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The establishment and maintenance of protected areas(PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values.
Establishing and maintaining protected areas (PAs) is a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting PAs based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences as well as real-time comparison of the outcome. Applying the tool across 1,346 terrestrial PAs, we demonstrate that decision makers frequently face trade-offs among conflicting objectives, e.g., between species protection and ecosystem integrity. Nevertheless, we show that transparent decision support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
Background The differential diagnosis between follicular thyroid adenoma and minimal invasive follicular thyroid carcinoma is often difficult for several reasons. One major aspect is the lack of typical cytological criteria in well differentiated specimens. New marker molecules, shown by poly- or monoclonal antibodies proved helpful. Methods We performed global gene expression analysis of 12 follicular thyroid tumours (4 follicular adenomas, 4 minimal invasive follicular carcinomas and 4 widely invasive follicular carcinomas), followed by immunohistochemical staining of 149 cases. The specificity of the antibody was validated by western blot analysis Results In gene expression analysis QPRT was detected as differently expressed between follicular thyroid adenoma and follicular thyroid carcinoma. QPRT protein could be detected by immunohistochemistry in 65% of follicular thyroid carcinomas including minimal invasive variant and only 22% of follicular adenomas. Conclusion Consequently, QPRT is a potential new marker for the immunohistochemical screening of follicular thyroid nodules.
The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allows imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. Tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.
Highlights
• Brain connectivity states identified by cofluctuation strength.
• CMEP as new method to robustly predict human traits from brain imaging data.
• Network-identifying connectivity ‘events’ are not predictive of cognitive ability.
• Sixteen temporally independent fMRI time frames allow for significant prediction.
• Neuroimaging-based assessment of cognitive ability requires sufficient scan lengths.
Abstract
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10 min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
LICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing.
We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.
Plants, fungi and algae are important components of global biodiversity and are fundamental to all ecosystems. They are the basis for human well-being, providing food, materials and medicines. Specimens of all three groups of organisms are accommodated in herbaria, where they are commonly referred to as botanical specimens.The large number of specimens in herbaria provides an ample, permanent and continuously improving knowledge base on these organisms and an indispensable source for the analysis of the distribution of species in space and time critical for current and future research relating to global biodiversity. In order to make full use of this resource, a research infrastructure has to be built that grants comprehensive and free access to the information in herbaria and botanical collections in general. This can be achieved through digitization of the botanical objects and associated data.The botanical research community can count on a long-standing tradition of collaboration among institutions and individuals. It agreed on data standards and standard services even before the advent of computerization and information networking, an example being the Index Herbariorum as a global registry of herbaria helping towards the unique identification of specimens cited in the literature.In the spirit of this collaborative history, 51 representatives from 30 institutions advocate to start the digitization of botanical collections with the overall wall-to-wall digitization of the flat objects stored in German herbaria. Germany has 70 herbaria holding almost 23 million specimens according to a national survey carried out in 2019. 87% of these specimens are not yet digitized. Experiences from other countries like France, the Netherlands, Finland, the US and Australia show that herbaria can be comprehensively and cost-efficiently digitized in a relatively short time due to established workflows and protocols for the high-throughput digitization of flat objects.Most of the herbaria are part of a university (34), fewer belong to municipal museums (10) or state museums (8), six herbaria belong to institutions also supported by federal funds such as Leibniz institutes, and four belong to non-governmental organizations. A common data infrastructure must therefore integrate different kinds of institutions.Making full use of the data gained by digitization requires the set-up of a digital infrastructure for storage, archiving, content indexing and networking as well as standardized access for the scientific use of digital objects. A standards-based portfolio of technical components has already been developed and successfully tested by the Biodiversity Informatics Community over the last two decades, comprising among others access protocols, collection databases, portals, tools for semantic enrichment and annotation, international networking, storage and archiving in accordance with international standards. This was achieved through the funding by national and international programs and initiatives, which also paved the road for the German contribution to the Global Biodiversity Information Facility (GBIF).Herbaria constitute a large part of the German botanical collections that also comprise living collections in botanical gardens and seed banks, DNA- and tissue samples, specimens preserved in fluids or on microscope slides and more. Once the herbaria are digitized, these resources can be integrated, adding to the value of the overall research infrastructure. The community has agreed on tasks that are shared between the herbaria, as the German GBIF model already successfully demonstrates.We have compiled nine scientific use cases of immediate societal relevance for an integrated infrastructure of botanical collections. They address accelerated biodiversity discovery and research, biomonitoring and conservation planning, biodiversity modelling, the generation of trait information, automated image recognition by artificial intelligence, automated pathogen detection, contextualization by interlinking objects, enabling provenance research, as well as education, outreach and citizen science.We propose to start this initiative now in order to valorize German botanical collections as a vital part of a worldwide biodiversity data pool.
Chordomas are rare bone tumors with few therapeutic options. Here we show, using whole-exome and genome sequencing within a precision oncology program, that advanced chordomas (n = 11) may be characterized by genomic patterns indicative of defective homologous recombination (HR) DNA repair and alterations affecting HR-related genes, including, for example, deletions and pathogenic germline variants of BRCA2, NBN, and CHEK2. A mutational signature associated with HR deficiency was significantly enriched in 72.7% of samples and co-occurred with genomic instability. The poly(ADP-ribose) polymerase (PARP) inhibitor olaparib, which is preferentially toxic to HR-incompetent cells, led to prolonged clinical benefit in a patient with refractory chordoma, and whole-genome analysis at progression revealed a PARP1 p.T910A mutation predicted to disrupt the autoinhibitory PARP1 helical domain. These findings uncover a therapeutic opportunity in chordoma that warrants further exploration, and provide insight into the mechanisms underlying PARP inhibitor resistance.
Background: Previous studies reported decreased volumes of acute stroke admissions during the COVID-19 pandemic. We aimed to examine whether aneurysmal subarachnoid hemorrhage (aSAH) volumes demonstrated similar declines in our department. Furthermore, the impact of the pandemic on disease progression should be analyzed.
Methods: We conducted a retrospective study in the neurosurgical department of the university hospital Frankfurt including patients with the diagnosis of aSAH during the first year of the COVID pandemic. One year cumulative volume for aSAH hospitalization procedures was compared to the year before (03/2020 – 02/2021 vs. 03/2019 – 02/2020) and the last 5 pre-COVID-pandemic years (2015-2020). All relevant patient characteristics concerning family history, disease history, clinical condition at admission, active/past COVID-infection, treatment management, complications, and outcome were analyzed.
Results: Compared to the 84 hospital admissions during the pre-pandemic years, the number of aSAH hospitalizations (n = 56) declined during the pandemic without reaching significance. No significant difference in the analyzed patient characteristics including clinical condition at onset, treatment, complications, and outcome, between 56 patients with aSAH admitted during the COVID pandemic and the treated patients in the last 5 years in the pre-COVID period were found. In our multivariable analysis, we detected young age (p < 0.05; OR 4.2) and no existence of early hydrocephalus (p < 0.05; OR 0.13) as important factors for a favorable outcome (mRS ≤ 0–2) after aSAH during the COVID pandemic. A past COVID-infection was detected in young patients suffering from aSAH (Age < 50years, p < 0.05; OR 10.5) with an increased rate of cerebral vasospasm after aSAH onset (p < 0.05; OR 26). Nevertheless, past COVID-infection did not reach significance as a high-risk factor for unfavorable outcomes.
Conclusion: There was a relative decrease in the number of patients with aSAH during the COVID-19 pandemic. Despite the extremely different conditions of hospitalization, there was no impairing significant effect on the treatment and outcome of admitted patients with aSAH. A past COVID infection seemed to be an irrelevant limiting factor concerning favorable outcomes.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Background and Objectives: Red blood cell (RBC) transfusions are needed by almost every acute myeloid leukaemia (AML) patient undergoing induction chemotherapy and constitute a cornerstone in supportive measures for cancer patients in general. Randomized controlled trials have shown non‐inferiority or even superiority of restrictive transfusion guidelines over liberal transfusion guidelines in specific clinical situations outside of medical oncology. In this study, we analysed whether more restrictive RBC transfusion reduces blood use without affecting hard outcomes.
Materials and Methods: A total of 352 AML patients diagnosed between 2007 and 2018 and undergoing intensive induction chemotherapy were included in this retrospective analysis. In the less restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 8 g/dl (2007–2014). In the restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 7 g/dl (2016–2018). Liberal transfusion triggers were never endorsed.
Results: A total of 268 (76·1%) and 84 (23·9%) AML patients fell into the less restrictive and restrictive transfusion groups, respectively. The less restrictive transfusion group had 1 g/dl higher mean haemoglobin levels, received their first RBC transfusions earlier and needed 1·5 more units of RBC during the hospital stay of induction chemotherapy. Febrile episodes, C‐reactive protein levels, admission to the intensive care unit, length of hospital stay as well as response and survival rates did not differ between the two cohorts.
Conclusion: From our retrospective analysis, we conclude that a more restrictive transfusion trigger does not affect important outcomes of AML patients. The opportunity to test possible effects of the more severe anaemia in the restrictive transfusion group on quality of life was missed.
Children’s and adolescents’ lives drastically changed during COVID lockdowns worldwide. To compare accident- and injury-related admissions to pediatric intensive care units (PICU) during the first German COVID lockdown with previous years, we conducted a retrospective multicenter study among 37 PICUs (21.5% of German PICU capacities). A total of 1444 admissions after accidents or injuries during the first lockdown period and matched periods of 2017–2019 were reported and standardized morbidity ratios (SMR) were calculated. Total PICU admissions due to accidents/injuries declined from an average of 366 to 346 (SMR 0.95 (CI 0.85–1.05)). Admissions with trauma increased from 196 to 212 (1.07 (0.93–1.23). Traffic accidents and school/kindergarten accidents decreased (0.77 (0.57–1.02 and 0.26 (0.05–0.75)), whereas household and leisure accidents increased (1.33 (1.06–1.66) and 1.34 (1.06–1.67)). Less neurosurgeries and more visceral surgeries were performed (0.69 (0.38–1.16) and 2.09 (1.19–3.39)). Non-accidental non-suicidal injuries declined (0.73 (0.42–1.17)). Suicide attempts increased in adolescent boys (1.38 (0.51–3.02)), but decreased in adolescent girls (0.56 (0.32–0.79)). In summary, changed trauma mechanisms entailed different surgeries compared to previous years. We found no evidence for an increase in child abuse cases requiring intensive care. The increase in suicide attempts among boys demands investigation.
Kinesins play an important role in many physiological functions including intracellular vesicle transport and mitosis. The emerging role of kinesins in different cancers led us to investigate the expression and functional role of kinesins in meningioma. Therefore, we re-analyzed our previous microarray dataset of benign, atypical, and anaplastic meningiomas (n = 62) and got evidence for differential expression of five kinesins (KIFC1, KIF4A, KIF11, KIF14 and KIF20A). Further validation in an extended study sample (n = 208) revealed a significant upregulation of these genes in WHO°I to °III meningiomas (WHO°I n = 61, WHO°II n = 88, and WHO°III n = 59), which was most pronounced in clinically more aggressive tumors of the same WHO grade. Immunohistochemical staining confirmed a WHO grade-associated upregulated protein expression in meningioma tissues. Furthermore, high mRNA expression levels of KIFC1, KIF11, KIF14 and KIF20A were associated with shorter progression-free survival. On a functional level, knockdown of kinesins in Ben-Men-1 cells and in the newly established anaplastic meningioma cell line NCH93 resulted in a significantly inhibited tumor cell proliferation upon siRNA-mediated downregulation of KIF11 in both cell lines by up to 95% and 71%, respectively. Taken together, in this study we were able to identify the prognostic and functional role of several kinesin family members of which KIF11 exhibits the most promising properties as a novel prognostic marker and therapeutic target, which may offer new treatment options for aggressive meningiomas.
Environmental change impacts on the C- and N-cycle of European forests: a model comparison study
(2013)
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon source was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Purpose: COVID-19 pandemic had multiple influences on the social, industrial, and medical situation in all affected countries. Measures of obligatory medical confinement were suspensions of scheduled non-emergent surgical procedures and outpatients’ clinics as well as overall access restrictions to hospitals and medical practices. The aim of this retrospective study was to assess if the obligatory confinement (lockdown) had an effect on the number of appendectomies (during and after the period of lockdown).
Methods: This retrospective study was based on anonymized nationwide administrative claims data of the German Local General Sickness Fund (AOK). Patients admitted for diseases of the appendix (ICD-10: K35-K38) or abdominal and pelvic pain (ICD-10: R10) who underwent an appendectomy (OPS: 5-470) were included. The study period included 6 weeks of German lockdown (16 March–26 April 2020) as well as 6 weeks before (03 February–15 March 2020) and after (27 April–07 June 2020). These periods were compared to the respective one in 2018 and 2019.
Results: The overall number of appendectomies was significantly reduced during the lockdown time in 2020 compared to that in 2018 and 2019. This decrease affects only appendectomies due to acute simple (ICD-10: K35.30, K35.8) and non-acute appendicitis (ICD-10: K36-K38, R10). Numbers for appendectomies in acute complex appendicitis remained unchanged. Female patients and in the age group 1–18 years showed the strongest decrease in number of cases.
Conclusion: The lockdown in Germany resulted in a decreased number of appendectomies. This affected mainly appendectomies in simple acute and non-acute appendicitis, but not complicated acute appendicitis. The study gives no evidence that the confinement measures resulted in a deterioration of medical care for appendicitis.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.
Background: To evaluate clinical outcomes after either immediate or deferred initiation of antiretroviral therapy in HIV-1-infected patients, presenting late with pneumocystis pneumonia (PCP) or toxoplasma encephalitis (TE).
Methods: Phase IV, multicenter, prospective, randomized open-label clinical trial. Patients were randomized into an immediate therapy arm (starting antiretroviral therapy (ART) within 7 days after initiation of OI treatment) versus a deferred arm (starting ART after completing the OI-therapy). All patients were followed for 24 weeks. The rates of clinical progression (death, new or relapsing opportunistic infections (OI) and other grade 4 clinical endpoints) were compared, using a combined primary endpoint. Secondary endpoints were hospitalization rates after completion of OI treatment, incidence of immune reconstitution inflammatory syndrome (IRIS), virologic and immunological outcome, adherence to proteinase-inhibitor based antiretroviral therapy (ART) protocol and quality of life.
Results: 61 patients (11 patients suffering TE, 50 with PCP) were enrolled. No differences between the two therapy groups in all examined primary and secondary endpoints could be identified: immunological and virologic outcome was similar in both groups, there was no significant difference in the incidence of IRIS (11 and 10 cases), furthermore 9 events (combined endpoint of death, new/relapsing OI and grade 4 events) occurred in each group.
Conclusions: In summary, this study supports the notion that immediate initiation of ART with a ritonavir-boosted proteinase-inhibitor and two nucleoside reverse transcriptase inhibitors is safe and has no negative effects on incidence of disease progression or IRIS, nor on immunological and virologic outcomes or on quality of life.