Proinsulin folding and trafficking defects trigger a common pathological disturbance of endoplasmic reticulum homeostasis

Primary defects in folding of mutant proinsulin can cause dominant-negative proinsulin accumulation in the endoplasmic reticulum (ER), impaired anterograde proinsulin trafficking, perturbed ER homeostasis, diminished insulin production, and β-cell dysfunction. Conversely, if primary impairment of ER-to-Golgi trafficking (which also perturbs ER homeostasis) drives misfolding of nonmutant proinsulin-this might suggest bi-directional entry into a common pathological phenotype (proinsulin misfolding, perturbed ER homeostasis, and deficient ER export of proinsulin) that can culminate in diminished insulin storage and diabetes. Here, we've challenged β-cells with conditions that impair ER-to-Golgi trafficking, and devised an accurate means to assess the relative abundance of distinct folded/misfolded forms of proinsulin using a novel nonreducing SDS-PAGE/immunoblotting protocol. We confirm abundant proinsulin misfolding upon introduction of a diabetogenic INS mutation, or in the islets of db/db mice. Whereas blockade of proinsulin trafficking in Golgi/post-Golgi compartments results in intracellular accumulation of properly-folded proinsulin (bearing native disulfide bonds), impairment of ER-to-Golgi trafficking (regardless whether such impairment is achieved by genetic or pharmacologic means) results in decreased native proinsulin with more misfolded proinsulin. Remarkably, reversible ER-to-Golgi transport defects (such as treatment with brefeldin A or cellular energy depletion) upon reversal quickly restore the ER folding environment, resulting in the disappearance of pre-existing misfolded proinsulin while preserving proinsulin bearing native disulfide bonds. Thus, proper homeostatic balance of ER-to-Golgi trafficking is linked to a more favorable proinsulin folding (as well as trafficking) outcome.

Pre-vaccination immunotypes reveal weak and robust antibody responders to influenza vaccination

Effective vaccine-induced immune responses are particularly essential in older adults who face an increased risk of immunosenescence. However, the complexity and variability of the human immune system make predicting vaccine responsiveness challenging. To address this knowledge gap, our study aimed to characterize immune profiles that are predictive of vaccine responsiveness using "immunotypes" as an innovative approach. We analyzed an extensive set of innate and adaptive immune cell subsets in the whole blood of 307 individuals (aged 25-92) pre- and post-influenza vaccination which we associated with day 28 hemagglutination inhibition (HI) antibody titers. Building on our previous work that stratified individuals into nine immunotypes based on immune cell subsets, we identified two pre-vaccination immunotypes associated with weak and one showing robust day 28 antibody response. Notably, the weak responders demonstrated HLA-DR+ T-cell signatures, while the robust responders displayed a high naïve-to-memory T-cell ratio and percentage of nonclassical monocytes. These specific signatures deepen our understanding of the relationship between the baseline of the immune system and its functional potential. This approach could enhance our ability to identify individuals at risk of immunosenescence. Our findings highlight the potential of pre-vaccination immunotypes as an innovative tool for informing personalized vaccination strategies and improving health outcomes, particularly for aging populations.

Refined innate plasma signature after rVSVΔG-ZEBOV-GP immunization is shared among adult cohorts in Europe and North America

Background

During the last decade Ebola virus has caused several outbreaks in Africa. The recombinant vesicular stomatitis virus-vectored Zaire Ebola (rVSVΔG-ZEBOV-GP) vaccine has proved safe and immunogenic but is reactogenic. We previously identified the first innate plasma signature response after vaccination in Geneva as composed of five monocyte-related biomarkers peaking at day 1 post-immunization that correlates with adverse events, biological outcomes (haematological changes and viremia) and antibody titers. In this follow-up study, we sought to identify additional biomarkers in the same Geneva cohort and validate those identified markers in a US cohort.

Methods

Additional biomarkers were identified using multiplexed protein biomarker platform O-link and confirmed by Luminex. Principal component analysis (PCA) evaluated if these markers could explain a higher variability of the vaccine response (and thereby refined the initial signature). Multivariable and linear regression models evaluated the correlations of the main components with adverse events, biological outcomes, and antibody titers. External validation of the refined signature was conducted in a second cohort of US vaccinees (n=142).

Results

Eleven additional biomarkers peaked at day 1 post-immunization: MCP2, MCP3, MCP4, CXCL10, OSM, CX3CL1, MCSF, CXCL11, TRAIL, RANKL and IL15. PCA analysis retained three principal components (PC) that accounted for 79% of the vaccine response variability. PC1 and PC2 were very robust and had different biomarkers that contributed to their variability. PC1 better discriminated different doses, better defined the risk of fever and myalgia, while PC2 better defined the risk of headache. We also found new biomarkers that correlated with reactogenicity, including transient arthritis (MCP-2, CXCL10, CXCL11, CX3CL1, MCSF, IL-15, OSM). Several innate biomarkers are associated with antibody levels one and six months after vaccination. Refined PC1 correlated strongly in both data sets (Geneva: r = 0.97, P < 0.001; US: r = 0.99, P< 0.001).

Conclusion

Eleven additional biomarkers refined the previously found 5-biomarker Geneva signature. The refined signature better discriminated between different doses, was strongly associated with the risk of adverse events and with antibody responses and was validated in a separate cohort.

Lymphodepletion - an essential but undervalued part of the chimeric antigen receptor T-cell therapy cycle

Lymphodepletion (LD) or conditioning is an essential step in the application of currently used autologous and allogeneic chimeric antigen receptor T-cell (CAR-T) therapies as it maximizes engraftment, efficacy and long-term survival of CAR-T. Its main modes of action are the depletion and modulation of endogenous lymphocytes, conditioning of the microenvironment for improved CAR-T expansion and persistence, and reduction of tumor load. However, most LD regimens provide a broad and fairly unspecific suppression of T-cells as well as other hematopoietic cells, which can also lead to severe side effects, particularly infections. We reviewed 1271 published studies (2011-2023) with regard to current LD strategies for approved anti-CD19 CAR-T products for large B cell lymphoma (LBCL). Fludarabine (Flu) and cyclophosphamide (Cy) (alone or in combination) were the most commonly used agents. A large number of different schemes and combinations have been reported. In the respective schemes, doses of Flu and Cy (range 75-120mg/m2 and 750-1.500mg/m2) and wash out times (range 2-5 days) differed substantially. Furthermore, combinations with other agents such as bendamustine (benda), busulfan or alemtuzumab (for allogeneic CAR-T) were described. This diversity creates a challenge but also an opportunity to investigate the impact of LD on cellular kinetics and clinical outcomes of CAR-T. Only 21 studies explicitly investigated in more detail the influence of LD on safety and efficacy. As Flu and Cy can potentially impact both the in vivo activity and toxicity of CAR-T, a more detailed analysis of LD outcomes will be needed before we are able to fully assess its impact on different T-cell subsets within the CAR-T product. The T2EVOLVE consortium propagates a strategic investigation of LD protocols for the development of optimized conditioning regimens.

Three year outcomes in infants with a family history of autism and/or attention deficit hyperactivity disorder

Background

Most research on early outcomes in infants with a family history (FH) of autism has focussed on categorically defined autism, although some have language and developmental delays. Less is known about outcomes in infants with a FH of attention deficit hyperactivity disorder (ADHD).

Methods

Infants with and without a FH of autism and/or ADHD, due to a first-degree relative with either or both conditions, were recruited at 5 or 10 months. Three year outcomes were characterised using latent profile analysis (LPA) across measures of cognitive ability, adaptive functioning and autism, ADHD and anxiety traits (n = 131). We additionally ran an LPA using only autism and ADHD measures, and the broader LPA in an independent cohort (n = 139) and in both cohorts combined (n = 270).

Results

A Low Developmental Level + High Behavioural Concerns class had elevated autism, ADHD and anxiety scores, low cognitive and adaptive function, and included all but one child with autism. A Low Developmental Level + Typical Behaviour class had average cognitive ability and typical behaviour but low adaptive function. A Typical Developmental Level + Some Behavioural Concerns class had average cognitive and adaptive function but slightly elevated behaviour scores. A High Developmental Level + Typical Behaviour class had above average cognitive ability and typical behaviour. All four LPAs identified classes characterised by combinations of either, or both, Low Development Level and elevated behaviour scores, as well as a typically developing class. No classes had elevated autism or ADHD traits in isolation.

Conclusions

Some infants with a FH of autism or ADHD have atypical developmental and behavioural outcomes, but do not show strong autism or ADHD traits in isolation. The field needs to recalibrate aims and methods to embrace the broader transdiagnostic pattern of outcomes seen in these infants.

Serum profiling identifies CCL8, CXCL13, and IL-1RA as markers of active disease in patients with systemic lupus erythematosus

Introduction

Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease that presents a challenge for clinicians. To identify potential biomarkers for diagnosis and disease activity in SLE, we investigated a selected yet broad panel of cytokines and autoantibodies in patients with SLE, healthy controls (HC), and patients with other autoimmune diseases (AIDs).

Methods

Serum samples from 422 SLE patients, 546 HC, and 1223 other AIDs were analysed within the frame of the European PRECISESADS project (NTC02890121). Cytokine levels were determined using Luminex panels, and autoantibodies using different immunoassays.

Results

Of the 83 cytokines analysed, 29 differed significantly between patients with SLE and HC. Specifically, CCL8, CXCL13, and IL-1RA levels were elevated in patients with active, but not inactive, SLE versus HC, as well as in patients with SLE versus other AIDs. The levels of these cytokines also correlated with SLE Disease Activity Index 2000 (SLEDAI-2K) scores, among five other cytokines. Overall, the occurrence of autoantibodies was similar across SLEDAI-2K organ domains, and the correlations between autoantibodies and activity in different organ domains were weak.

Discussion

Our findings suggest that, upon validation, CCL8, CXCL13, and IL-1RA could serve as promising serum biomarkers of activity in SLE.

Precision medicine in regulatory decision making: Biomarkers used for patient selection in European Public Assessment Reports from 2018 to 2020

Biomarkers can guide precision medicine in clinical trials and practice. They can increase clinical trials' efficiency through selection of study populations more likely to benefit from treatment, thus increasing statistical power and reducing sample size requirements or study duration. We performed a narrative synthesis to explore biomarker utilization for patient selection to guide precision medicine trials in marketing authorization dossiers of centrally approved medicines in Europe between 2018 and 2020 and analyzed in-depth those that eventually included biomarkers in the medicines' indications. From 119 eligible products, 26 included a biomarker in the indication, of which most were oncology products (n = 15). Included biomarkers were often known from literature or from previously approved products in the European Union or the United States. Additionally, 52 dossiers mentioned one or more biomarkers for patient selection in their clinical efficacy and safety information. Although these were not always included in the medicines' indication, they were often implicitly embedded in condition definitions adopted from clinical guidelines or practice. In 15 out of the 26 medicines with a biomarker-guided indication, only biomarker-positive populations were included in the main clinical studies supporting the marketing authorization. These studies were mostly randomized controlled trials or single-arm trials; only two products were studied for multiple indications in an innovative basket trial. Definitions of biomarkers could be subject of debate and needed adaptation after post hoc analyses requested by the assessment committee in four cases, stressing the importance of thorough justification of these definitions to include the right population for an optimal benefit-risk balance, enabling precise medicine.

Infant sleep predicts trajectories of social attention and later autism traits

BACKGROUND

Children with neurodevelopmental disorders including autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) often experience sleep disturbances, but little is known about when these sleep differences emerge and how they relate to later development.

METHODS

We used a prospective longitudinal design in infants with a family history of ASD and/or ADHD to examine infant sleep and its relation to trajectories of attention and later neurodevelopmental disorders. We formed factors of Day and Night Sleep from parent-reported measures (including day/night sleep duration, number of naps in the day, frequency of night awakenings and sleep onset problems). We examined sleep in 164 infants at 5-, 10- and 14-months with/without a first-degree relative with ASD and/or ADHD who underwent a consensus clinical assessment for ASD at age 3.

RESULTS

By 14-months, infants with a first-degree relative with ASD (but not ADHD) showed lower Night Sleep scores than infants with no family history of ASD; lower Night Sleep scores in infancy were also associated with a later ASD diagnosis, decreased cognitive ability, increased ASD symptomatology at 3-years, and developing social attention (e.g., looking to faces). We found no such effects with Day Sleep.

CONCLUSIONS

Sleep disturbances may be apparent at night from 14-months in infants with a family history of ASD and also those with later ASD, but were not associated with a family history of ADHD. Infant sleep disturbances were also linked to later dimensional variation in cognitive and social skills across the cohort. Night Sleep and Social Attention were interrelated over the first 2 years of life, suggesting that this may be one mechanism through which sleep quality influences neurodevelopment. Interventions targeted towards supporting families with their infant's sleep problems may be useful in this population.

Non-invasive prediction of overall survival time for glioblastoma multiforme patients based on multimodal MRI radiomics

Glioblastoma multiforme (GBM) is the most common and deadly primary malignant brain tumor. As GBM tumor is aggressive and shows high biological heterogeneity, the overall survival (OS) time is extremely low even with the most aggressive treatment. If the OS time can be predicted before surgery, developing personalized treatment plans for GBM patients will be beneficial. Magnetic resonance imaging (MRI) is a commonly used diagnostic tool for brain tumors with high-resolution and sound imaging effects. However, in clinical practice, doctors mainly rely on manually segmenting the tumor regions in MRI and predicting the OS time of GBM patients, which is time-consuming, subjective and repetitive, limiting the effectiveness of clinical diagnosis and treatment. Therefore, it is crucial to segment the brain tumor regions in MRI, and an accurate pre-operative prediction of OS time for personalized treatment is highly desired. In this study, we present a multimodal MRI radiomics-based automatic framework for non-invasive prediction of the OS time for GBM patients. A modified 3D-UNet model is built to segment tumor subregions in MRI of GBM patients; then, the radiomic features in the tumor subregions are extracted and combined with the clinical features input into the Support Vector Regression (SVR) model to predict the OS time. In the experiments, the BraTS2020, BraTS2019 and BraTS2018 datasets are used to evaluate our framework. Our model achieves competitive OS time prediction accuracy compared to most typical approaches.

Enhanced antiviral immunity and dampened inflammation in llama lymph nodes upon MERS-CoV sensing: bridging innate and adaptive cellular immune responses in camelid reservoirs

Middle East respiratory syndrome coronavirus (MERS-CoV) infection can cause fatal pulmonary inflammatory disease in humans. Contrarily, camelids and bats are the main reservoir hosts, tolerant for MERS-CoV replication without suffering clinical disease. Here, we isolated cervical lymph node (LN) cells from MERS-CoV convalescent llamas and pulsed them with two different viral strains (clades B and C). Viral replication was not supported in LN, but a cellular immune response was mounted. Reminiscent Th1 responses (IFN-γ, IL-2, IL-12) were elicited upon MERS-CoV sensing, accompanied by a marked and transient peak of antiviral responses (type I IFNs, IFN-λ3, ISGs, PRRs and TFs). Importantly, expression of inflammatory cytokines (TNF-α, IL-1β, IL-6, IL-8) or inflammasome components (NLRP3, CASP1, PYCARD) was dampened. The role of IFN-λ3 to counterbalance inflammatory processes and bridge innate and adaptive immune responses in camelid species is discussed. Our findings shed light into key mechanisms on how reservoir species control MERS-CoV in the absence of clinical disease.

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Alzheimer's disease-associated R47H TREM2 increases, but wild-type TREM2 decreases, microglial phagocytosis of synaptosomes and neuronal loss

Triggering receptor on myeloid cells 2 (TREM2) is an innate immune receptor, upregulated on the surface of microglia associated with amyloid plaques in Alzheimer's disease (AD). Individuals heterozygous for the R47H variant of TREM2 have greatly increased risk of developing AD. We examined the effects of wild-type (WT), R47H and knock-out (KO) of human TREM2 expression in three microglial cell systems. Addition of mouse BV-2 microglia expressing R47H TREM2 to primary mouse neuronal cultures caused neuronal loss, not observed with WT TREM2. Neuronal loss was prevented by using annexin V to block exposed phosphatidylserine, an eat-me signal and ligand of TREM2, suggesting loss was mediated by microglial phagocytosis of neurons exposing phosphatidylserine. Addition of human CHME-3 microglia expressing R47H TREM2 to LUHMES neuronal-like cells also caused loss compared to WT TREM2. Expression of R47H TREM2 in BV-2 and CHME-3 microglia increased their uptake of phosphatidylserine-beads and synaptosomes versus WT TREM2. Human iPSC-derived microglia with heterozygous R47H TREM2 had increased phagocytosis of synaptosomes vs common-variant TREM2. Additionally, phosphatidylserine liposomes increased activation of human iPSC-derived microglia expressing homozygous R47H TREM2 versus common-variant TREM2. Finally, overexpression of TREM2 in CHME-3 microglia caused increased expression of cystatin F, a cysteine protease inhibitor, and knock-down of cystatin F increased CHME-3 uptake of phosphatidylserine-beads. Together, these data suggest that R47H TREM2 may increase AD risk by increasing phagocytosis of synapses and neurons via greater activation by phosphatidylserine and that WT TREM2 may decrease microglial phagocytosis of synapses and neurons via cystatin F.

Assessing the feasibility of a web-based outcome measurement system in child and adolescent mental health services - myHealthE a randomised controlled feasibility pilot study

BACKGROUND

Interest in internet-based patient reported outcome measure (PROM) collection is increasing. The NHS myHealthE (MHE) web-based monitoring system was developed to address the limitations of paper-based PROM completion. MHE provides a simple and secure way for families accessing Child and Adolescent Mental Health Services to report clinical information and track their child's progress. This study aimed to assess whether MHE improves the completion of the Strengths and Difficulties Questionnaire (SDQ) compared with paper collection. Secondary objectives were to explore caregiver satisfaction and application acceptability.

METHODS

A 12-week single-blinded randomised controlled feasibility pilot trial of MHE was conducted with 196 families accessing neurodevelopmental services in south London to examine whether electronic questionnaires are completed more readily than paper-based questionnaires over a 3-month period. Follow up process evaluation phone calls with a subset (n = 8) of caregivers explored system satisfaction and usability.

RESULTS

MHE group assignment was significantly associated with an increased probability of completing an SDQ-P in the study period (adjusted hazard ratio (HR) 12.1, 95% CI 4.7-31.0; p = <.001). Of those caregivers' who received the MHE invitation (n = 68) 69.1% completed an SDQ using the platform compared to 8.8% in the control group (n = 68). The system was well received by caregivers, who cited numerous benefits of using MHE, for example, real-time feedback and ease of completion.

CONCLUSIONS

MHE holds promise for improving PROM completion rates. Research is needed to refine MHE, evaluate large-scale MHE implementation, cost effectiveness and explore factors associated with differences in electronic questionnaire uptake.

Hurdles and signposts on the road to virtual control groups-A case study illustrating the influence of anesthesia protocols on electrolyte levels in rats

Introduction: Virtual Control Groups (VCGs) represent the concept of using historical control data from legacy animal studies to replace concurrent control group (CCG) animals. Based on the data curation and sharing activities of the Innovative Medicine Initiatives project eTRANSAFE (enhancing TRANSlational SAFEty Assessment through Integrative Knowledge Management) the ViCoG working group was established with the objectives of i) collecting suitable historical control data sets from preclinical toxicity studies, ii) evaluating statistical methodologies for building adequate and regulatory acceptable VCGs from historical control data, and iii) sharing those control-group data across multiple pharmaceutical companies. During the qualification process of VCGs a particular focus was put on the identification of hidden confounders in the data sets, which might impair the adequate matching of VCGs with the CCG. Methods: During our analyses we identified such a hidden confounder, namely, the choice of the anesthetic procedure used in animal experiments before blood withdrawal. Anesthesia using CO₂ may elevate the levels of some electrolytes such as calcium in blood, while the use of isoflurane is known to lower these values. Identification of such hidden confounders is particularly important if the underlying experimental information (e.g., on the anesthetic procedure) is not routinely recorded in the standard raw data files, such as SEND (Standard for Exchange of Non-clinical Data). We therefore analyzed how the replacement of CCGs with VCGs would affect the reproducibility of treatment-related findings regarding electrolyte values (potassium, calcium, sodium, and phosphate). The analyses were performed using a legacy rat systemic toxicity study consisting of a control and three treatment groups conducted according to pertinent OECD guidelines. In the report of this study treatment-related hypercalcemia was reported. The rats in this study were anesthetized with isoflurane. Results: Replacing the CCGs with VCGs derived from studies comprising both anesthetics resulted in a shift of control electrolyte parameters. Instead of the originally reported hypercalcemia the use of VCG led to fallacious conclusions of no observed effect or hypocalcemia. Discussion: Our study highlights the importance of a rigorous statistical analysis including the detection and elimination of hidden confounders prior to the implementation of the VCG concept.

Unique dynamic profiles of social attention in autistic females

BACKGROUND

Social attention affords learning opportunities across development and may contribute to individual differences in developmental trajectories, such as between male and female individuals, and in neurodevelopmental conditions, such as autism.

METHODS

Using eye-tracking, we measured social attention in a large cohort of autistic (n = 123) and nonautistic females (n = 107), and autistic (n = 330) and nonautistic males (n = 204), aged 6-30 years. Using mixed Growth Curve Analysis, we modelled sex and diagnostic effects on the temporal dynamics of proportional looking time to three types of social stimuli (lean-static, naturalistic-static, and naturalistic-dynamic) and examined the link between individual differences and dimensional social and nonsocial autistic traits in autistic females and males.

RESULTS

In the lean-static stimulus, average face-looking was higher in females than in males of both autistic and nonautistic groups. Differences in the dynamic pattern of face-looking were seen in autistic vs. nonautistic females, but not males, with face-looking peaking later in the trial in autistic females. In the naturalistic-dynamic stimulus, average face-looking was higher in females than in males of both groups; changes in the dynamic pattern of face looking were seen in autistic vs. nonautistic males, but not in females, with a steeper peak in nonautistic males. Lower average face-looking was associated with higher observer-measured autistic characteristics in autistic females, but not in males.

CONCLUSIONS

Overall, we found stronger social attention in females to a similar degree in both autistic and nonautistic groups. Nonetheless, the dynamic profiles of social attention differed in different ways in autistic females and males compared to their nonautistic peers, and autistic traits predicted trends of average face-looking in autistic females. These findings support the role of social attention in the emergence of sex-related differences in autistic characteristics, suggesting an avenue to phenotypic stratification.

Bioengineered Pancreas-Liver Crosstalk in a Microfluidic Coculture Chip Identifies Human Metabolic Response Signatures in Prediabetic Hyperglycemia

Aberrant glucose homeostasis is the most common metabolic disturbance affecting one in ten adults worldwide. Prediabetic hyperglycemia due to dysfunctional interactions between different human tissues, including pancreas and liver, constitutes the largest risk factor for the development of type 2 diabetes. However, this early stage of metabolic disease has received relatively little attention. Microphysiological tissue models that emulate tissue crosstalk offer emerging opportunities to study metabolic interactions. Here, a novel modular multitissue organ-on-a-chip device is presented that allows for integrated and reciprocal communication between different 3D primary human tissue cultures. Precisely controlled heterologous perfusion of each tissue chamber is achieved through a microfluidic single "synthetic heart" pneumatic actuation unit connected to multiple tissue chambers via specific configuration of microchannel resistances. On-chip coculture experiments of organotypic primary human liver spheroids and intact primary human islets demonstrate insulin secretion and hepatic insulin response dynamics at physiological timescales upon glucose challenge. Integration of transcriptomic analyses with promoter motif activity data of 503 transcription factors reveals tissue-specific interacting molecular networks that underlie β-cell stress in prediabetic hyperglycemia. Interestingly, liver and islet cultures show surprising counter-regulation of transcriptional programs, emphasizing the power of microphysiological coculture to elucidate the systems biology of metabolic crosstalk.

What matters most to patients with multiple myeloma? A Pan-European patient preference study

INTRODUCTION

Given the rapid increase in novel treatments for patients with multiple myeloma (MM), this patient preference study aimed to establish which treatment attributes matter most to MM patients and evaluate discrete choice experiment (DCE) and swing weighting (SW) as two elicitation methods for quantifying patients' preferences.

METHODS

A survey incorporating DCE and SW was disseminated among European MM patients. The survey included attributes and levels informed by a previous qualitative study with 24 MM patients. Latent class and mixed logit models were used to estimate the DCE attribute weights and descriptive analyses were performed to derive SW weights. MM patients and patient organisations provided extensive feedback during survey development.

RESULTS

393 MM patients across 21 countries completed the survey (M years since diagnosis=6; M previous therapies=3). Significant differences (p<.01) between participants' attribute weights were revealed depending on participants' prior therapy experience, and their experience with side-effects and symptoms. Multivariate analyses showed that participants across the three MM patient classes identified via the latent class model differed regarding their past number of therapies (F=4.772, p=.009). Patients with the most treatments (class 1) and those with the least treatments (class 3) attached more value to life expectancy versus quality of life-related attributes such as pain, mobility and thinking problems. Conversely, patients with intermediary treatment experience (class 2) attached more value to quality of life-related attributes versus life expectancy. Participants highlighted the difficulty of trading-off between life expectancy and quality of life and between physical and mental health. Participants expressed a need for greater psychological support to cope with their symptoms, treatment side-effects, and uncertainties. With respect to patients' preferences for the DCE or SW questions, 42% had no preference, 32% preferred DCE, and 25% preferred SW.

CONCLUSIONS

Quality of life-related attributes affecting MM patients' physical, mental and psychological health such as pain, mobility and thinking problems were considered very important to MM patients, next to life expectancy. This underscores a need to include such attributes in decision-making by healthcare stakeholders involved in MM drug development, evidence generation, evaluation, and clinical practice. This study highlights DCE as the preferred methodology for understanding relative attribute weights from a patient's perspective.

In vivo and in vitro characterization of GL0034, a novel long-acting glucagon-like peptide-1 receptor agonist

AIMS

To describe the in vitro characteristics and antidiabetic in vivo efficacy of the novel glucagon-like peptide-1 receptor agonist (GLP-1RA) GL0034.

MATERIALS AND METHODS

Glucagon-like peptide-1 receptor (GLP-1R) kinetic binding parameters, cyclic adenosine monophosphate (cAMP) signalling, endocytosis and recycling were measured using HEK293 and INS-1832/3 cells expressing human GLP-1R. Insulin secretion was measured in vitro using INS-1832/3 cells, mouse islets and human islets. Chronic administration studies to evaluate weight loss and glycaemic effects were performed in db/db and diet-induced obese mice.

RESULTS

Compared to the leading GLP-1RA semaglutide, GL0034 showed increased binding affinity and potency-driven bias in favour of cAMP over GLP-1R endocytosis and β-arrestin-2 recruitment. Insulin secretory responses were similar for both ligands. GL0034 (6 nmol/kg) led to at least as much weight loss and lowering of blood glucose as did semaglutide at a higher dose (14 nmol/kg).

CONCLUSIONS

GL0034 is a G protein-biased agonist that shows powerful antidiabetic effects in mice, and may serve as a promising new GLP-1RA for obese patients with type 2 diabetes.

Hospital costs associated with adverse events in people with diabetes in the UK

AIM

To estimate the annual hospital costs associated with a range of adverse events for people with diabetes in the UK.

METHODS

Annual hospital costs (2019/2020) were derived from 15 436 ASCEND participants from 2005 to 2017 (120 420 person-years). The annual hospital costs associated with cardiovascular events (myocardial infarction, coronary revascularization, transient ischaemic attack [TIA], ischaemic stroke, heart failure), bleeding (gastrointestinal [GI] bleed, intracranial haemorrhage, other major bleed), cancer (GI tract cancer, non-GI tract cancer), end-stage renal disease (ESRD), lower limb amputation and death (vascular, non-vascular) were estimated using a generalized linear model following adjustment for participants' sociodemographic and clinical factors.

RESULTS

In the year of event, ESRD was associated with the largest increase in annual hospital cost (£20 954), followed by lower limb amputation (£17 887), intracranial haemorrhage (£12 080), GI tract cancer (£10 160), coronary revascularization (£8531 if urgent; £8302 if non-urgent), heart failure (£8319), non-GI tract cancer (£7409), ischaemic stroke (£7170), GI bleed (£5557), myocardial infarction (£4913), other major bleed (£3825) and TIA (£1523). In subsequent years, most adverse events were associated with lasting but smaller increases in hospital costs, except for ESRD, where the additional cost remained high (£20 090).

CONCLUSIONS

Our study provides robust estimates of annual hospital costs associated with a range of adverse events in people with diabetes that can inform future cost-effectiveness analyses of diabetes interventions. It also highlights the potential cost savings that could be derived from prevention of these costly complications.

Significant reduction in chronic kidney disease progression with sodium-glucose cotransporter-2 inhibitors compared to dipeptidyl peptidase-4 inhibitors in adults with type 2 diabetes in a UK clinical setting: An observational outcomes study based on international guidelines for kidney disease

AIMS

To confirm the reno-protective effects of sodium-glucose cotransporter-2 (SGLT2) inhibitors compared with dipeptidyl peptidase-4 (DPP-4) inhibitors on the onset and progression of chronic kidney disease (CKD) in routine clinical practice.

MATERIALS AND METHODS

We conducted a retrospective cohort study using the Clinical Practice Research Datalink Aurum database linked to Hospital Episode Statistics. The primary outcome was risk of the composite CKD endpoint based on the recent consensus guidelines for kidney disease: >40% decline in estimated glomerular filtration rate (eGFR), kidney death or end-stage kidney disease (ESKD; a composite of kidney transplantation, maintenance of dialysis, sustained low eGFR <15 ml/min/1.73m² or diagnosis of ESKD). Secondary outcomes were components of the composite CKD endpoint, analysed separately. Patients were propensity-score-matched 1:1 for SGLT2 inhibitor versus DPP-4 inhibitor use.

RESULTS

A total of 131 824 people with type 2 diabetes (T2D) were identified; 79.0% had no known history of CKD. During a median follow-up of 2.1 years, SGLT2 inhibitor initiation was associated with lower risk of progression to composite kidney endpoints than DPP-4 inhibitor initiation (7.48 vs. 11.77 events per 1000 patient-years, respectively). Compared with DPP-4 inhibitor initiation, SGLT2 inhibitor initiation was associated with reductions in the primary composite CKD endpoint (hazard ratio [HR] 0.64, 95% confidence interval [CI] 0.56-0.74), all-cause mortality (HR 0.74, 95% CI 0.64-0.86) and ESKD (HR 0.37, 95% CI 0.25-0.55), reduced the rate of sustained low eGFR (HR 0.33, 95% CI 0.19-0.57), and reduced diagnoses of ESKD in primary care (HR 0.04, 95% CI 0.01-0.18). Results were consistent across subgroup and sensitivity analyses.

CONCLUSIONS

In adults with T2D, initiation of an SGLT2 inhibitor was associated with a significantly reduced risk of CKD progression and death compared with initiation of a DPP-4 inhibitor.

Benchmarking post-GWAS analysis tools in major depression: Challenges and implications

Our knowledge of complex disorders has increased in the last years thanks to the identification of genetic variants (GVs) significantly associated with disease phenotypes by genome-wide association studies (GWAS). However, we do not understand yet how these GVs functionally impact disease pathogenesis or their underlying biological mechanisms. Among the multiple post-GWAS methods available, fine-mapping and colocalization approaches are commonly used to identify causal GVs, meaning those with a biological effect on the trait, and their functional effects. Despite the variety of post-GWAS tools available, there is no guideline for method eligibility or validity, even though these methods work under different assumptions when accounting for linkage disequilibrium and integrating molecular annotation data. Moreover, there is no benchmarking of the available tools. In this context, we have applied two different fine-mapping and colocalization methods to the same GWAS on major depression (MD) and expression quantitative trait loci (eQTL) datasets. Our goal is to perform a systematic comparison of the results obtained by the different tools. To that end, we have evaluated their results at different levels: fine-mapped and colocalizing GVs, their target genes and tissue specificity according to gene expression information, as well as the biological processes in which they are involved. Our findings highlight the importance of fine-mapping as a key step for subsequent analysis. Notably, the colocalizing variants, altered genes and targeted tissues differed between methods, even regarding their biological implications. This contribution illustrates an important issue in post-GWAS analysis with relevant consequences on the use of GWAS results for elucidation of disease pathobiology, drug target prioritization and biomarker discovery.

Transcriptional regulation and drug resistance in Mycobacterium tuberculosis

Bacterial drug resistance is one of the major challenges to present and future human health, as the continuous selection of multidrug resistant bacteria poses at serious risk the possibility to treat infectious diseases in the near future. One of the infection at higher risk to become incurable is tuberculosis, due to the few drugs available in the market against Mycobacterium tuberculosis. Drug resistance in this species is usually due to point mutations in the drug target or in proteins required to activate prodrugs. However, another interesting and underexplored aspect of bacterial physiology with important impact on drug susceptibility is represented by the changes in transcriptional regulation following drug exposure. The main regulators involved in this phenomenon in M. tuberculosis are the sigma factors, and regulators belonging to the WhiB, GntR, XRE, Mar and TetR families. Better understanding the impact of these regulators in survival to drug treatment might contribute to identify new drug targets and/or to design new strategies of intervention.

Hypo-METRICS: Hypoglycaemia-MEasurement, ThResholds and ImpaCtS-A multi-country clinical study to define the optimal threshold and duration of sensor-detected hypoglycaemia that impact the experience of hypoglycaemia, quality of life and health economic outcomes: The study protocol

INTRODUCTION

Hypoglycaemia is a significant burden to people living with diabetes and an impediment to achieving optimal glycaemic outcomes. The use of continuous glucose monitoring (CGM) has improved the capacity to assess duration and level of hypoglycaemia. The personal impact of sensor-detected hypoglycaemia (SDH) is unclear. Hypo-METRICS is an observational study designed to define the threshold and duration of sensor glucose that provides the optimal sensitivity and specificity for events that people living with diabetes experience as hypoglycaemia.

METHODS

We will recruit 600 participants: 350 with insulin-treated type 2 diabetes, 200 with type 1 diabetes and awareness of hypoglycaemia and 50 with type 1 diabetes and impaired awareness of hypoglycaemia who have recent experience of hypoglycaemia. Participants will wear a blinded CGM device and an actigraphy monitor to differentiate awake and sleep times for 10 weeks. Participants will be asked to complete three short surveys each day using a bespoke mobile phone app, a technique known as ecological momentary assessment. Participants will also record all episodes of self-detected hypoglycaemia on the mobile app. We will use particle Markov chain Monte Carlo optimization to identify the optimal threshold and duration of SDH that have optimum sensitivity and specificity for detecting patient-reported hypoglycaemia. Key secondary objectives include measuring the impact of symptomatic and asymptomatic SDH on daily functioning and health economic outcomes.

ETHICS AND DISSEMINATION

The protocol was approved by local ethical boards in all participating centres. Study results will be shared with participants, in peer-reviewed journal publications and conference presentations.

Development of Human Cell-Based In Vitro Infection Models to Determine the Intracellular Survival of Mycobacterium avium

The Mycobacterium avium (Mav) complex accounts for more than 80% of all pulmonary diseases caused by non-tuberculous mycobacteria (NTM) infections, which have an alarming increase in prevalence and vary in different regions, currently reaching 0.3–9.8 per 100,000 individuals. Poor clinical outcomes, as a result of increasing microbial drug resistance and low treatment adherence due to drug-toxicities, emphasize the need for more effective treatments. Identification of more effective treatments, however, appears to be difficult, which may be due to the intracellular life of NTM and concomitant altered drug sensitivity that is not taken into account using traditional drug susceptibility testing screenings. We therefore developed human cell-based in vitro Mav infection models using the human MelJuSo cell line as well as primary human macrophages and a fluorescently labeled Mav strain. By testing a range of multiplicity of infection (MOI) and using flow cytometry and colony-forming unit (CFU) analysis, we found that an MOI of 10 was the most suitable for Mav infection in primary human macrophages, whereas an MOI of 50 was required to achieve similar results in MelJuSo cells. Moreover, by monitoring intracellular bacterial loads over time, the macrophages were shown to be capable of controlling the infection, while MelJuSo cells failed to do so. When comparing the MGIT system with the classical CFU counting assay to determine intracellular bacterial loads, MGIT appeared as a less labor-intensive, more precise, and more objective alternative. Next, using our macrophage Mav infection models, the drug efficacy of the first-line drug rifampicin and the more recently discovered bedaquiline on intracellular bacteria was compared to the activity on extracellular bacteria. The efficacy of the antibiotics inhibiting bacterial growth was significantly lower against intracellular bacteria compared to extracellular bacteria. This finding emphasizes the crucial role of the host cell during infection and drug susceptibility and highlights the usefulness of the models. Taken together, the human cell-based Mav infection models are reliable tools to determine the intracellular loads of Mav, which will enable researchers to investigate host–pathogen interactions and to evaluate the efficacy of (host-directed) therapeutic strategies against Mav.

Validation of a Harmonized Enzyme-Linked-Lectin-Assay (ELLA-NI) Based Neuraminidase Inhibition Assay Standard Operating Procedure (SOP) for Quantification of N1 Influenza Antibodies and the Use of a Calibrator to Improve the Reproducibility of the ELLA-NI With Reverse Genetics Viral and Recombinant Neuraminidase Antigens: A FLUCOP Collaborative Study

Current vaccination strategies against influenza focus on generating an antibody response against the viral haemagglutination surface protein, however there is increasing interest in neuraminidase (NA) as a target for vaccine development. A critical tool for development of vaccines that target NA or include an NA component is available validated serology assays for quantifying anti-NA antibodies. Additionally serology assays have a critical role in defining correlates of protection in vaccine development and licensure. Standardisation of these assays is important for consistent and accurate results. In this study we first validated a harmonized enzyme-linked lectin assay (ELLA)- Neuraminidase Inhibition (NI) SOP for N1 influenza antigen and demonstrated the assay was precise, linear, specific and robust within classical acceptance criteria for neutralization assays for vaccine testing. Secondly we tested this SOP with NA from influenza B viruses and showed the assay performed consistently with both influenza A and B antigens. Third, we demonstrated that recombinant NA (rNA) could be used as a source of antigen in ELLA-NI. In addition to validating a harmonized SOP we finally demonstrated a clear improvement in inter-laboratory agreement across several studies by using a calibrator. Importantly we showed that the use of a calibrator significantly improved agreement when using different sources of antigen in ELLA-NI, namely reverse genetics viruses and recombinant NA. We provide a freely available and detailed harmonized SOP for ELLA-NI. Our results add to the growing body of evidence in support of developing biological standards for influenza serology.

Case Report: Bosentan and Sildenafil Exposure in Human Milk - A Contribution From the ConcePTION Project

Introduction: Quantitative information on disposition of maternal medicines in human milk remains a major knowledge gap. This case report presents the clinical and pharmacokinetic data of a single mother-infant pair exposed to bosentan and sildenafil for the treatment of pulmonary arterial hypertension (PAH) during lactation.

Case presentation: A 43-year old mother was treated with sildenafil (20 mg, 3x/day) and bosentan (125 mg, 2x/day) for PAH. Her 21-months old infant received breastfeeding in combination with adequate complementary foods. Milk samples were collected over 24 h, at day 637 and 651 after delivery. The observed average steady-state concentrations of sildenafil (2.84 μg/L) and bosentan (49.0 μg/L) in human milk were low. The Daily Infant Dosage ingested by the nursing infant through human milk was 0.02 μg/kg/day for sildenafil and 0.29 μg/kg/day for bosentan at day 637, and 0.03 μg/kg/day and 0.60 μg/kg/day at day 651. The Relative Infant Dose calculated for an exclusively breastfed infant with an estimated milk intake of 150 ml/kg/day, was 0.06% for sildenafil and 0.24% for bosentan. General health outcome of the infant, reported by the mother, was uneventful until the sampling days.

Conclusion: Low medicine concentrations were found in human milk expressed 21 months after delivery after maternal intake of 20 mg sildenafil three times daily and 125 mg bosentan twice daily. General health of the nursing infant until sampling was reported as optimal by the mother.

Improving Small Molecule pKa Prediction Using Transfer Learning With Graph Neural Networks

Enumerating protonation states and calculating microstate pK_a values of small molecules is an important yet challenging task for lead optimization and molecular modeling. Commercial and non-commercial solutions have notable limitations such as restrictive and expensive licenses, high CPU/GPU hour requirements, or the need for expert knowledge to set up and use. We present a graph neural network model that is trained on 714,906 calculated microstate pK_a predictions from molecules obtained from the ChEMBL database. The model is fine-tuned on a set of 5,994 experimental pK_a values significantly improving its performance on two challenging test sets. Combining the graph neural network model with Dimorphite-DL, an open-source program for enumerating ionization states, we have developed the open-source Python package pkasolver, which is able to generate and enumerate protonation states and calculate pK_a values with high accuracy.

Memory B Cell Activation Induced by Pertussis Booster Vaccination in Four Age Groups of Three Countries

Background

Immunogenicity of acellular pertussis (aP) vaccines is conventionally assessed by measuring antibody responses but antibody concentrations wane quickly after vaccination. Memory B cells, however, are critical in sustaining long-term protection and therefore may be an important factor when assessing pertussis immunity after vaccination.

Aim

We studied pertussis specific memory B cell (re)activation induced by an aP booster vaccination in four different age groups within three countries.

Materials and methods

From a phase IV longitudinal interventional study, 268 participants across Finland, the Netherlands and the United Kingdom were included and received a 3-component pertussis booster vaccine: children (7-10y, n=53), adolescents (11-15y, n=66), young adults (20-34y, n=74), and older adults (60-70y, n=75). Memory B cells at baseline, day 28, and 1 year post-vaccination were measured by a pertussis toxin (Ptx), filamentous haemagglutinin (FHA), and pertactin (Prn) specific ELISpot assay. Antibody results measured previously were available for comparison. Furthermore, study participants were distributed into groups based on their baseline memory B cell frequencies, vaccine responses were monitored between these groups.

Results

Geometric mean (GM) memory B cell frequencies for pertussis antigens at baseline were low. At 28 days post-vaccination, these frequencies increased within each age group and were still elevated one year post-booster compared to baseline. Highest frequencies at day 28 were found within adolescents (GM: 5, 21, and 13, for Ptx, FHA and Prn, respectively) and lowest within older adults (GM: 2, 9, and 3, respectively). Moderate to strong correlations between memory B cell frequencies at day 28 and antibody concentrations at day 28 and 1 year were observed for Prn. Memory B cell frequencies &gt; 1 per 100,000 PBMCs at baseline were associated with significantly higher memory responses after 28 days and 1 year.

Conclusions

An aP booster vaccine (re)activated memory B cells in all age groups. Still elevated memory B cell frequencies after one year indicates enhanced immunological memory. However, antigen specific memory B cell activation seems weaker in older adults, which might reflect immunosenescence. Furthermore, the presence of circulating memory B cells at baseline positively affects memory B cell responses. This study was registered at www.clinicaltrialsregister.eu: No. 2016-003678-42.

Impedance-Based Phenotypic Readout of Transporter Function: A Case for Glutamate Transporters

Excitatory amino acid transporters (EAAT/SLC1) mediate Na⁺-dependent uptake of extracellular glutamate and are potential drug targets for neurological disorders. Conventional methods to assess glutamate transport in vitro are based on radiolabels, fluorescent dyes or electrophysiology, which potentially compromise the cell’s physiology and are generally less suited for primary drug screens. Here, we describe a novel label-free method to assess human EAAT function in living cells, i.e., without the use of chemical modifications to the substrate or cellular environment. In adherent HEK293 cells overexpressing EAAT1, stimulation with glutamate or aspartate induced cell spreading, which was detected in real-time using an impedance-based biosensor. This change in cell morphology was prevented in the presence of the Na⁺/K⁺-ATPase inhibitor ouabain and EAAT inhibitors, which suggests the substrate-induced response was ion-dependent and transporter-specific. A mechanistic explanation for the phenotypic response was substantiated by actin cytoskeleton remodeling and changes in the intracellular levels of the osmolyte taurine, which suggests that the response involves cell swelling. In addition, substrate-induced cellular responses were observed for cells expressing other EAAT subtypes, as well as in a breast cancer cell line (MDA-MB-468) with endogenous EAAT1 expression. These findings allowed the development of a label-free high-throughput screening assay, which could be beneficial in early drug discovery for EAATs and holds potential for the study of other transport proteins that modulate cell shape.

Molecular Mingling: Multimodal Predictions of Ligand Promiscuity in Pentameric Ligand-Gated Ion Channels

Background: Human pentameric ligand-gated ion channels (pLGICs) comprise nicotinic acetylcholine receptors (nAChRs), 5-hydroxytryptamine type 3 receptors (5-HT3Rs), zinc-activated channels (ZAC), γ-aminobutyric acid type A receptors (GABAARs) and glycine receptors (GlyRs). They are recognized therapeutic targets of some of the most prescribed drugs like general anesthetics, anxiolytics, smoking cessation aids, antiemetics and many more. Currently, approximately 100 experimental structures of pLGICs with ligands bound exist in the protein data bank (PDB). These atomic-level 3D structures enable the generation of a comprehensive binding site inventory for the superfamily and the in silico prediction of binding site properties. Methods: A panel of high throughput in silico methods including pharmacophore screening, conformation analysis and descriptor calculation was applied to a selection of allosteric binding sites for which in vitro screens are lacking. Variant abundance near binding site forming regions and computational docking complement the approach. Results: The structural data reflects known and novel binding sites, some of which may be unique to individual receptors, while others are broadly conserved. The membrane spanning domain, comprising four highly conserved segments, contains ligand interaction sites for which in vitro assays suitable for high throughput screenings are critically lacking. This is also the case for structurally more variable novel sites in the extracellular domain. Our computational results suggest that the phytocannabinoid Δ9-tetrahydrocannabinol (Δ9-THC) can utilize multiple pockets which are likely to exist on most superfamily members. Conclusion: With this study, we explore the potential for polypharmacology among pLGICs. Our data suggest that ligands can display two forms of promiscuity to an extent greater than what has been realized: 1) Ligands can interact with homologous sites in many members of the superfamily, which bears toxicological relevance. 2) Multiple pockets in distinct localizations of individual receptor subtypes share common ligands, which counteracts efforts to develop selective agents. Moreover, conformational states need to be considered for in silico drug screening, as certain binding sites display considerable flexibility. In total, this work contributes to a better understanding of polypharmacology across pLGICs and provides a basis for improved structure guided in silico drug development and drug derisking.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software

PURPOSE

A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed.

METHODS

The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate μ $\mu$ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV.

RESULTS

The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1-2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration.

CONCLUSIONS

We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases

Objective: Background incidence rates are routinely used in safety studies to evaluate an association of an exposure and outcome. Systematic research on sensitivity of rates to the choice of the study parameters is lacking. Materials and Methods: We used 12 data sources to systematically examine the influence of age, race, sex, database, time-at-risk, season and year, prior observation and clean window on incidence rates using 15 adverse events of special interest for COVID-19 vaccines as an example. For binary comparisons we calculated incidence rate ratios and performed random-effect meta-analysis. Results: We observed a wide variation of background rates that goes well beyond age and database effects previously observed. While rates vary up to a factor of 1,000 across age groups, even after adjusting for age and sex, the study showed residual bias due to the other parameters. Rates were highly influenced by the choice of anchoring (e.g., health visit, vaccination, or arbitrary date) for the time-at-risk start. Anchoring on a healthcare encounter yielded higher incidence comparing to a random date, especially for short time-at-risk. Incidence rates were highly influenced by the choice of the database (varying by up to a factor of 100), clean window choice and time-at-risk duration, and less so by secular or seasonal trends. Conclusion: Comparing background to observed rates requires appropriate adjustment and careful time-at-risk start and duration choice. Results should be interpreted in the context of study parameter choices.

Real-World Walking Speed Assessment Using a Mass-Market RTK-GNSS Receiver

Walking speed is an important clinical parameter because it sums up the ability to move and predicts adverse outcomes. However, usually measured inside the clinics, it can suffer from poor ecological validity. Wearable devices such as global positioning systems (GPS) can be used to measure real-world walking speed. Still, the accuracy of GPS systems decreases in environments with poor sky visibility. This work tests a solution based on a mass-market, real-time kinematic receiver (RTK), overcoming such limitations. Seven participants walked a predefined path composed of tracts with different sky visibility. The walking speed was calculated by the RTK and compared with a reference value calculated using an odometer and a stopwatch. Despite tracts with totally obstructed visibility, the correlation between the receiver and the reference system was high (0.82 considering all tracts and 0.93 considering high-quality tracts). Similarly, a Bland Altman analysis showed a minimal detectable change of 0.12 m/s in the general case and 0.07 m/s considering only high-quality tracts. This work demonstrates the feasibility and validity of the presented device for the measurement of real-world walking speed, even in tracts with high interference. These findings pave the way for clinical use of the proposed device to measure walking speed in the real world, thus enabling digital remote monitoring of locomotor function. Several populations may benefit from similar devices, including older people at a high risk of fall, people with neurological diseases, and people following a rehabilitation intervention.

A population-based study of 92 clinically recognized risk factors for heart failure: co-occurrence, prognosis and preventive potential

AIMS

Primary prevention strategies for heart failure (HF) have had limited success, possibly due to a wide range of underlying risk factors (RFs). Systematic evaluations of the prognostic burden and preventive potential across this wide range of risk factors are lacking. We aimed at estimating evidence, prevalence and co-occurrence for primary prevention and impact on prognosis of RFs for incident HF.

METHODS AND RESULTS

We systematically reviewed trials and observational evidence of primary HF prevention across 92 putative aetiologic RFs for HF identified from US and European clinical practice guidelines. We identified 170 885 individuals aged ≥30 years with incident HF from 1997 to 2017, using linked primary and secondary care UK electronic health records (EHR) and rule-based phenotypes (ICD-10, Read Version 2, OPCS-4 procedure and medication codes) for each of 92 RFs. Only 10/92 factors had high quality observational evidence for association with incident HF; 7 had effective randomized controlled trial (RCT)-based interventions for HF prevention (RCT-HF), and 6 for cardiovascular disease prevention, but not HF (RCT-CVD), and the remainder had no RCT-based preventive interventions (RCT-0). We were able to map 91/92 risk factors to EHR using 5961 terms, and 88/91 factors were represented by at least one patient. In the 5 years prior to HF diagnosis, 44.3% had ≥4 RFs. By RCT evidence, the most common RCT-HF RFs were hypertension (48.5%), stable angina (34.9%), unstable angina (16.8%), myocardial infarction (15.8%), and diabetes (15.1%); RCT-CVD RFs were smoking (46.4%) and obesity (29.9%); and RCT-0 RFs were atrial arrhythmias (17.2%), cancer (16.5%), heavy alcohol intake (14.9%). Mortality at 1 year varied across all 91 factors (lowest: pregnancy-related hormonal disorder 4.2%; highest: phaeochromocytoma 73.7%). Among new HF cases, 28.5% had no RCT-HF RFs and 38.6% had no RCT-CVD RFs. 15.6% had either no RF or only RCT-0 RFs.

CONCLUSION

One in six individuals with HF have no recorded RFs or RFs without trials. We provide a systematic map of primary preventive opportunities across a wide range of RFs for HF, demonstrating a high burden of co-occurrence and the need for trials tackling multiple RFs.

Restoration of Default Blood Monocyte-Derived Macrophage Polarization With Adalimumab But Not Etanercept in Rheumatoid Arthritis

Introduction

We previously reported a specific defect of rheumatoid arthritis (RA) monocyte polarization to anti-inflammatory M2-like macrophages related to increased miR-155 expression in all RA patients except those receiving adalimumab (ADA). In this longitudinal study, we examined whether different tumor necrosis factor inhibitors were able to restore monocyte polarization to M2-like macrophages and their effect on the transcriptomic signature.

Methods

M2-like polarization induced by human serum AB was studied in 7 healthy donors and 20 RA patients included in the ABIRA cohort before and 3 months after starting ADA or etanercept (ETA). The differential gene expression of M2- and M1-related transcripts was studied in macrophage-derived monocytes after differentiation.

Results

At baseline, RA monocytes showed a defect of polarization to M2-like macrophages as compared with healthy donor monocytes, which was negatively correlated with disease activity. M2-like polarization from circulating monocytes was restored only with ADA and not ETA treatment. The transcriptomic signature demonstrated downregulation of M2-related transcripts and upregulation of M1-related transcripts in active RA. In patients receiving ADA, the transcriptomic signature of M2-related transcripts was restored.

Conclusion

This longitudinal study demonstrates that ADA but not ETA is able to restore the M2-like polarization of monocytes that is defective in RA.

Unmet support needs relating to hypoglycaemia among adults with type 1 diabetes: Results of a multi-country web-based qualitative study

OBJECTIVE

Hypoglycaemic episodes and fear of hypoglycaemia can be burdensome for adults with type 1 diabetes. This study explored support needs relating to hypoglycaemia among adults with type 1 diabetes living in Denmark, Germany, the Netherlands and the United Kingdom.

RESEARCH DESIGN AND METHODS

Respondents participated in a web-based qualitative study involving four open-ended questions that asked what they wished other people understood about hypoglycaemia and what other people could do differently to support them with hypoglycaemia. Responses were analyzed using reflexive thematic analysis.

RESULTS

Participants were 219 adults with type 1 diabetes (mean ± SD age 39 ± 13 years; mean ± SD diabetes duration 20 ± 14 years). They described unmet needs relating to: (1) Clinical support, involving access to new diabetes technologies, training on hypoglycaemia prevention, personalised care and psychological support; (2) Practical support, involving family and friends better supporting them with hypoglycaemia management and prevention; (3) Education for other people, involving others becoming more informed about hypoglycaemia; and (4) An appreciation of the burden, involving others recognizing the experience and impact of episodes, and the burden of living with the risk of hypoglycaemia.

CONCLUSIONS

Adults with type 1 diabetes report several unmet support needs relating to hypoglycaemia. Service delivery should be person-centred and prioritise the individual's support needs. Clinical conversations are needed to identify the individual's support needs and develop tailored support plans. People with diabetes and their family members should be offered hypoglycaemia-specific education and training.

In vitro beta-cell killing models using immune cells and human pluripotent stem cell-derived islets: Challenges and opportunities

Type 1 diabetes (T1D) is a disease of both autoimmunity and β-cells. The β-cells play an active role in their own demise by mounting defense mechanisms that are insufficient at best, and that can become even deleterious in the long term. This complex crosstalk is important to understanding the physiological defense mechanisms at play in healthy conditions, their alterations in the T1D setting, and therapeutic agents that may boost such mechanisms. Robust protocols to develop stem-cell-derived islets (SC-islets) from human pluripotent stem cells (hPSCs), and islet-reactive cytotoxic CD8⁺ T-cells from peripheral blood mononuclear cells offer unprecedented opportunities to study this crosstalk. Challenges to develop in vitro β-cell killing models include the cluster morphology of SC-islets, the relatively weak cytotoxicity of most autoimmune T-cells and the variable behavior of in vitro expanded CD8⁺ T-cells. These challenges may however be highly rewarding in light of the opportunities offered by such models. Herein, we discuss these opportunities including: the β-cell/immune crosstalk in an islet microenvironment; the features that make β-cells more sensitive to autoimmunity; therapeutic agents that may modulate β-cell vulnerability; and the possibility to perform analyses in an autologous setting, i.e., by generating T-cell effectors and SC-islets from the same donor.

Applying the ESC 2016, H2 FPEF, and HFA-PEFF diagnostic algorithms for heart failure with preserved ejection fraction to the general population

AIMS

Heart failure with preserved ejection fraction (HFpEF) is common in patients presenting with dyspnoea. Recently, clinical tools were developed to facilitate the diagnosis of HFpEF. Here, we apply the European Society of Cardiology (ESC) 2016 heart failure guidelines and the H2 FPEF and HFA-PEFF scores to a middle-aged sample of the general population and compared the different groups with each other.

METHODS AND RESULTS

This study included the first 10 000 participants of the population-based Hamburg City Health Study. A total of 5613 subjects, aged 62 ± 8.7 years (51.1% women), qualified for the analysis. Unexplained dyspnoea was present in 407 (7.3%) subjects. In those, the estimated prevalence of HFpEF was 20.4% (ESC 2016), 12.3% (H2 FPEF), and 7.6% (HFA-PEFF). The majority of subjects was classified as HFpEF not excludable according to the HFA-PEFF (57.7%) and H2 FPEF (59.2%) scores. For all algorithms, subjects diagnosed with HFpEF showed elevated age and body mass index as well as a higher prevalence of atrial fibrillation, diabetes, and arterial hypertension compared with those without HFpEF or HFpEF not excludable. The distribution of those co-morbidities and risk factors varied between the differently diagnosed HFpEF groups with the highest burden in the HFpEF group defined by the H2 FPEF score. The overlap of subjects diagnosed with HFpEF according to the different algorithms was very limited.

CONCLUSIONS

Unexplained dyspnoea is common in the middle-aged general population. The ESC 2016 algorithm and the H2 FPEF and HFA-PEFF scores detect different, discordant subpopulations of probands with breathlessness. Further classification of the HFpEF syndrome is desirable.

Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.