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The OpenAIRE Graph (formerly the OpenAIRE Research Graph) is one of the largest open scholarly record collections worldwide. It is key in fostering Open Science and establishing its practices in daily research activities. Conceived as a public and transparent good, populated out of data sources trusted by scientists, the Graph aims at bringing discovery, monitoring, and assessment of science back into the hands of the scientific community. OpenAIRE collects metadata records from more than 70K scholarly communication sources worldwide, including Open Access institutional repositories, data archives, and journals. All the metadata records (i.e., descriptions of research products) are put together in a data lake with records from Crossref, Unpaywall, ORCID, ROR, and information about projects provided by national and international funders. This technical Report describes the main Aggregation Workflow to orchestrate the data aggregation and the implemented mapping from some of the main datasources into the OpenAIRE research graph data model.

The OpenAIRE Graph (formerly known as the OpenAIRE Research Graph) is one of the largest open scholarly record collections worldwide, key to fostering Open Science and establishing its practices in daily research activities. Conceived as a public and transparent good, populated out of data sources trusted by scientists, the Graph aims at bringing discovery, monitoring, and assessment of science back into the hands of the scientific community. Imagine a vast collection of research products all linked together, contextualized, and openly available. For the past years, OpenAIRE has been working to gather this valuable record. It is a massive collection of metadata and links between scientific products such as articles, datasets, software, and other research products, entities like organizations, funders, funding streams, projects, communities, and data sources. This technical Report describes the public data model adopted by the OpenAIRE Graph.

In recent years, a large number of Scholarly Knowledge Graphs (SKGs) have been introduced in the literature. The communities behind these graphs strive to gather, clean, and integrate scholarly metadata from various sources to produce clean and easy-to-process knowledge graphs. In this context, a very important task of the respective cleaning and integration workflows is deduplication. In this paper, we briefly describe and evaluate the accuracy of the deduplication algorithm used for the OpenAIRE Research Graph. Our experiments show that the algorithm has an adequate performance producing a small number of false positives and an even smaller number of false negatives.

InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.

The OpenAIRE aggregation workflow can collect metadata records from different providers about the same scholarly work. Each metadata record can carry different information because, for example, some providers are not aware of links to projects, keywords, or other details. Another typical case is when OpenAIRE collects one metadata record from a repository about a pre-print and another from a journal about the published article. To provide correct statistics, OpenAIRE must identify those cases and "merge" the two metadata records so that the scholarly work is counted only once in the statistics OpenAIRE produces. This technical Report describes the Deduplication workflow and technique adopted to deduplicate the OpenAIRE Graph.

Since 2012, the "Open Researcher and Contributor Identification Initiative" (ORCID) has been successfully running a worldwide registry, with the aim of unequivocally pinpoint researchers and the body of knowledge they contributed to. In practice, ORCID clients, e.g., publishers, repositories, and CRIS systems, make sure their metadata can refer to iDs in the ORCID registry to associate authors and their work unambiguously. However, the ORCID infrastructure still suffers from several "service misuses", which put at risk its very mission and should be therefore identified and tackled. In this paper, we classify and qualitatively document such misuses, occurring from both users (researchers and organisations) of the ORCID registry and the ORCID clients. We conclude providing an outlook and a few recommendations aiming at improving the exploitation of the ORCID infrastructure.

InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2020 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, e\-Sci\-ence, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, \ie D4Science and OpenAIRE. During 2020 InfraScience members contributed to the publishing of 30 papers, to the research and development activities of 12 research projects (11 funded by EU), to the organization of conferences and training events, to several working groups and task forces.

The HIV care continuum is a tool that describes the quality of HIV care for people living with HIV and assesses the extent to which the goal of viral suppression has been achieved. In 2014, we conducted a retrospective cross-sectional study to assess the characteristics associated with three steps of the HIV continuum of care in Italy [i.e., most recent diagnoses, people diagnosed and in care who are on therapy, and people with viral load (VL) suppressed among those on therapy]. Among the 10,262 individuals diagnosed and linked to care, 9,810 (95.6%) were on therapy and among these 8,383 (85.7%) had VL suppressed. The comparison between people diagnosed in 2013 to those diagnosed before 2013 shows that they were more likely to be male [adjusted odds ratios (AOR) = 1.46; 95% confidence interval (95% CI): 1.18-1.79]

Despite the hype, the effective implementation of Open Science is hindered by several cultural and technical barriers. Researchers embraced digital science, use “digital laboratories” (e.g. research infrastructures, thematic services) to conduct their research and publish research data, but practices and tools are still far from achieving the expectations of transparency and reproducibility of Open Science. The places where science is performed and the places where science is published are still regarded as different realms. Publishing is still a post-experimental, tedious, manual process, too often limited to articles, in some contexts semantically linked to datasets, rarely to software, generally disregarding digital representations of experiments. In this work we present the OpenAIRE Research Community Dashboard (RCD), designed to overcome some of these barriers for a given research community, minimizing the technical efforts and without renouncing any of the community services or practices. The RCD flanks digital laboratories of research communities with scholarly communication tools for discovering and publishing interlinked scientific products such as literature, datasets, and software. The benefits of the RCD are show-cased by means of two real-case scenarios: the European Marine Science community and the European Plate Observing System (EPOS) research infrastructure. © Springer Nature Switzerland AG 2019.

This work describes the specification of the OpenAIRE publishing APIs that support third-party services at publishing metadata about interlinked and packaged research products into the OpenAIRE Research Graph, in respect of the OpenAIRE interoperability guidelines (https://guidelines.openaire.eu). Research products generated by researchers using services of research infrastructures are today manually published by researchers in a repository external to their research infrastructure. This phase is often considered an extra burden, because researchers have to fill in metadata forms with information that is already available in the scope of the services they used. By using the OpenAIRE publishing APIs, services of research infrastructures can implement an on-demand publishing workflow for any type of research products to support their researchers at improving the FAIRness of their research products and relief them from the tedious step of finding a suitable repository and manually depositing the products in it.

Epstein-Barr virus (EBV) often accesses the central nervous system (CNS) where it may lead to blood brain barrier (BBB) integrity disruption, facilitating the migration of immune cells into brain parenchyma. Our aim was to study the association between cerebrospinal fluid (CSF) EBV DNA and HIV-1 compartmental replication. 281 HIV-positive adults undergoing lumbar punctures for clinical reasons (excluding those with lymphoproliferative disorders) and CSF samples were examined. CSF virological, neurodamage (tau, p-tau, 1-42 beta amyloid) and immune activation (neopterin and S100beta) markers were measured by immune-enzymatic, ELISA and PCR validated methods. Two hundred eighty one patients were included; 111 (40.5 %) were naïve for antiretroviral treatment. CSF EBV DNA was detectable in 25 (21.9%) naïve and 26 (16%) treated patients at low levels (ImportanceEBV is a human gamma-herpesvirus with a seroprevalence in adults approaches 95% and the pattern of clinical manifestations is very heterogeneous and varies from asymptomatic or mild viral infection to a tightly linked with several malignancies as nasopharyngeal carcinoma, Hodgkin’s lymphoma and Burkitt’s lymphoma. HIV-infected and immunocompetent patients were both at risk of primary infection and complications linked to EBV.Primary tropism of EBV is for lymphocytes (type B, T and NK), epithelial, endothelial and smooth muscle cells and establishes lifelong latent infection. Central nervous system could be affected by this herpesvirus in primary infection and reactivation and EBV-DNA is not an uncommon finding in CSF in HIV-infected population. The significance of our research is in identifying the presence of a link between HIV and EBV CNS replication.

The aim of this deliverable is to describe how the OpenAIRE data model is extended for the representation of artefacts different from publications and datasets. In particular, OpenAIRE-Connect extends the OpenAIRE data model with: (i) entities for there presentation of research communities, research methods and research packages; (ii) relationships between those new entities and the already existing OpenAIRE entities; (iii) new controlled vocabularies for properties of research methods and packages; and(iv) new termstobeaddedtocontrolledvocabulariesalreadyinusebytheOpenAIREinfrastructure. Requirements have been collected from the research communities involved in OpenAIRE-Connect, which helpedthedefinitionofthemodelextensionsbyspecifyingtheircurrentpracticeanddesiderataaboutthe publishingofresearchartefactsintheirspecificdiscipline.Inadditiontotherequirementsoftheresearch communities, requirements and expectations from the existing "consumers" of the OpenAIRE infrastructure, including data sources (providing content to OpenAIRE), portal end-users of various roles (researchers, project coordinators, general public, research communities), OpenAIRE data curators (responsibleoftheworkflowsforcollecting,harmonizing,de-duplicating,inferringcontent),andthird-party services(accessing content via APIs), have been considered. The data model will be subject to changes in the future, depending on the evolution of the requirements of the OpenAIRE infrastructure and of the communities involved in OpenAIRE-Connect.

OpenAIRE , the point of reference for Open Access in Europe, is now addressing the problem of enabling the Open Science paradigm. To this aim it will provide services to: (i) overcome the limits of today's scientific communication landscape, by allowing research communities and the relative e-infrastructures to fully publish, interlink, package and reuse their research artefacts (e.g. literature, data, and software) and their funding grants within the European and global ecosystem as supported/promoted by OpenAIRE, (ii) enable end-users (e.g. researchers, funder officers) to search and consult a rich and up-to-date knowledge graph of research results and (iii) enable scientific and educational information repositories and publishers to subscribe and be notified of changes in the OpenAIRE knowledge graph. These combined actions will bring long-term and immediate benefits to research communities, research organisations, repository managers, and funders by affecting the way research results are disseminated and reused. On the one hand, publishing the interlinked and packaged research literature, data and software via OpenAIRE drives research communities to an Open Science transition in a consistent and interoperable fashion. On the other hand, the resulting infrastructure concretely enables the construction of Open Science oriented services, supporting practices such as machine-assisted research reproducibility and evaluation.

The aim of this deliverable is to present the functional requirements, a specification of the software,and a release plan for the deployment of the OpenAIRE-connect Catch-All Notification Broker Service ( CAB Service ). The CAB Service will connect all types of research artefacts providers(institutional repositories,publishers, data, repositories,and CRIS systems) and allow them to subscribe and be notified by OpenAIRE of events interesting to them. These notifications will comprise: 1) the existence of artefacts of interest to the providers (which may pertain their collection) 2)the existence of links from artefacts in their collection to other artefacts. The CAB Service will extend OpenAIRE's notification brokering services, which serves literature repositories, and will broaden the content provider base with the ones that serve specific research communities. Content provider managers will be allowed to register as consumers of the service, set and test the service (preview the results of the service over some subscriptions), to commit their subscriptions, and finally to manage their history of notifications overtime. The broker service will be tested in two bata releases and changed and/or updated following the requirements obtained from the betas. The deliverable is published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D5_1.

The aim of this document is to explain in detail how the software release plan for upgrading OpenAIRE back-ends and Invenio according to the data model described in D4.1OpenAIREDatamodelextension will be accomplished by the technical partners. For this, it will illustrate the plan of design, development, testing, and integration into beta and production of the infrastructure services to be delivered by T4.1 (OpenAIRE extension to research methods and artifact packages) and T4.2 OpenAIRE's Zenodo for research methodsandartifactpackages).Theplan's technical activities will be supervised and led by CNR and carried out across the technical partners CNR and CERN, in synergy with the partners Jisc, UMinho, UniHB, PIN, CNRS,IRD,ICRE8. The deliverable is on-going and will be updated at M15 (before first BETA release of the service), M23 (beforesecondBETAreleaseoftheservice),andM27 (beforeproductionreleaseoftheservice).The first release of this document reports on extensions to be provided byM8. Toease the update of the planand support the collaborativeapproach, the deliverableis published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_2.

The aim of this deliverable is to provide the specification of the software and the release plan for the OpenAIRE publishing APIsthat support third-party services at publishingmetadata about interlinked and packaged research productsin to the OpenAIRE Information Graph. The OpenAIRE publishing APIs supports the concept of "continuous publishing" in digital research settings where researchers conduct their activities in digital laboratories using ICT tools and services for processing and analysing research data. By using the OpenAIRE publishing APIs, a service/tool can automatically publish metadata on behalf of the researchers. The service/tool and its underlying infrastructure is responsible for keeping persistent identifiers, preserving the payload of the objects and the metadata.The service pushes metadata into OpenAIRE,the effect being: o the metadata record is immediately visible via the OpenAIRE search portal and APIs; o the metadata record will be cleaned and de-duplicated in a second stage according to the OpenAIRE content provision workflow described at https://www.openaire.eu/aggregation-and-contentprovision-workflows and http://doi.org/10.5281/zenodo.996006. Researchers benefit from a service that uses the OpenAIRE publishing APIs in several ways: o The service will support the generation of metadata to improve the FAIRness of the relative research products; o Researchers are relieved of the burden of depositing the products they want to publish in a repositoryexternaltotheirdigitallaboratory; o Researchers can choose to publish research products at any step of their research activity. The full specification of the APIs are published as a wiki and available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_5.

In this thesis we start from the experiences and solutions for duplicate identification in Big Data collections and address the broader and more complex problem of 'Entity Deduplication over Big Graphs'. By 'Graph' we mean any digital representation of an Entity Relationship model, hence entity types (structured properties) and relationships between them. By 'Big' we mean that duplicate identification over the objects of such entity types cannot be handled with traditional backends and solutions, e.g .ranging from tens of millions of objects to any higher number. By 'entity deduplication' we mean the combined process of duplicate identification and graph disambiguation. Duplicate identification has the aim of efficiently identifying pairs of equivalent objects for the same entity type, while graph disambiguation has the goal of removing the duplication anomaly from the graph. A large number of Big Graphs are today being maintained, e.g. collections populated over time with no duplicate controls, aggregations of multiple collections, which need continuous or extemporaneous entity deduplication cleaning. Examples are person deduplication in census records, deduplication of authors on library bibliographical collections (e.g. Google Scholar graph, Thomson Reuters citation graph, OpenAIRE graph), deduplication of catalogues from multiple stores, deduplication of Linked Open Data clouds resulting from integration of multiple clouds, any subset of the Web, etc.. As things stand today, data curators can find a plethora of tools supporting duplicate identification for Big collections of objects, which they can adopt to efficiently process the objects of individual entity type collections. However, the extension of such tools to the Big Data scenario is absent, as well as the support for graph disambiguation. In order to implement a full entity deduplication workflow for Big Graphs data curators end-up realizing patchwork systems, tailored to their graph data model, often bound to their physical representation of the graph (i.e. graph storage), expensive in terms of design, development, and maintenance, and in general not reusable by other practitioners with similar problems in different domains. This first contribution of this thesis is a reference architecture for 'Big Graph Entity Deduplication Systems' (BGEDSs), which are integrated, scalable, general purpose systems for entity deduplication over Big Graphs. BGEDSs are intended to support data curators with the out-of-the-box functionalities they need to implement all phases of duplicates identification and graph disambiguation. The architecture formally defines the challenge, by providing graph type language and graph object language, defining the specifics of the entity deduplication phases, and explaining how such phases manipulate the initial graph to eventually return the final disambiguated graph. Most importantly, it defines the level of configuration, i.e. customization, that data curators should be able to exploit when relying on BGEDSs to implement entity deduplication. The second contribution of this thesis is GDup, an implementation of a BGEDS whose instantiation is today used in the real production environment of the OpenAIRE infrastructure, the European e-infrastructure for Open Science and Access. GDup can be used to operate over Big Graphs represented using standards such as RDF-graphs or JSON-LD graphs and conforming to any graph schema. The system supports highly configurable duplicate identification and graph disambiguation settings, allowing data curators to tailor object matching functions by entity type properties and define the strategy of duplicate objects merging that will disambiguate the graph. GDup also provides functionalities to semi-automatically manage a Ground Truth, i.e. a set of trustworthy assertions of equality between objects, that can be used to preprocess objects of the same entity type and reduce computation time. The system is conceived to be extensible with other, possibly new methods in the deduplication domain (e.g. clustering functions, similarity functions) and supports scalability and performance over Big Graphs by exploiting an HBase - Hadoop MapReduce stack.

The OpenAIRE infrastructure services populate and provide access to a graph of objects relative to publications, datasets, people, organizations, projects, and funders aggregated from a variety of data sources. Not only, objects in the graph are harmonized to achieve semantic homogeneity, de-duplicated and merged, and enriched by inference with missing properties and/or relationships. The OpenAIRE Literature Broker Service is designed to offer subscription and notification functionalities for institutional repositories to: (i) learn about publication objects in OpenAIRE that do not appear in their collection but may be pertinent to it, and (ii) learn about extra properties or relationships relative to publication objects in their collection. Due to the high variability of the information space the following problems may arise: (i) subscriptions may vary over time to adapt to information space evolution, (ii) repository managers need to be able to quickly test their configurations before activating them, (iii) notifications may be redundant, and (iv) notifications may be very large over time. This paper presents the data model and software architecture of the OLBS, specifically designed to address these issues.

The extent to which HIV-1 proviral DNA mutations cause clinically relevant antiretroviral resistance is still controversial. Paired plasma HIV-1 RNA and whole blood DNA were compared in patients failing HAART to investigate if the additional knowledge of archived mutations could improve the selection of potentially active drugs. Seventy-three HIV-1-infected patients with first/second HAART failure were studied before starting a new regimen based on RNA genotyping. Follow-up data after a 12-week therapy were available. DNA genotyping was retrospectively performed on stored whole blood samples and mutational profiles were compared to those from RNA. The mean number of IAS pol mutations was significantly higher in RNA (4.45 ± 2.76) than in DNA (2.88 ± 2.47) (P < 0.001). DNA genotyping provided a 6% increase in detection of resistance-associated mutations. Among 64/73 patients showing discordant DNA/RNA profiles, 54 (84%) also differed for predicted active drugs. 16/73 (22%) patients had ≥1 mutation revealed by DNA genotyping alone, probably affecting therapy success in 2/16. However, neither RNA/DNA discordance nor detection of isolated DNA mutations were statistically associated with outcome. In conclusion, plasma RNA remains the elective choice for HIV genotyping in patients with therapy failure, even if the detection of proviral resistance-associated mutations, not simultaneously found in RNA, is a frequent event. Therefore, in some cases DNA plus RNA genotyping might assist in choosing more accurately subsequent antiretroviral regimens. © 2008 Wiley-Liss, Inc.

The aim of this deliverable is to describe the structure and semantics of the OpenAIRE Information Space, i.e., the OpenAIRE data model, by providing an abstract definition of its main entities and the relationships between them. Requirements have been collected over the years from all "consumers" of the OpenAIRE infrastructure, including data sources (providing content to OpenAIRE), portal end-users of various roles (researchers, project coordinators, general public, research communities), OpenAIRE data curators (responsible of the workflows for collecting, harmonizing, de-duplicating, inferring content), and third-party services (accessing content via APIs). The data model will be subject to changes in the future, depending on the evolution of of the requirements of the OpenAIRE infrastructure, and this document will be updated accordingly.

This deliverable presents the plan of design and development of the OpenAIRE infrastructure services for the next 12 months. At month 12 and 24 an update of this deliverable will be produced. Its intended use is mainly for technical partners to locate their software release duties in the wider context of the project software release, but also for the generic reader to get an overall picture and insight view of the technical activities.

This deliverable describes the APIs offered by the OpenAIRE infrastructure to provide accessibility to the objects in its information space. APIs are organized by entity type (publication, dataset, and projects) and are characterized by access protocol, data exchange format, and schema.

The OpenAire infrastructure offers services for collecting records (publications, datasets, persons, organizations, data sources, projects) from external data sources with the purpose of identifying relationships between them. The collected objects and their relationships are stored in HBASE according to the OpenAIRE data model. The Action Manager framework has been designed to offer an OpenAIRE data model oriented API for the enrichment and the fixing of the OpenAIRE HBASE information space.

The OpenAIRE infrastructure services populate and provide access to a graph of objects relative to publications, datasets, people, organizations, projects, and funders aggregated from a variety of data sources. Not only, objects in the graph are harmonized to achieve semantic homogeneity, de-duplicated and merged, and enriched by inference with missing properties and/or relationships. The aim of this technical report is to describe to third-party service managers (developers in the need of accessing data) how the OpenAIRE information space can be accessed and according to which combination of protocol and format. The document is organized according to a data centric view, where managers should first identify the typology of data they would like to access, and then verify which protocols and formats are available.

This deliverable describes the APIs offered by the OpenAIRE infrastructure to provide accessibility to the objects in its information space. APIs are organized by entity type (publication, dataset, and projects) and are characterized by access protocol, data exchange format, and schema.

The deliverable describes how the services of the OpenAIRE infrastructure dedicated to collecting, storing, curating and indexing of content have been adapted to cope with management of data conforming to the data model (D6.1) of the OpenAIREplus infrastructure.

The goal of this deliverable is to (i) describe the motivations behind the realization of an authority file management service in OpenAIREplus, (ii) explicit the requirements of such a service, and (iii) define the specification of the service. Finally, it proposes a high-level description of the technical solution devised in the project and currently driving the implementation of the service.

The OpenAIREplus web site will offer functionalities for administrators, anonymous and registered users to manage an Information Space of publications, together with their connections with funding projects (from the EC and national agencies) and research datasets. The aim of this document is to describe the conceived structure and semantics of this Information Space, i.e., the OpenAIREplus data model, by providing an abstract definition of its main entities and the relationships between them. In this definitional process, the interaction with the EuroCRIS initiatives, several scientific institutes (i.e., KNAW-DANS, EBI-EMBL, BADC) as well as inspiration from DataCite and LinkedData play an important role in the specification of project data, i.e., how project data should be described, stored and exported in OpenAIRE, dataset metadata, how datasets should be described, and in the specification of how such interconnected entities can be made available and consumable by third-party systems. The data model will be subject to changes in the future and therefore result in further versions. Such changes will be described in the following Section, in order to summarize to the reader the differences form the previous versions.

The sesquiterpene bilobalide, extracted from Ginkgo biloba leaves, was tested in vitro and in vivo for the ability to inhibit Pneumocystis carinii growth. Bilobalide was inhibitory to trophozoites cultured on human embryonic lung fibroblasts (HEL 299) at approximately the same concentration as trimethoprim plus sulfamethoxazole (lowest effective concentration, 50 micrograms of bilobalide per ml versus 9/45 microgram of trimethoprim-sulfamethoxazole per ml), inducing microscopically detectable morphological changes in the cytoplasm of the parasite. In pharmacologically immunosuppressed Sprague-Dawley rats transtracheally infected with a suspension of about 5 x 10(6) P. carinii trophozoites per ml, the daily intraperitoneal administration of bilobalide (10 mg/kg of body weight for 8 days) lowered the number of organisms by approximately 2 logs (that is, about 99%). There was no apparent toxicity either in uninfected HEL 299 feeder cells or in infected and uninfected animals. These studies suggest that the sesquiterpene bilobalide might be useful for therapy of and prophylaxis against P. carinii infections in humans.

A sample of 300 sexually-active adults was selected at random from patients, from the rural area of Malenga Makali, Tanzania, who were attending a dispensary because they had diarrhoea of at least 2 weeks' duration. The potential associations between the patient's health (in terms of the World Health Organization's clinical definition of AIDS), HIV-1 seroprevalence and malaria and other parasitic infections were then investigated. Although, HIV-1 seroprevalence was 20.6% overall, the level of seroprevalence was directly correlated with the distance between the patients' home villages and the nearest main road. Strict application of the clinical definition of AIDS gave 98.7% specificity, 46% sensitivity and a predictive value of 90.6% when validated by HIV-1 seropositivity. Although malaria infection was more common in HIV-1 seropositives than in the seronegatives, the intensity of the Plasmodium falciparum infections, intestinal amoebiasis and giardiasis did not appear to be correlated with HIV-1 infection. In contrast, intestinal infections with Cryptosporidium parvum and Isospora belli were virtually restricted to HIV-1 seropositive individuals who had had diarrhoea for a relatively long time.