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Today's uncertain HIV funding landscape threatens to slow progress towards treatment goals. Understanding the costs of antiretroviral therapy (ART) will be essential for governments to make informed policy decisions about the pace of scale-up under the 2013 WHO HIV Treatment Guidelines, which increase the number of people eligible for treatment from 17.6 million to 28.6 million. The study presented here is one of the largest of its kind and the first to describe the facility-level cost of ART in a random sample of facilities in Ethiopia, Malawi, Rwanda, South Africa and Zambia. In 2010-2011, comprehensive data on one year of facility-level ART costs and patient outcomes were collected from 161 facilities, selected using stratified random sampling. Overall, facility-level ART costs were significantly lower than expected in four of the five countries, with a simple average of $208 per patient-year (ppy) across Ethiopia, Malawi, Rwanda and Zambia. Costs were higher in South Africa, at $682 ppy. This included medications, laboratory services, direct and indirect personnel, patient support, equipment and administrative services. Facilities demonstrated the ability to retain patients alive and on treatment at these costs, although outcomes for established patients (2-8% annual loss to follow-up or death) were better than outcomes for new patients in their first year of ART (77-95% alive and on treatment). This study illustrated that the facility-level costs of ART are lower than previously understood in these five countries. While limitations must be considered, and costs will vary across countries, this suggests that expanded treatment coverage may be affordable. Further research is needed to understand investment costs of treatment scale-up, non-facility costs and opportunities for more efficient resource allocation.

Predicting progression and prognosis in Interstitial Lung Diseases (ILD), especially Idiopathic Pulmonary Fibrosis (IPF) and Progressive Pulmonary Fibrosis (PPF), remains a challenge. Integrating patient-centered measurements is essential for earlier and safer detection of disease progression. Home monitoring through e-health technologies, such as spirometry and oximetry connected to smartphone applications, holds promise for early detection of ILD progression or acute exacerbations, enabling timely therapeutic interventions. The European ILD Registry Algorithm for Self-Assessment in ILD (eurILDreg ASA-ILD), developed by all eurILDreg principal investigators, includes questionnaires on symptom burden, respiratory infections, and quality of life (EQ5D VAS, K-BILD, LCQ). The algorithm also incorporates spirometry and oxygen saturation measurements, both at rest and during exercise (one-minute sit-to-stand test, 1STST). This ASA-ILD algorithm is integrated into the patientMpower Ltd. smartphone application, used for patient-led monitoring, research, and clinical care since 2016, and available on both Apple and Android platforms. For patient-centered measurements, participants in the multicenter eurILDreg study will receive a patientMpower account, a handheld clinical-grade spirometer (Spirobank Smart, MIR, Italy), and a pulse oximeter (Nonin Medical, Inc. Plymouth, MN, USA), along with usage instructions. Artificial intelligence software (ArtiQ) will analyze spirometry maneuvers in real-time, ensuring compliance with recent ERS/ATS criteria and providing automated feedback. Pulse oximetry is integrated into the exercise testing within the application, following an automated in-app protocol developed with clinician involvement for safety and accuracy. The application will send reminders to participants to complete patient-reported outcome measures (PROMs) according to the study protocol. This study is designed to explore the potential of e-Health technologies, such as home monitoring via spirometry and oximetry, integrated with the eurILDreg ASA-ILD algorithm and patientMpower app, to improve early detection and management of ILD. A pilot trial showed promising adherence to spirometry, indicating that digital health interventions could enhance patient care and outcomes in ILD. The ethics committee of the Justus-Liebig-University of Giessen has approved the eurILDreg and this substudy with the protocol reference number 111/08. The research was conducted strictly according to the principles of the Declaration of Helsinki. Patients were included into the registry upon having signed the informed consent. The eurIPFreg and eurIPFbank are listed in ClinicalTrials.gov (NCT02951416). EurILDreg is registered in German Clinical Trials Register, DRKS 00028968.

Background and Aims Interstitial lung diseases (ILDs), encompassing both pediatric and adult cases, present a diverse spectrum of chronic conditions with variable prognosis. Despite limited therapeutic options beyond antifibrotic drugs and immunosuppressants, accurate diagnosis is challenging, often necessitating invasive procedures that may not be feasible for certain patients. Drawn against this background, experts across pediatric and adult ILD fields have joined forces in the RARE-ILD initiative to pioneer novel non-invasive diagnostic algorithms and biomarkers. Collaborating with the RARE-ILD consortium, the eurILDreg aims to comprehensively describe different ILDs, analyze genetically defined forms across age groups, create innovative diagnostic and therapeutic biomarkers, and employ artificial intelligence for data analysis. Methods The foundation of eurILDreg is built on a comprehensive parameter list developed and adopted by clinical experts, encompassing over 1,800 distinct parameters related to patient history, clinical examinations, diagnosis, lung function and biospecimen collection. This robust dataset is further enriched with daily assessments captured through the patientMpower app, including handheld spirometry and exercise tests, conducted on approximately 350 patients over the course of a year. This approach involves app-based daily assessments of quality of life, symptom tracking, handheld spirometry, saturation measurement, and the 1-min sit-to-stand test (1-STST). Additionally, pediatric data from the ChILD-EU registry will be integrated into the RARE-ILD Data Warehouse, with the ultimate goal of including a total of 4.000 ILD patients and over 100.000 biospecimen. Discussion The collaborative efforts within the consortium are poised to streamline research endeavors significantly, promising to advance patient-centered care, foster innovation, and shape the future landscape of interstitial lung disease research and healthcare practices. Trial Registration EurILDreg is registered in the German Clinical Trials Register (DRKS 00028968, 26.07.2022), and eurIPFreg is registered in ClinicalTrials.gov (NCT02951416).

The HIV Infant Tracking System (HITSystem) is an eHealth intervention to improve early infant diagnosis (EID) through alerts to providers and text messages to mothers. This study explored mothers’ experiences receiving standard and HITSystem-enhanced EID services to assess perceived intervention benefits, acceptability, and opportunities for improvement. This qualitative study was embedded within a cluster-randomized control trial to evaluate the HITSystem at six Kenyan government hospitals (3 intervention, 3 control). We conducted semi-structured interviews with 137 mothers attending EID follow-up visits. Compared to control sites, participants at HITSystem sites described enhanced EID quality; HITSystem-generated texts informed them of result availability and retesting needs, provided cues-to-action for clinic attendance, and engendered opportunities for patient support. They described improved EID efficiency through shorter waiting periods for results and fewer hospital visits. Participants reported high satisfaction with EID and acceptability of text messages; however, modifications to ensure text delivery, increase repeat testing reminders, include low literacy content options, and provide encouraging messages were suggested. These user experience data suggest improvements in EID at HITSystem sites when compared with control sites.

Background. Metabolic effects following combination antiretroviral therapy (cART) vary by regimen type. Changes in metabolic effects were assessed following cART in the AIDS Clinical Trials Group (ACTG) A5257 study, and correlated with plasma ritonavir trough concentrations (C24). Methods. Treatment-naive adult subjects were randomized to ritonavir-boosted atazanavir or darunavir, or raltegravir-based cART. Changes in lipids and other metabolic outcomes over time were estimated. Differences between arms were estimated with 97.5% confidence intervals and compared using pairwise Student t tests. Associations between ritonavir C24 and lipid changes at week 48 were evaluated via linear regression. Results. Analyses included 1797 subjects with baseline fasting data. Baseline lipid profiles and metabolic syndrome rates (approximately 21%) were similar across arms. Comparable increases occurred in total cholesterol, triglycerides, and low-density lipoprotein cholesterol with the boosted protease inhibitors (PIs); each PI had greater increases relative to raltegravir (all P ≤ .001 at week 96). Metabolic syndrome incident rates by week 96 (approximately 22%) were not different across arms. Ritonavir C24 was not different by arm (P = .89) (median, 69 ng/mL and 74 ng/mL in the atazanavir and darunavir arms, respectively) and were not associated with changes in lipid measures (all P > .1). Conclusions. Raltegravir produced the most favorable lipid profile. Metabolic syndrome rates were high at baseline and increased to the same degree in all arms. Ritonavir C24 was not different in the PI arms and had no relationship with the modest but comparable increased in lipids observed with either atazanavir or darunavir. The long-term clinical significance of the lipid changes noted with the PIs relative to raltegravir deserves further evaluation. Clinical Trials Registration. NCT 00811954.

Literature suggests that electronic health (eHealth) interventions can improve the efficiency and accuracy of health service delivery and improve health outcomes and are generally well received by patients; however, there are limited data on provider experiences using eHealth interventions in resource-limited settings. The HIV Infant Tracking System (HITSystem) is an eHealth intervention designed to improve early infant diagnosis (EID) outcomes among HIV-exposed infants. We aimed to compare provider experiences with standard EID and HITSystem implementation at 6 Kenyan hospitals and 3 laboratories. The objective of this study was to better understand provider experiences implementing and using the HITSystem in order to assess facilitators and barriers that may impact adoption and sustainability of this eHealth intervention. As part of a randomized controlled trial to evaluate the HITSystem, we conducted semistructured interviews with 17 EID providers at participating intervention and control hospitals and laboratories. Providers emphasized the perceived usefulness of the HITSystem, including improved efficiency in sample tracking and patient follow-up, strengthened communication networks among key stakeholders, and improved capacity to meet patient needs compared to standard EID. These advantages were realized from an intervention that providers saw as easy to use and largely compatible with workflow. However, supply stock outs and patient psychosocial factors (including fear of HIV status disclosure and poverty) provided ongoing challenges to EID service provision. Furthermore, slow or sporadic internet access and heavy workload prevented real-time HITSystem data entry for some clinicians. Provider experiences with the HITSystem indicate that the usefulness of the HITSystem, along with the ease with which it is able to be incorporated into hospital workflows, contributes to its sustained adoption and use in Kenyan hospitals. To maximize implementation success, care should be taken in intervention design and implementation to ensure that end users see clear advantages to using the technology and to account for variations in workflows, patient populations, and resource levels by allowing flexibility to suit user needs. ClinicalTrials.gov NCT02072603; https://clinicaltrials.gov/ct2/show/NCT02072603 (Archived by WebCite at http://www.webcitation.org/71NgMCrAm).

Background Interstitial lung diseases (ILD) are a group of rare lung diseases with severe outcomes. The COST Innovator Grant aims to establish a first-of-a-kind open-access Biorepository of patient-derived induced pluripotent stem cells (iPSC) and to train researchers in the skills required to generate a robust preclinical model of ILD using these cells. This study aims to describe and evaluate the effectiveness of a training course designed to train researchers in iPSC techniques to model ILD. Methods 74 researchers, physicians and stakeholders attended the training course in Dublin in May 2022 with 31 trainees receiving teaching in practical iPSC culturing skills. The training course learners were divided into the Hands-on (16 trainees) and Observer groups (15 trainees), with the Observers attending a supervised live-streamed experience of the laboratories skills directly delivered to the Hands-on group. All participants were asked to participate in an evaluation to analyse their satisfaction and knowledge gained during the Training Course, with means compared using t -tests. Results The gender balance in both groups was predominantly females (77.4%). The Hands-on group consisted mainly of researchers (75%), whereas all participants of the Observer group described themselves as clinicians. All participants in the Hands-on group were at least very satisfied with the training course compared to 70% of the participants in the Observer group. The knowledge assessment showed that the Hands-on group retained significantly more knowledge of iPSC characteristics and culturing techniques compared to the Observers (* < 0.05; p  = 0.0457). A comprehensive learning video detailing iPSC culturing techniques was produced and is included with this manuscript. Conclusions The majority of participants were highly or very satisfied with the training course and retained significant knowledge about iPSC characteristics and culturing techniques after attending the training course. Overall, our findings demonstrate the feasibility of running hybrid Hands-on and Observer teaching events and underscore the importance of this type of training programme to appeal to a broad spectrum of interested clinicians and researchers particularly in rare disease. The long-term implications of this type of training event requires further study to determine its efficacy and impact on adoption of iPSC disease modelling techniques in participants’ laboratories.

The glycosylation of IgG plays a critical role during human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, activating immune cells and inducing cytokine production. However, the role of IgM N-glycosylation has not been studied during human acute viral infection. The analysis of IgM N-glycosylation from healthy controls and hospitalized coronavirus disease 2019 (COVID-19) patients reveals increased high-mannose and sialylation that correlates with COVID-19 severity. These trends are confirmed within SARS-CoV-2-specific immunoglobulin N-glycan profiles. Moreover, the degree of total IgM mannosylation and sialylation correlate significantly with markers of disease severity. We link the changes of IgM N-glycosylation with the expression of Golgi glycosyltransferases. Lastly, we observe antigen-specific IgM antibody-dependent complement deposition is elevated in severe COVID-19 patients and modulated by exoglycosidase digestion. Taken together, this work links the IgM N-glycosylation with COVID-19 severity and highlights the need to understand IgM glycosylation and downstream immune function during human disease. The role of IgG glycosylation in the immune response has been studied, but less is known about IgM glycosylation. Here the authors characterize glycosylation of SARS-CoV-2 spike specific IgM and show that it correlates with COVID-19 severity and affects complement deposition.

We apply an empirical, data-driven approach for describing crop yield as a function of monthly temperature and precipitation by employing generative probabilistic models with parameters determined through Bayesian inference. Our approach is applied to state-scale maize yield and meteorological data for the US Corn Belt from 1981 to 2014 as an exemplar, but would be readily transferable to other crops, locations and spatial scales. Experimentation with a number of models shows that maize growth rates can be characterised by a two-dimensional Gaussian function of temperature and precipitation with monthly contributions accumulated over the growing period. This approach accounts for non-linear growth responses to the individual meteorological variables, and allows for interactions between them. Our models correctly identify that temperature and precipitation have the largest impact on yield in the six months prior to the harvest, in agreement with the typical growing season for US maize (April to September). Maximal growth rates occur for monthly mean temperature 18 °C-19 °C, corresponding to a daily maximum temperature of 24 °C-25 °C (in broad agreement with previous work) and monthly total precipitation 115 mm. Our approach also provides a self-consistent way of investigating climate change impacts on current US maize varieties in the absence of adaptation measures. Keeping precipitation and growing area fixed, a temperature increase of 2 °C, relative to 1981-2014, results in the mean yield decreasing by 8%, while the yield variance increases by a factor of around 3. We thus provide a flexible, data-driven framework for exploring the impacts of natural climate variability and climate change on globally significant crops based on their observed behaviour. In concert with other approaches, this can help inform the development of adaptation strategies that will ensure food security under a changing climate.

In this work we report the discovery of the hyperluminous galaxy HELP_J100156.75+022344.7 at the photometric redshift of z ~ 4.3. The galaxy was discovered in the Cosmological Evolution Survey (COSMOS) field, one of the fields studied by the Herschel Extragalactic Legacy Project (HELP). We present the spectral energy distribution (SED) of the galaxy and fit it with the CYprus models for Galaxies and their NUclear Spectra (CYGNUS) multi-component radiative transfer models. We find that its emission is dominated by an obscured quasar with a predicted total 1-1000um luminosity of \\(3.91^{+1.69}_{-0.55} \\times 10^{13} L_\\odot\\) and an active galactic nucleus (AGN) fraction of ~89%. We also fit HELP_J100156.75+022344.7 with the Code Investigating GALaxy Emission (CIGALE) code and find a similar result. This is only the second z > 4 hyperluminous obscured quasar discovered to date. The discovery of HELP_J100156.75+022344.7 in the ~ 2deg^2 COSMOS field implies that a large number of obscured hyperluminous quasars may lie in the HELP fields which cover ~ 1300deg^2. If this is confirmed, tension between supermassive black hole evolution models and observations will be alleviated. We estimate the space density of objects like HELP_J100156.75+022344.7 at z ~ 4.5 to be \\(\\sim 1.8 \\times 10^{-8}\\)Mpc\\(^{-3}\\). This is slightly higher than the space density of coeval hyperluminous optically selected quasars suggesting that the obscuring torus in z > 4 quasars may have a covering factor \\(\\gtrsim 50\\%\\).