Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.

Vitamin A deficiency (VAD) poses significant health risks and is prevalent in children and adolescents in India. This study aimed to determine the effect of seasonal variation and availability of vitamin A-rich (VA-rich) foods on serum retinol in adolescents. Data on serum retinol levels from adolescents (n 2297, mean age 14 years) from the Comprehensive National Nutrition Survey (2016–2018) in India were analysed, with VAD defined as serum retinol < 0·7 µmol/L. Five states were selected based on a comparable under-five mortality rate and the seasonal spread of the data collection period. Dietary data from adolescents and children ≤ 4 years old were used to assess VA-rich food consumption. A linear mixed model framework was employed to analyse the relationship between serum retinol, month of the year and VA-rich food consumption, with a priori ranking to control for multiple hypothesis testing. Consumption of VA-rich foods, particularly fruits and vegetables/roots and tubers, showed seasonal patterns, with higher consumption during summer and monsoon months. Significant associations were found between serum retinol concentrations and age, month of sampling, consumption of VA-rich foods and fish. VAD prevalence was lowest in August, coinciding with higher consumption of VA-rich fruits and foods. Findings highlight the importance of considering seasonality in assessing VAD prevalence and careful interpretation of survey findings. Intentional design, analysis and reporting of surveys to capture seasonal variation is crucial for accurate assessment and interpretation of VAD prevalence, including during monitoring and evaluation of programmes, and to ensure that public health strategies are appropriately informed.

The First Large Absorption Survey in H i (FLASH) is a large-area radio survey for neutral hydrogen in and around galaxies in the intermediate redshift range $0.4\lt z\lt1.0$, using the 21-cm H i absorption line as a probe of cold neutral gas. The survey uses the ASKAP radio telescope and will cover 24,000 deg$^2$ of sky over the next five years. FLASH breaks new ground in two ways – it is the first large H i absorption survey to be carried out without any optical preselection of targets, and we use an automated Bayesian line-finding tool to search through large datasets and assign a statistical significance to potential line detections. Two Pilot Surveys, covering around 3000 deg$^2$ of sky, were carried out in 2019-22 to test and verify the strategy for the full FLASH survey. The processed data products from these Pilot Surveys (spectral-line cubes, continuum images, and catalogues) are public and available online. In this paper, we describe the FLASH spectral-line and continuum data products and discuss the quality of the H i spectra and the completeness of our automated line search. Finally, we present a set of 30 new H i absorption lines that were robustly detected in the Pilot Surveys, almost doubling the number of known H i absorption systems at $0.4\lt z\lt1$. The detected lines span a wide range in H i optical depth, including three lines with a peak optical depth $\tau\gt1$, and appear to be a mixture of intervening and associated systems. Interestingly, around two-thirds of the lines found in this untargeted sample are detected against sources with a peaked-spectrum radio continuum, which are only a minor (5–20%) fraction of the overall radio-source population. The detection rate for H i absorption lines in the Pilot Surveys (0.3 to 0.5 lines per 40 deg$^2$ ASKAP field) is a factor of two below the expected value. One possible reason for this is the presence of a range of spectral-line artefacts in the Pilot Survey data that have now been mitigated and are not expected to recur in the full FLASH survey. A future paper in this series will discuss the host galaxies of the H i absorption systems identified here.

Aerosol-cloud interactions contribute significant uncertainty to modern climate model predictions. Analysis of complex observed aerosol-cloud parameter relationships is a crucial piece of reducing this uncertainty. Here, we apply two machine learning methods to explore variability in in-situ observations from the NASA ACTIVATE mission. These observations consist of flights over the Western North Atlantic Ocean, providing a large repository of data including aerosol, meteorological, and microphysical conditions in and out of clouds. We investigate this dataset using principal component analysis (PCA), a linear dimensionality reduction technique, and an autoencoder, a deep learning non-linear dimensionality reduction technique. We find that we can reduce the dimensionality of the parameter space by more than a factor of 2 and verify that the deep learning method outperforms a PCA baseline by two orders of magnitude. Analysis in the low dimensional space of both these techniques reveals two consistent physically interpretable regimes—a low pollution regime and an in-cloud regime. Through this work, we show that unsupervised machine learning techniques can learn useful information from in-situ atmospheric observations and provide interpretable results of low-dimensional variability.

Inflammation and infections such as malaria affect concentrations of many micronutrient biomarkers and hence estimates of nutritional status. We aimed to assess the relationship between malaria infection and micronutrient biomarker concentrations in pre-school children (PSC), school-age children (SAC) and women of reproductive age (WRA) in Malawi and examine the potential role of malarial immunity on the relationship between malaria and micronutrient biomarkers. Data from the 2015/2016 Malawi micronutrient survey were used. The associations between current or recent malaria infection, detected by rapid diagnostic test and concentration of serum ferritin, soluble transferrin receptor (sTfR), zinc, serum folate, red blood cell folate and vitamin B12 were estimated using multivariable linear regression. Factors related to malarial immunity including age, altitude and presence of hemoglobinopathies were examined as effect modifiers. Serum ferritin, sTfR and zinc were adjusted for inflammation using the BRINDA method. Malaria infection was associated with 68 % (95 % CI 51, 86), 28 % (18, 40) and 34 % (13, 45) greater inflammation-adjusted ferritin in PSC, SAC and WRA, respectively (P < 0·001 for each). In PSC, the positive association was stronger in younger children, high altitude and children who were not carriers of the sickle cell trait. In PSC and SAC, sTfR was elevated (+ 25 % (16, 29) and + 15 % (9, 22) respectively, P < 0·001). Serum folate and erythrocyte folate were elevated in WRA with malaria (+ 18 % (3, 35) and + 11 % (1, 23), P = 0·01 and P = 0·003 respectively). Malaria affects the interpretation of micronutrient biomarker concentrations, and examining factors related to malarial immunity may be informative.

Quantum field theory predicts a nonlinear response of the vacuum to strong electromagnetic fields of macroscopic extent. This fundamental tenet has remained experimentally challenging and is yet to be tested in the laboratory. A particularly distinct signature of the resulting optical activity of the quantum vacuum is vacuum birefringence. This offers an excellent opportunity for a precision test of nonlinear quantum electrodynamics in an uncharted parameter regime. Recently, the operation of the high-intensity Relativistic Laser at the X-ray Free Electron Laser provided by the Helmholtz International Beamline for Extreme Fields has been inaugurated at the High Energy Density scientific instrument of the European X-ray Free Electron Laser. We make the case that this worldwide unique combination of an X-ray free-electron laser and an ultra-intense near-infrared laser together with recent advances in high-precision X-ray polarimetry, refinements of prospective discovery scenarios and progress in their accurate theoretical modelling have set the stage for performing an actual discovery experiment of quantum vacuum nonlinearity.

The Automated Meteorology—Ice—Geophysics Observation System 3 (AMIGOS-3) is a multi-sensor on-ice ocean mooring and weather, camera and precision GPS measurement station, controlled by a Python script. The station is designed to be deployed on floating ice in the polar regions and operate unattended for up to several years. Ocean mooring sensors (SeaBird MicroCAT and Nortek Aquadopp) record conductivity, temperature and depth (reported at 10 min intervals), and current velocity (hourly intervals). A Silixa XT fiber-optic distributed temperature sensing system provides a temperature profile time-series through the ice and ocean column with a cadence of 6 d−1 to 1 week−1 depending on available station power. A subset of the station data is telemetered by Iridium modem. Two-way communication, using both single-burst data and file transfer protocols, facilitates station data collection changes and power management. Power is supplied by solar panels and a sealed lead-acid battery system. Two AMIGOS-3 systems were installed on the Thwaites Eastern Ice Shelf in January 2020, providing data well into 2022. We discuss the components of the system and present several of the data sets, summarizing observed climate, ice and ocean conditions.

Inflammation and infections such as malaria affect micronutrient biomarker concentrations and hence estimates of nutritional status. It is unknown whether correction for C-reactive protein (CRP) and α1-acid glycoprotein (AGP) fully captures the modification in ferritin concentrations during a malaria infection, or whether environmental and sociodemographic factors modify this association. Cross-sectional data from eight surveys in children aged 6–59 months (Cameroon, Cote d’Ivoire, Kenya, Liberia, Malawi, Nigeria and Zambia; n 6653) from the Biomarkers Reflecting Inflammation and Nutritional Determinants of Anaemia (BRINDA) project were pooled. Ferritin was adjusted using the BRINDA adjustment method, with values < 12 μg/l indicating iron deficiency. The association between current or recent malaria infection, detected by microscopy or rapid test kit, and inflammation-adjusted ferritin was estimated using pooled multivariable linear regression. Age, sex, malaria endemicity profile (defined by the Plasmodium falciparum infection prevalence) and malaria diagnostic methods were examined as effect modifiers. Unweighted pooled malaria prevalence was 26·0 % (95 % CI 25·0, 27·1) and unweighted pooled iron deficiency was 41·9 % (95 % CI 40·7, 43·1). Current or recent malaria infection was associated with a 44 % (95 % CI 39·0, 52·0; P < 0·001) increase in inflammation-adjusted ferritin after adjusting for age and study identifier. In children, ferritin increased less with malaria infection as age and malaria endemicity increased. Adjustment for malaria increased the prevalence of iron deficiency, but the effect was small. Additional information would help elucidate the underlying mechanisms of the role of endemicity and age in the association between malaria and ferritin.

Background: After a transient ischemic attack (TIA) or minor stroke, the long-term risk of subsequent stroke is uncertain. Methods: Electronic databases were searched for observational studies reporting subsequent stroke during a minimum follow-up of 1 year in patients with TIA or minor stroke. Unpublished data on number of stroke events and exact person-time at risk contributed by all patients during discrete time intervals of follow-up were requested from the authors of included studies. This information was used to calculate the incidence of stroke in individual studies, and results across studies were pooled using random-effects meta-analysis. Results: Fifteen independent cohorts involving 129794 patients were included in the analysis. The pooled incidence rate of subsequent stroke per 100 person-years was 6.4 events in the first year and 2.0 events in the second through tenth years, with cumulative incidences of 14% at 5 years and 21% at 10 years. Based on 10 studies with information available on fatal stroke, the pooled case fatality rate of subsequent stroke was 9.5% (95% CI, 5.9 – 13.8). Conclusions: One in five patients is expected to experience a subsequent stroke within 10 years after a TIA or minor stroke, with every tenth patient expected to die from their subsequent stroke.

Recent research has shown the potential of speleothem δ13C to record a range of environmental processes. Here, we report on 230Th-dated stalagmite δ13C records for southwest Sulawesi, Indonesia, over the last 40,000 yr to investigate the relationship between tropical vegetation productivity and atmospheric methane concentrations. We demonstrate that the Sulawesi stalagmite δ13C record is driven by changes in vegetation productivity and soil respiration and explore the link between soil respiration and tropical methane emissions using HadCM3 and the Sheffield Dynamic Global Vegetation Model. The model indicates that changes in soil respiration are primarily driven by changes in temperature and CO2, in line with our interpretation of stalagmite δ13C. In turn, modelled methane emissions are driven by soil respiration, providing a mechanism that links methane to stalagmite δ13C. This relationship is particularly strong during the last glaciation, indicating a key role for the tropics in controlling atmospheric methane when emissions from high-latitude boreal wetlands were suppressed. With further investigation, the link between δ13C in stalagmites and tropical methane could provide a low-latitude proxy complementary to polar ice core records to improve our understanding of the glacial–interglacial methane budget.

Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients,1 leading to substantial morbidity, mortality, and excess healthcare expenditures,1 and persistent gaps remain between what is recommended and what is practiced.

The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes2 in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.3

The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.

New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or “hybrid” trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.

One challenge for multisite clinical trials is ensuring that the conditions of an informative trial are incorporated into all aspects of trial planning and execution. The multicenter model can provide the potential for a more informative environment, but it can also place a trial at risk of becoming uninformative due to lack of rigor, quality control, or effective recruitment, resulting in premature discontinuation and/or non-publication. Key factors that support informativeness are having the right team and resources during study planning and implementation and adequate funding to support performance activities. This communication draws on the experience of the National Center for Advancing Translational Science (NCATS) Trial Innovation Network (TIN) to develop approaches for enhancing the informativeness of clinical trials. We distilled this information into three principles: (1) assemble a diverse team, (2) leverage existing processes and systems, and (3) carefully consider budgets and contracts. The TIN, comprised of NCATS, three Trial Innovation Centers, a Recruitment Innovation Center, and 60+ CTSA Program hubs, provides resources to investigators who are proposing multicenter collaborations. In addition to sharing principles that support the informativeness of clinical trials, we highlight TIN-developed resources relevant for multicenter trial initiation and conduct.

The radio signal transmitted by the Mars Express (MEX) spacecraft was observed regularly between the years 2013–2020 at X-band (8.42 GHz) using the European Very Long Baseline Interferometry (EVN) network and University of Tasmania’s telescopes. We present a method to describe the solar wind parameters by quantifying the effects of plasma on our radio signal. In doing so, we identify all the uncompensated effects on the radio signal and see which coronal processes drive them. From a technical standpoint, quantifying the effect of the plasma on the radio signal helps phase referencing for precision spacecraft tracking. The phase fluctuation of the signal was determined for Mars’ orbit for solar elongation angles from 0 to 180 deg. The calculated phase residuals allow determination of the phase power spectrum. The total electron content of the solar plasma along the line of sight is calculated by removing effects from mechanical and ionospheric noises. The spectral index was determined as $-2.43 \pm 0.11$ which is in agreement with Kolmogorov’s turbulence. The theoretical models are consistent with observations at lower solar elongations however at higher solar elongation ($>$160 deg) we see the observed values to be higher. This can be caused when the uplink and downlink signals are positively correlated as a result of passing through identical plasma sheets.

We present a timeseries of 14CO2 for the period 1910–2021 recorded by annual plants collected in the southwestern United States, centered near Flagstaff, Arizona. This timeseries is dominated by five commonly occurring annual plant species in the region, which is considered broadly representative of the southern Colorado Plateau. Most samples (1910–2015) were previously archived herbarium specimens, with additional samples harvested from field experiments in 2015–2021. We used this novel timeseries to develop a smoothed local record with uncertainties for “bomb spike” 14C dating of recent terrestrial organic matter. Our results highlight the potential importance of local records, as we document a delayed arrival of the 1963–1964 bomb spike peak, lower values in the 1980s, and elevated values in the last decade in comparison to the most current Northern Hemisphere Zone 2 record. It is impossible to retroactively collect atmospheric samples, but archived annual plants serve as faithful scribes: samples from herbaria around the Earth may be an under-utilized resource to improve understanding of the modern carbon cycle.