventive method to approximate changes in the connectome using the segmented scan and a diffusion MRI atlas. The network metric derived from this approximated connectome is used as additional information during the NPH prediction process. To our knowledge, this is the first time connectome information has been combined with volumetric segmentation features to predict the presence of a disorder such as NPH.(1)We have developed a robust, data-driven CT segmentation method which is derived from data from NPH and age-matched normal patients which can aid in NPH diagnosis. Our algorithm is the first of its kind to take into account the spatial distribution of the regions of interest. The robustness of our algorithm allows for the segmentation of CT scans from both normal and NPH subjects, which has historically been a challenge even with deep learning (2)Additionally, we combine diffusion tractography information with the segmentation in a novel way to improve NPH prediction(3)https://github.com/UCSB-VRL/NPH_Prediction/tree/connectomeThe creation of a novel and valuable dataset of detailed and full manual segmentations of CT brain scans. This data will be made publicly available and can further benefit the medical research community. The code is available on GitHub at The major contributions of this paper are as follows. To study the morphological differences between NPH and non-NPH patients and create a pipeline for predicting NPH, CT brain scans are collected from patients with and without NPH. To incorporate additional white matter structural (diffusion tractography) information into the NPH prediction process, diffusion MRI of normal subjects between the ages of 75 and 85 are collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).The CT data comes from two sources: the University of California Irvine Medical Center (UCI) and the Santa Barbara Cottage Hospital. This is a retrospective study, with all images deidentified as specified by the IRB agreement between each medical center and the University of California, Santa Barbara.There is no protocol determining the number of slices, orientation, or other imaging parameters for the data used in this study. CT scans of 40 manual segmentations are performed by members of the research team under direct supervision and validation by a neurological surgeon. Each annotation took approximately 20 hours to complete and includes the subarachnoid space, ventricles, gray-white matter, and cerebellum. The annotation is first initialized using semisupervised snake segmentation through the ITK-SNAP tool , then fFor annotation consistency using ITK-SNAP, the viewing window is adjusted to have a viewing intensity minimum of The refined annotation is compared to the initial semisupervised segmentation. Evan’s index, measured under direct supervision of a neurological surgeon, is calculated for all subjects.As noted earlier, diffusion tractography information is incorporated in a novel way into the NPH prediction process to improve the prediction results. In addition to the CT data, diffusion MRI of 11 normal subjects between the ages of 75 and 85 from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) are used to create an average connectome with which to conduct connectivity studies comparing NPH and non-NPH subjects.First, the CT image is segmented into three regions of interest (ROI)—the gray-white matter, subarachnoid space, and lateral ventricles—using a modified trained 3D UNet. These ROIs are important to NPH prediction due to the enlargement of the lateral ventricles in relation to the rest of the brain which occurs during NPH. The UNet uses both the original CT scan and a probability map created from the ground truth annotations to provide contextual data to the upsampling layers. The segmented volumes are used to create a subject-specific connectome from average older subject diffusion MRI tractography. The segmented volumetric and diffusion tractography information are used as input features to a fully connected layer to perform feature fusion. The fused features are then used to make the final prediction of NPH vs. non-NPH. Figure Input: CT scan of the subject, MNI152 Atlas, and population average diffusion data for diffusion tractography computation in the MNI152 space Output: 3D segmentation of CT scan into 3 regions, and NPH score 1 Compute the affine transform matrix 2 Compute probability maps using ground truth annotations and transform it into the subject space using 3 The CT scans are segmented using modified 3D UNet and affine transformed probability maps. The resulting segmentation is mapped back to the MNI152 space using 4 Compute ROA (Region of Avoidance) tractographs using the ventricles as the ROA5 Compute patient-specific connectivity matrix and the derived network properties6 Using the segmentation volumes and network properties, predict whether the subject has NPHWe modified a 3D UNet architecture to perform accurate segmentations of the lateral ventricles, subarachnoid space, and gray-white matter in Computed Tomography (CT) scans of the brain. The relative values in each CT scan are preserved to maintain density information. In preparation for the next steps, an affine transform matrix is computed by matching the features of the CT scan to an MRI MNI152 atlas using FSL FLIRT . The orThree-dimensional convolutional neural network models are currently the state-of-the-art for medical image segmentation. Because many of the most successful models are variants of 3D UNet . These u and He ), and anWhile the base 3D UNet model provided good results for brain CT segmentation, the trained network still failed to differentiate between subarachnoid space and ventricle on some border regions. In addition to this, subarachnoid space would often be misclassified as gray-white matter if the subarachnoid spaces are thin, as the intensity values are lighter for thin subarachnoid spaces. Since the occurrence of subarachnoid space and ventricles are highly similar between subjects, a location-aware layer is added to the network to boost performance in these areas. Regional probability maps are generated from the ground truth annotations and used in the upsampling layer of the 3D UNet. The probability maps are created by averaging all of the ground truth annotations once they have been registered to a common space (MNI152). The same probability map is used for each patient, but it is transformed into that patient’s space using a reverse affine transformation that is calculated through the registration process. Two convolutional layers and a RELU are used to learn the weights with which to apply each probability map, and the output of the RELU is concatenated to the output features of the 3D UNet at the last upsampling layer. The dimensions of the input and output to the probability maps layers are Since the swelling of the ventricles that occur during NPH may result in damaged white matter tracts that affect brain connectivity as a whole, we analyzed the effect of using white matter disturbance information in the NPH prediction process. However, diffusion MRI are not commonly collected from patients with suspected NPH in a clinical setting. Therefore, we used a proxy for the possible white matter disturbances by modifying the average diffusion tractography from normal (control) older subjects in the ADNI dataset with the automated segmentation outputs of each subject. Deterministic fiber tractography using QSDR reconstruction (Yeh and Tseng ) is condFor each subject in the NPH dataset, the predicted ventricle segmentation is used as a Region of Avoidance (ROA) during fiber tractography. Affine transformations are computed using FSL  in MNI1r et al. .The volumes per class from the modified 3D UNet segmentation results are concatenated with the patient-specific network properties defined in Table The modified 3D UNet with the probability map modification is trained on 30 segmented CT scans using a learning rate of 0.001, Adam optimizer, weight decay of 0.0001, dropout rate of 0.5, and hard per image cross-entropy for 300 epochs. The segmentation masks have 6 classes—the ventricle, subarachnoid space, and gray-white matter, and the same tissue classes in the cerebellum. The cerebellum is differentiated from the rest of the brain so that its volume can be observed and monitored separately for future medical studies. Fivefold cross-validation is used to verify the segmentation accuracy of the model. Example results of our segmentation algorithm are shown in Figure Some basic machine learning methods are implemented to compare with the proposed method. They include random forest (RF) classification, 3D morphological geodesic active contours (MGAC) , and 3DThe implementations of these alternative methods of ventricle segmentation use thresholding to find the skull region and remove any labels outside of this region. Each implementation first computes and applies the affine transformations into MNI152 space, then computes and applies the inverse transformation after completing segmentation. For the MCV and MGAC methods, the volumes are seeded in anatomically informed locations pertaining to the gray-white matter. The regions are then grown according to their perspective algorithms.For the scores in Table The results of Table The proposed method is unique in that it allows for better separation of ventricle space and subarachnoid space. The subarachnoid space and the ventricles are both composed of cerebrospinal fluid, so they show up with similar intensities on a CT scan. Our method successfully separates these similar-looking regions with high performance.The following plots further analyze the results of the segmentations for NPH and normal subjects. Figures For comparison, each scan is labeled with Evan’s ratio as measured under direct supervision of a neurological surgeon. NPH predictions on the labeled subset using only Evan’s ratio are first computed by the current guidelines, with subjects having Evan’s ratio greater than or equal to 0.3 classified as NPH, and the remaining subjects classified as non-NPH.Precision and recall are calculated for 3 methods of NPH prediction—thresholding of the manually annotated Evans’ index, using fully connected layers with the modified 3D UNet features, and using fully connected layers with the modified 3D UNet features along with the network properties.Precision is defined as the number of true predicted positives over the number of all predicted positives. Recall is defined as the number of true predicted positives over the total number of actual positives. Essentially, precision is a proxy for how many selected elements are relevant, while recall is a proxy for how many relevant elements are selected.As seen in Table We plot the AUC and feature importance of the SVM in Figures Feature importance was calculated by using 5-fold cross-validation to generate class membership probabilities using logistic regression on SVM’s scores (Platt and Karampatziakis ). After The paper presents a fully automated, volumetric method of lateral ventricles, subarachnoid space, and gray-white mass segmentation in CT scans. Additionally, this paper proposes a fully automated method to predict NPH diagnosis, which, in conjunction with the clinical symptomatology, can facilitate the diagnosis of NPH and rule out subjects who do not meet the radiographic criteria of an NPH diagnosis. This technological system outperforms the thresholding method using Evan’s ratio and can be used as a screening tool to identify or stratify possible NPH cases in a clinical setting. The segmentation model for this paper can be used to segment and study the volumes of CT brain scans in cases other than NPH.Furthermore, this paper contributes a novel method of using network properties to aid in NPH diagnosis prediction and explores potential brain regions most affected by NPH by studying the connectivity changes that may occur during ventricle dilation.The work presented in this paper is intended as a proof of concept, with representative samples of CT scans from subjects in each category. The network is sensitive to differences in CT appearance due to age, so a fusion of networks may be used in the future to accommodate patients of all ages, not only those in the NPH risk range. Additionally, it would be beneficial to provide more examples of CT scans with high resolution in the sagittal and coronal planes, to make the model robust to scanning direction. One intrinsic limitation of this paper is the idiopathic nature of NPH, meaning it is diagnosed when other conditions have been ruled out. This could lead to a biased dataset. We would like to include more confounding factors in future studies, such as the presence of Alzheimer’s, Parkinson’s, or non-NPH hydrocephalus.Currently, the runtime for diffusion tractography and network analysis takes approximately 1.5 minutes per subject on a standard computer with 64 GB of RAM. It is possible to explore alternatives to the tractography process using methods such as probabilistic tractography, as described in  or tracTo conclude, autosegmentations of CT scans are helpful because CT scans are more common, readily available, and accessible compared to MRI scans. Since autosegmentations of CT scans have not been done before in such detail, this machine-learning-based algorithm can be applied to study many other neurological conditions. In particular, changes over time with serial CT scans can be examined both retrospectively and prospectively. For example, CT scans of patients with Alzheimer’s disease, TBI, or NPH can be analyzed to compare the ratios of ventricles to subarachnoid to the cerebrum. Changes in these ratios can hold valuable information about the progression/resolution of these disease entities. Furthermore, with respect to NPH, this ability to do this type of detailed volumetric analysis space offers tremendous potential for determining whether or not there are changes reflective of proper shunt functioning.


Tumor necrosis factor exerts many adverse biological effects, from cell proliferation to cell death. Accurate diagnosis and treatment are therefore difficult due to many factors influencing tumor necrosis factor-alpha (TNF-α) signaling, including microRNAs (miRNAs), especially in tumors. The aim of the study was to determine the influence of miRNAs on the expression profile of genes and proteins related to TNF-α signaling in endometrial cancer.The material consisted of 45 endometrioid endometrial cancer and 45 normal endometrium tissue samples. Gene expression was determined with microarrays and then validated for TNF-α, tumor necrosis factor receptor 1 (TNFR1) and 2 (TNFR2), caveolin 1 (CAV1), nuclear factor kappa B subunit 1 (NFKB1), and TGF-beta activated kinase 1 (MAP3K7)-binding protein 2 (TAB2) using real-time quantitative reverse transcription reaction (RT-qPCR). The protein concentration was assessed by enzyme-linked immunosorbent assay (ELISA). In addition, differentiating miRNAs were identified using miRNA microarrays and their relationships with TNF-α signaling genes were evaluated using the mirDIP tool.TNF-α, TNFR1, TNFR2, CAV1, NFKB1, and TAB2 were upregulated both on the mRNA and protein levels. The decrease in the activity of miR-1207-5p, miR-1910-3p, and miR-940 may be related to CAV1 overexpression. Similarly for miR-572 and NFKB1 as well as miR-939-5p and TNF-α. In turn, miR-3178 may partially inhibit TNFR1 activity up to grade 2 cancer.TNF-α signaling, especially the TNF-α/NF-κB axis, is disrupted in endometrial cancer and worsens with disease progression. The observed changes may be the result of miRNAs’ activity in the initial stage of endometrial cancer and its gradual loss in later grades. Endometrial cancer is one of the most commonly diagnosed gynecological cancer worldwide  is a pleiotropic cytokine that is largely involved in inflammation and the immune response. Its activity is possible due to its binding to tumor necrosis factor receptor 1 (TNFR1) and 2 (TNFR2), which results in the activation of numerous signaling cascades Wajant . DependiThe aim of the study was to determine the influence of miRNAs on the expression profile of genes and proteins related to TNF-α signaling.Among 106 mRNAs corresponding to genes related to TNF-α signaling, significant expression changes were noted for 14 mRNAs, including 2 for G1, 8 for G2, and 11 for G3. The construction of the Venn diagram revealed which mRNAs are characteristic of a given grade and which are common  analysis based on the GEPIA database was performed for the studied genes. The results are shown in Fig. TNF, low-TNFR1, and high-NFKB1. In the case of TNFR2, worse OS was observed for low-TNFR2 only after 100 months, and similarly for CAV1 and TAB2.The analysis showed a similar OS result for both the high and low levels of each gene group. From about 40 months, better OS was noted for high-Using the GEPIA database, it was also noted that the studied genes do not belong to the top 100 most differential survival genes for both overall survival and disease-free survival.TNF, TNFR1, TNFR2, CAV1, NFKB1, and TAB2 gene expression  belongs to the family of structural proteins involved in caveolae formation, which are regulators of signal transduction. Interestingly, caveolin 1 deficiency is associated with premature cell aging due to mitochondrial dysfunction , associated with the TNF receptor complex . The collected surgical samples were subjected to histopathological evaluation and divided into three subgroups according to the degree of histological differentiation: G1, 15 samples; G2, 15 samples; G3, 15 samples. The exclusion criteria were the diagnosis of non-endometrioid endometrial cancer, endometriosis, coexistence of another cancer, extreme obesity, and use of hormone therapy 24 months prior to surgery. The control group consisted of 45 patients without neoplastic changes who underwent surgery due to the prolapse of the uterus. The absence of cancer was also confirmed histopathologically. Patient characteristics are presented in Table The collected tissue samples were placed in tubes containing Allprotect Tissue Reagent  and stored according to the manufacturer’s instructions. Total RNA was extracted using the TRIzol reagent . Its quality was assessed by electrophoresis  and its quantity was evaluated by spectrophotometry .http://pathcards.genecards.org/) accessed on April 27, 2022  and the GeneChip™ HT 3′IVT PLUS Reagent Kit  were used to determine the expression profile of genes involved in TNF-α signaling. 8 µg of RNA was used as a template to synthesize cDNA with SuperScript Choice System . BioArray HighYield RNA Transcript Labeling Kit  was then used to synthesize biotinylated cRNA. It was later purified with RNeasy Mini Kit . The next step included fragmentation of the biotin-labeled cRNA with the Sample Cleanup Module Kit . After hybridization to the microarray, cRNA was stained with streptavidin–phycoerythrin. A GeneArray scanner  was used to acquire the fluorescence signals. The list of genes related to TNF-α signaling was prepared based on data from the PathCards database  and β-actin (ACTB) as endogenous control. The thermal profile included reverse transcription , polymerase activation , and 40 cycles of denaturation , annealing , and elongation .ACTB cDNA). Opticon™ DNA Engine Sequence Detector  calculated the mRNA copy numbers of studied genes in each sample. Table For each run, a standard curve was plotted based on the β-actin quantitative standard  at five different concentrations , Human TNF-R1 ELISA Kit , Human TNF-R2 ELISA Kit , Human Caveolin 1 ELISA Kit , Human Nuclear Factor Kappa B (NFkB) ELISA Kit , and Human TGF-beta-activated kinase 1 and MAP3K7-binding protein 2 ELISA Kit .The miRNA expression profile was determined with miRNA 2.0 microarrays  according to the manufacturer’s protocol. GeneChip Scanner 3000 7G  and Affymetrix GeneChip Command Console Software (AGCC) were used to read the obtained signals.The mirDIP database was used to predict miRNAs targets among genes related to TNF-α signaling. The miRanda algorithm and bidirectional search with very high confidence filter were used . Analysis of the RT-qPCR and ELISA results was performed on R using RStudio . The GEPIA database was used for overall survival analysis (http://gepia.cancer-pku.cn/).Analysis of results from mRNA and miRNA microarray experiments was performed using the Transcriptome Analysis Console software . ANOVA and Tukey’s post hoc test were performed, and a Venn diagram was constructed (


Heart failure with preserved ejection fraction (HFpEF) accounts for half of all heart failure presentations and is associated with a dismal prognosis. HFpEF is an umbrella term that constitutes several distinct pathophysiological entities. Coronary microvascular dysfunction (CMD), defined as the inability of the coronary vasculature to augment blood flow adequately in the absence of epicardial coronary artery disease, is highly prevalent amongst the HFpEF population and likely represents one distinct HFpEF endotype, the CMD-HFpEF endotype. This review appraises recent studies that have demonstrated an association between CMD and HFpEF with an aim to understand the pathophysiological links between the two. This is of significant clinical relevance as better understanding of the pathophysiology underlying CMD-HFpEF may result in more targeted and efficacious therapeutic options in this patient cohort.There is a high prevalence of CMD, diagnosed invasively or noninvasively, in patients with HFpEF. Patients with HFpEF who have an impaired myocardial perfusion reserve (MPR) have a worse outcome than those with a normal MPR. Both MPR and coronary flow reserve (CFR) are associated with measures of left ventricular diastolic function and left ventricular filling pressures during exercise. Impaired lusitropy and subendocardial ischaemia link CMD and HFpEF mechanistically.CMD-HFpEF is a prevalent endotype of HFpEF and one that is associated with adverse cardiovascular prognosis. Whether CMD leads to HFpEF, through subendocardial ischaemia, or whether it is secondary to the impaired lusitropy that is characteristic of HFpEF is not known. Further mechanistic work is needed to answer this pertinent question. Up to 50% of patients with angina have nonobstructive coronary arteries (ANOCA) . ANOCA iCoronary microvascular dysfunction can result from altered function of endothelial cells, leading to attenuated nitric oxide (NO) production (endothelium-dependent microvascular dysfunction), or it can be because of the inability of the vascular smooth muscle (VSM) cells to vasodilate in response to NO (endothelium-independent microvascular dysfunction) . In clinet al.; they reported a high prevalence of CMD (71%) in the HFpEF group, with higher right ventricular systolic and mean pulmonary pressures in those with an impaired CFR [et al.[It is not known whether a specific CMD endotype predominates within the coronary microvascular dysfunction and heart failure with preserved ejection fraction (CMD-HFpEF) population. Mohammed et al. have repet al., which il.[et al.▪ also rel.[et al. have alsl.[et al.. Other gl.[et al., have rel.[et al.. Here, Ml.[et al.. Howeveroutcomes ▪. This routcomes ▪. Dryer ired CFR . WhetherR [et al. investigR [et al.. EndotheR [et al.. The finTwo potential mechanisms, linking CMD and HFpEF, have been identified. These will be discussed in detail below.The novel paradigm of HFpEF pathophysiology implicates the NO pathway in HFpEF pathogenesis . A systeFurthermore, an up-regulation of inducible nitric oxide synthase (iNOS) has also been implicated in the pathogenesis of HFpEF . PharmacThese purported mechanistic links place the NO pathway at the centre of CMD-HFpEF pathogenesis.Previous studies have demonstrated that patients with HFpEF have an inability to adequately augment their MBF during stress , which cMyocardial perfusion is dependent on CFR and the dynamic interaction between myocardium and microvasculature. Coronary flow is linked to myocardial relaxation and contraction; this process is called cardiac–coronary coupling, which can be characterized by coronary wave intensity analysis . Wave inCoronary microvascular dysfunction is highly prevalent in patients with heart failure with preserved ejection fraction. CFR and MPR correlate with left ventricular diastolic function, LV filling pressures during exercise, and cardiac outcomes in patients with HFpEF. Impaired lusitropy and subendocardial ischaemia are the likely mechanistic links between CMD and HFpEF, although they are interlinked and identifying which comes first is often difficult to do. Further mechanistic work is needed to better characterize the CMD-HFpEF endotype with the end goal of better therapeutic options in this patient cohort.None.A.S. is the recipient of a UK Medical Research Council Clinical Research Training Fellowship grant (MR/T029390/1).There are no conflicts of interest.


To summarize experimental and clinical evidence on the association between tumor necrosis factor-α (TNF-α) and nonalcoholic fatty liver disease (NAFLD) and discuss potential treatment considerations.Experimental evidence suggests that TNF-α is a cytokine with a critical role in the pathogenesis of NAFLD. Although, the production of TNF-α may be an early event during the course of nonalcoholic fatty liver (NAFL), TNF-α may play a more substantial role in the pathogenesis of nonalcoholic steatohepatitis (NASH) and NAFLD-associated fibrosis. Moreover, TNF-α may potentiate hepatic insulin resistance, thus interconnecting inflammatory with metabolic signals and possibly contributing to the development of NAFLD-related comorbidities, including cardiovascular disease, hepatocellular carcinoma, and extra-hepatic malignancies. In clinical terms, TNF-α is probably associated with the severity of NAFLD; circulating TNF-α gradually increases from controls to patients with NAFL, and then, to patients with NASH. Given this potential association, various therapeutic interventions  have been evaluated for their effect on TNF-α and NAFLD. Interestingly, anti-TNF biologics have shown favorable metabolic and hepatic effects, which may open a possible therapeutic window for the management of advanced NAFLD.The potential key pathogenic role of TNF-α in NAFLD warrants further investigation and may have important diagnostic and therapeutic implications. Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent disease affecting approximately 30% of the general population; the prevalence is much higher in certain populations, such as patients with type 2 diabetes mellitus (T2DM) and obesity, reaching 60% and 90%, respectively . AlthougNASH and hepatic fibrosis are associated with increased risk of hepatic complications, including cirrhosis and HCC, as well as extra-hepatic complications, including cardiovascular disease (CVD), chronic kidney disease, and extrahepatic malignancies . NASH isThis review, first, focuses on the possible pathogenic role of TNF-α in NAFLD; second, summarizes clinical evidence on the association between TNF-α and NAFLD; and third, discusses potential treatment considerations derived from this association.NAFLD is characterized by a state of chronic, low-grade hepatic and systemic inflammation affecting multiple organs beyond the liver . TNF-α iObesity may affect the liver, at least partly, through the secretion of adipokines , which are produced mainly but not exclusively by the adipocytes, and cytokines , which are produced mainly by the immune cells infiltrating the adipose tissue when it expands; there is an ever continuing and dynamic interplay among various adipokines and cytokines, exhibiting synergistic or antagonistic action . As for In the liver, KCs respond to two main types of stimuli: the intrahepatic danger-associated molecular patterns (DAMPs), which are released by the lipid-infiltrated and damaged hepatocytes, and the gut-derived bacterial antigens, also known as pathogen-associated molecular patterns (PAMPs), which translocate from the intestine to the liver due to an impaired intestinal epithelial barrier . Both DAOnce released, TNF-α manifests its biological functions by binding its cognate receptors, TNF receptor 1 (TNFR1) and TNF receptor 2 (TNFR2), which are expressed on the cell membrane . Bindingde novo lipogenesis; it is highlighted that insulin is also a major regulator of the mTOR pathway [Although the production of TNF-α may be an early event in NAFL, potentially enhancing the severity of hepatic steatosis, NAFL is strongly associated with insulin resistance (IR), which is considered a major pathogenic driver of lipid accumulation in the liver . As ment pathway . An effeApart from its possible role in the pathogenesis of NAFL, TNF-α may play a more substantial role in the pathogenesis of NASH and NAFLD-associated fibrosis . In NASHHepatocellular death, another important feature distinguishing NASH from NAFL, is reciprocally connected with inflammation, as both processes may positively regulate each other . In the TNF-α is also involved in the pathogenesis of hepatic fibrogenesis. TNF-α induces the production of transforming growth factor-beta (TGF-β) by the hepatocytes and KCs, which triggers the activation, differentiation, and proliferation of hepatic stellate cells (HSCs) . In addiTNF-α may link inflammation and IR, two hallmarks of NAFLD pathogenesis. Mice lacking TNF-α or TNFR were, at least partly, protected from IR in several “loss-of-function” experimental studies . In lineTherefore, TNF-α may integrate both inflammatory and metabolic signals, potentially connecting inflammation with IR, which synergically deteriorate NAFLD. Of note, these interconnecting mechanisms may also predispose to the development of NAFLD-related comorbidities, including CVD and HCC. Both IR and increased circulating TNF-α have been associated with NAFLD and CVD. Based on mechanistic studies, TNF-α may be one of the factors linking NAFLD, IR, and CVD , 35, theThe above considering, TNF-α seems to be an important cytokine that potentiates hepatic IR and exhibits potential steatogenic, inflammatory, fibrogenic, and apoptotic effects in the liver. As a result, increased circulating and hepatic TNF-α may be associated with the onset and progression of NAFLD and its connection with hepatic complications and extrahepatic comorbidities. Figure Although most experimental and mechanistic studies suggest a causal role of TNF-α in the onset and progression of NAFLD from the early to advanced disease, clinical observational studies on the association between circulating TNF-α and NAFLD have yielded contradictory results. Most studies suggested that NAFLD patients had higher levels of circulating TNF-α than controls –43. HoweBecause of these heterogeneous and inconsistent findings, two meta-analyses on this topic have attempted to quantify the results of existing observational studies. In a meta-analysis of 56 studies, we demonstrated that circulating TNF-α was associated with the severity of NAFLD: TNF-α was higher in patients with NAFL than in non-NAFLD controls and higher in patients with NASH than NAFL or controls . Ιn metaDue to the potential association between TNF-α and NAFLD, there are experimental and clinical studies targeting to evaluate the effect of various therapeutic interventions on TNF-α and NAFLD. Furthermore, anti-TNF-α therapies in various diseases have opened a possible therapeutic window for the management of advanced NAFLD.This section provides an overview of current and emerging pharmacologic strategies for NAFLD that reduce circulating or hepatic TNF-α based on prevailing experimental or clinical evidence. These data are also summarized in Tables Obeticholic acid (OCA) is a potent farnesoid X receptor (FXR) agonist, an intriguing class of medication under investigation for the treatment of NAFLD. In addition to controlling a number of metabolic processes, including bile acid synthesis, glucose homeostasis, and lipid metabolism, OCA also exhibits anti-inflammatory and anti-fibrotic properties in the liver . OCA hasoff-label treatment in selected patients with biopsy-proven NASH and fibrosis stage (F) ≥ 2 [Peroxisome proliferator-activated receptors (PPARs) are a superfamily of lipid-sensoring nuclear receptors, which are considered promising therapeutic targets for NAFLD, as they regulate glucose and lipid metabolism, inflammation and possibly fibrosis . Pioglit (F) ≥ 2 . Similar (F) ≥ 2 , 69; how (F) ≥ 2 . It shou (F) ≥ 2 . Fenofib (F) ≥ 2 . In line (F) ≥ 2 –74. Simi (F) ≥ 2 –75. Saro (F) ≥ 2 . Lanifib (F) ≥ 2 . LanifibFollowing favorable effects on non-invasive biomarkers of hepatic steatosis and fibrosis by sodium-glucose co-transporter-2 (SGLT-2) inhibitors in patients with NAFLD , a phaseA number of RCTs have evaluated the efficacy and safety of probiotics in the treatment of NAFLD. The rationale lies on the proposed ability of probiotics to modulate the gut microbiome, thus beneficially affecting the gut-liver axis. At present, various strains, preparations, dosage schemes, and durations of treatment have been investigated on different NAFLD-related endpoints, which increases the heterogeneity between studies, thus rendering hard any secure conclusions. Probiotics improved LFTs, hepatic steatosis, plasma glucose and insulin levels, and lipid profile, but they did not affect body mass index (BMI) or circulating TNF-α, according to a meta-analysis of 21 RCTs involving 1037 patients with NAFLD . In contRifaximin is a broad-spectrum minimally absorbable antibiotic, which targets dysbiosis of intestinal microbiota and related endotoxemia. A 6-week course of 800 mg rifaximin daily in 15 histologically-proven NASH patients was not associated with robust changes in LFTs, hepatic steatosis, insulin sensitivity, and pro-inflammatory serum cytokines, including TNF-α . A previoff-label for selected NASH patients with F ≥ 2 for maximum 2 years [Vitamin E is a potent antioxidant, which may also exhibit anti-TNF-α action, as shown in rats with diet-induced NASH . Indeed, 2 years .n = 5), did not show a significant difference in TNF-α levels between pentoxifylline and placebo [Pentoxifylline is a xanthine derivative, which is a non-selective phosphodiesterase inhibitor, shown to histologically improve NASH in two meta-analyses , 91. TheUDCA, a secondary bile acid, was shown efficacy to reduce pro-inflammatory cytokines in animal studies . ClinicaFibroblast growth factor-21 (FGF-21) analogs or mimetics act at the same receptors as the endogenous hepatokine FGF-21, which is regarded as a promising molecule against hepatic steatosis, inflammation and apoptosis . B1344, Atorvastatin, a strong and widely used statin for the treatment of dyslipidemia , was shoDue to their triglyceride lowering effect, N-3 polyunsaturated fatty acids (n-3 PUFAs) were considered to be beneficial for NAFLD . SupplemAngiotensin receptor blockers (ARBs) have been proposed as alternative therapeutic option for NAFLD, mainly owing to their potentially anti-inflammatory and anti-fibrotic effects in the liver . Both vaGiven the potential steatotic, inflammatory, and fibrogenic effects of TNF-α in the liver, targeting TNF-α may be promising for the treatment of advanced NAFLD. TNF inhibitors are a class of biologic agents, which include infliximab, adalimumab, etanercept, golimumab, and certolizumab pegol, and have been widely used to treat chronic immune-related diseases, such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), and inflammatory bowel diseases (IBD) . Importa. Hepatic steatosis, although improved, seems to be less affected by anti-TNF agents than other histological features of NAFLD [Experimental evidence has shown favorable effects of anti-TNF approaches on NAFLD outcomes; administration of infliximab in rats with diet-induced NASH resulted in histological regression of hepatic inflammation and fibrosis . Hepaticof NAFLD .In the clinical setting, initial reports on the metabolic and hepatic effects of anti-TNF biologics derive mostly from observational studies in patients with RA and PsA. PsA patients receiving a 24-month course of etanercept and adalimumab showed an improvement in metabolic syndrome components, like waist circumference, triglycerides, high-density lipoprotein-cholesterol (HDL-C), and glucose, when compared with those treated with methotrexate . In lineConcerning IBD populations, most studies showed higher prevalence of NAFLD in IBD patients than the general population . Most st.Clinical trials assessing anti-TNF medications specifically in NASH patients are not yet available. Before initiating such studies, observational studies with patients on anti-TNF agents for other conditions, who also have concomitant NASH, would be an excellent starting point . Also, pCollectively, based on current mechanistic and experimental studies, TNF-α seems to be a contributor, critically implicated in the onset and progression of NAFLD. Furthermore, clinical data are showing higher circulating concentrations of TNF-α in NAFLD patients. Importantly, TNF-α may be associated with disease severity; more advanced phenotypes  seem to be associated with higher circulating TNF-α, which may also link NAFLD with extrahepatic manifestations, such as CVD and malignancies.Based on these considerations, this topic may have valuable perspectives and clinical implications, but also considerable challenges. TNF-α has been suggested as a potentially useful biomarker for the non-invasive stratification of patients with NAFLD , an hypo