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Background: Obesity is a major risk factor for kidney dysfunction, with cellular senescence and senescence-associated secretory phenotype (SASP) activation contributing to early kidney injury. Urinary extracellular vesicles (uEVs) provide a non-invasive approach to assess cellular stress. We hypothesised that obesity induces podocyte senescence detectable by podocyte-derived uEVs.

Methods: We recruited 28 obese (OB) individuals and 16 healthy volunteers (HV). Of these, uEVs from 21 OB (OB-1) and 10 HV (HV-1) were analysed for tubular-derived (urat1⁺, uromodulin⁺, or prominin⁺) or podocyte-specific (PODXL⁺) uEVs bearing markers of senescence (p16) and SASP (MCP-1) using flow cytometry. Their correlations with metabolic and urinary renal injury markers (kidney injury molecule-1 [KIM-1], neutrophil gelatinase-associated lipocalin [NGAL], tumour necrosis factor-alpha [TNF-α], proteinuria) were assessed. Furthermore, kidney biopsies obtained from comparable OB-2 (n = 7) and HV-2 (n = 6) subjects were examined for tissue podocyte senescence using immunofluorescence. Podocytes were also counted in a subset of HV (n = 5) and OB (n = 4) urine samples.

Findings: OB had elevated body mass index (BMI) but preserved kidney function. OB-1 exhibited significantly elevated P16⁺MCP-1⁺PODXL⁺ uEVs fractions compared to HV-1, which correlated with metabolic dysfunction (BMI, insulin resistance) and renal injury markers. Tubular-derived uEVs showed no differences between the groups. Kidney biopsies confirmed increased podocyte senescence (P16⁺ PODXL⁺ immunoreactivity) in OB-2 vs. HV-2, and numbers of urinary podocytes increased in OB.

Interpretation: Human obesity induces in persons with normal kidney function podocyte senescence, which is detectable non-invasively by uEVs.

Fundings: This study was partly supported by NIH grant numbers: DK120292, DK122734, HL158691, AG062104 (all LOL), and AG076537 (LJH). KDIGO provided support to Dr. Kukla to the 2024 Obesity and Chronic Kidney Disease Controversies Conference.

Background: Early detection is a major clinical challenge in pancreatic cancer due to its nonspecific symptoms and frequent late-stage diagnosis. While predictive models using electronic health record (EHR) data show promise, their real world implementation remains underexplored. We previously developed a random survival forest (RSF) model to estimate pancreatic cancer risk using structured EHR data from 2007 to 2017. This study evaluates practical considerations for deploying such a model in a prospective clinical context.

Methods: We refit the original RSF model using a cohort from 2018 to 2019 and evaluated its performance on a 2020 cohort. We assessed how model refitting and different imputation strategies influenced predictive performance and compared execution times to evaluate computational feasibility. Three imputation strategies were tested: sub-model estimation (SME), stacked multiple imputation (SMI), and imputation via fixed chained equations (IFCE). To simulate real time use, we applied the model to 53 sequential weekly patient batches (with average batch size 190,206).

Findings: Refitting improved discrimination and calibration. Without refitting, the C-index ranged from 0.69 to 0.84 depending on imputation method; with refitting, it ranged from 0.79 to 0.83. The IFCE method achieved the best balance between performance (C-index: 0.83 with refit) and runtime (19.54 min). SME had the highest C-index (0.85) and sensitivity (18.41%) but required construction of multiple sub-models. SMI was the most computationally intensive, limiting its scalability in routine use. Calibration improved markedly with refitting. Model performance differed across racial and ethnic groups; calibration was poorest among Black patients but improved with SMI. Execution time varied substantially across methods.

Interpretation: Model refitting and appropriate handling of missing data improve the real world performance of predictive models. Among imputation approaches, IFCE offers the best trade-off between computational efficiency and predictive accuracy. These findings provide practical, implementation-focused guidance for deploying risk prediction models in prospective clinical settings.

Funding: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA230442.

Background: Orthohantaviruses (hantaviruses) are emerging rodent-borne pathogens that can cause severe human disease. They are present on multiple continents and are responsible for thousands of human cases per year. Despite this, no licenced therapeutics are available, vaccines for most strains are lacking, and the immunological response to infection is poorly characterised. This study aimed to analyse the humoral immune response to Puumala virus (PUUV) infection to inform future studies focussing on the production of therapeutic monoclonal antibodies and vaccination strategies.

Methods: Serum was obtained from a cohort of 24 patients hospitalised with PUUV infection at four time points, covering the early acute, late acute, early convalescent, and late convalescent stages of the disease. The humoral immune responses at each time point were quantified, and cross-binding, cross-neutralising antibody responses were investigated. Serum cytokine levels were also interrogated, and expression was correlated with humoral outputs.

Findings: PUUV infection elicited a robust anti-PUUV neutralising antibody response. However, cross-reactive antibodies that were capable of binding diverse hantaviruses were also induced in late convalescence. Modulations in the abundance of IgG subclasses were evident following infection, with significant differences present months after infection.

Interpretation: This study demonstrates that broadly reactive anti-hantavirus antibodies are produced in response to Old-World hantavirus infection, but predominantly months after recovery. As this is concomitant with changes in IgG subtypes, our results suggest that PUUV infection promotes prolonged class-switching and somatic hypermutation, favouring conserved epitopes long after exposure.

Funding: Work at Mount Sinai was supported by Institutional Funds, work at the Medical University of Vienna was supported by Institutional Funds. The study was supported in part by the Styrian government, Austria (project no. ABT12-106729/2022-13) and the Austrian Science Fund (FWF) (number J 4737-B).

Background: Biallelic loss-of-function ZNF808 variants were recently identified as a cause of pancreatic agenesis characterised by insulin-treated permanent neonatal diabetes (PNDM), low birthweight and exocrine pancreatic insufficiency.

Methods: We investigated the phenotypic diversity caused by biallelic loss-of-function ZNF808 variants by screening a cohort of 4699 individuals with genetically undiagnosed monogenic diabetes: 335 with neonatal diabetes (NDM, diagnosed <6 months), 194 with infancy-onset diabetes (diagnosed 6-12 months) and 4170 diagnosed with diabetes between 1 and 60 years of age.

Findings: Through a combination of genome and targeted next-generation-sequencing, we identified 17 previously unreported individuals with biallelic loss-of-function ZNF808 variants, bringing the total number of cases identified in the Exeter cohort to 31 when combined with previously described cases. 30/31 individuals were born to related parents. Clinically, 19 had PNDM, whilst the remaining 12 had other diabetes phenotypes: 5 with infancy-onset diabetes, 4 with transient diabetes and 3 with diabetes diagnosed aged 10, 14 and 23 years. Individuals with ZNF808-diabetes did not always require insulin treatment, with sulphonylurea treatment reported in 3 individuals. Exocrine pancreatic function was not consistently affected across the cohort, with no clinical features of exocrine insufficiency reported in 17 individuals and normal exocrine function biochemically confirmed in one further individual.

Interpretation: Biallelic loss of ZNF808 results in a variable pancreatic phenotype ranging from pancreatic agenesis to adult-onset diabetes without exocrine insufficiency. ZNF808 gene testing should be considered in individuals with diabetes diagnosed after the neonatal period, especially if born to related parents.

Funding: Wellcome Trust, Diabetes UK.

Background: Sepsis is common and deadly, and subtypes are proposed to guide precision treatment. However, little is known about the uncertainty in subtype classification, and its implications for trajectory and treatment response.

Methods: In multiple electronic health record and trial data of adults with sepsis, we assigned patients clinical sepsis subtypes (α, β, γ, or δ-type), and measured uncertainty by defining core (≥90%) and margin (<90%) strata for each subtype according to model-derived membership probabilities. In multivariable logistic regression models, we determined the association between subtype, core/margin strata, and two outcomes, i.) change in subtype over 48 h and ii.) 365-day mortality in the ProCESS randomised trial.

Findings: We included 35,691 adult patients (mean age 68 [SD 16] years; 51% male, 85% White, 5.7% in-hospital mortality) with community-acquired sepsis according to Sepsis-3. Most patients changed clinical sepsis subtype during the 48 h after presentation (82%) regardless of initial subtype. The majority of patients were in the margin stratum of the subtype (α-type: 70%, β-type: 66%, γ-type: 64%), except for those in δ-type (18% margin strata). The odds of subtype change over 48 h was increased in the margin strata (interaction p = 0.023), where, for example, patients with the margin delta subtype had significantly higher odds than patients with alpha core (ref) subtype (odds ratio, 7.13; 95% confidence interval [CI], 5.16-9.85). For risk-adjusted 365-day mortality in the ProCESS trial, the effect of randomised treatment was modified by the subtype margin strata (interaction p = 0.026).

Interpretation: In patients with community sepsis, clinical subtypes are dynamic. Patients on the subtype margin are more likely to change groups, and uncertainty of subtype classification modified treatment effects.

Funding: National Institutes of Health, National Institute of General Medical Sciences (R35GM119519).

Alzheimer's disease-related dementia (ADRD) is a progressive neurodegenerative condition characterised by cognitive decline and overlapping pathological features. Despite advances in diagnostic tools and therapies, challenges persist due to limited efficacy, high costs, and the complexity of ADRD pathophysiology. Evidence suggests that ADRD arises from a lifelong interplay of genetic, lifestyle, and environmental factors, with recent findings indicating potential neurodevelopmental origins. Proteins implicated in neurodegeneration, such as amyloid and tau, may play critical roles in early nervous system development, whereas disruptions during critical periods, such as adolescence, may increase later-life susceptibility to ADRD. The global prevalence of ADRD is projected to reach 153 million by 2050, emphasising the urgent need for prevention strategies in addition to therapeutic interventions. Reframing ADRD as a neurodevelopmental condition with a delayed onset may provide alternative insights into its aetiology, paving the way for alternative innovative therapeutic and preventive approaches.

Background: Accurate monitoring of antimicrobial consumption is essential for developing effective stewardship interventions. Hospitals are mandated to report antibiotic treatment duration using the CDC's Standardized Antimicrobial Administration Ratio (SAAR). We aimed to create a metric for measuring antimicrobial spectrum to complement SAAR, benchmarked against local and individual resistance.

Methods: This retrospective cohort study utilised data from nine acute care hospitals within BJC Healthcare from January 2018 to December 2023. Adult patients meeting CDC sepsis event criteria were included, focussing on infections caused by Gram-negative bacilli (GNB). Data on patient characteristics, microbiology results, treatments, and timing were collected. We defined the antibiotic effective spectrum (AES) as the ratio of susceptible GNB to all GNB cultured. Mathematical optimisation identified the optimal antibiotic as the antibiotic with the narrowest effective spectrum active against the isolated GNB. We calculated the empirical (before culture results are available) and directed Optimal Spectrum Antibiotic Ratio (OSAR) as the ratio between the AES chosen clinically to the optimal AES, reported it for each hospital yearly, and compared it to SAAR and the Antibiotic Spectrum Index (ASI). Sensitivity analyses focused on empirical undertreatment (OSAR <1, where the empirical choice did not cover the cultured GNB).

Findings: We included 10,277 GNB cultured from clinical specimens in 7997 distinct patients. The AES ranged from 0.15 for ampicillin to 0.94 for amikacin. Empirical OSAR varied between 1.08 (95% CI 1.05-1.10) and 1.89 (95% CI 1.51-2.28), with undertreatment present in 1396 (13.6%) of cases overall and wide variations across hospitals. Directed OSAR was lower, ranging between 0.74 (95% CI 0.73-0.75) and 1.45 (95% CI 1.41-1.49). OSAR, SAAR and ASI had different trends across hospitals over the six study years.

Interpretation: The OSAR yielded different conclusions about antibiotic utilisation, complementing duration-based measures like SAAR. It determines the appropriateness of antibiotic spectrum based on local and individual resistance.

Funding: The project was funded by the CDC (5U54CK000609).

Super-resolution ultrasound, with its ability to achieve sub-diffraction resolution and directly track microvascular flow velocity in vivo, offers a level of vascular information inaccessible previously. To fully realise its clinical value, quantitative vascular markers have been explored. In this review, we explore the quantitative super-resolution markers that have been reported, with a focus on occasions where markers have been applied in a clinical or pre-clinical setting, comparing healthy and diseased cases to test the validity and usefulness of these markers. We define all the used markers from structural markers such as vessel density to velocity metrics such as flow rate, we then provide a summary showing what has been attempted and what has been found successful. We hope that this review can act as a guide both as to the range of markers that currently exist as well as indications as to what markers show potential for each clinical application.

Background: Pallidal deep brain stimulation (DBS) has remarkable effects in patients with cervical dystonia. Yet, its neurophysiological mechanisms are not fully resolved to date. Converging evidence suggests that pallidal DBS modulates sensorimotor and cerebellar network activity in dystonia, possibly by disrupting pathologically enhanced low-frequency oscillations in the basal ganglia. Still, anatomical and electrophysiological findings have rarely been linked, and it is unclear whether oscillatory changes occur in the same network identified in neuroimaging studies.

Methods: In this cross-sectional study, we investigate the effects of pallidal DBS in patients with cervical dystonia using magnetoencephalography recordings on and off stimulation. We correlated DBS outcomes to the whole-cortex pattern of DBS-induced power changes in each cortical vertex.

Findings: This analysis revealed a distinct low-frequency electrophysiological signature that accounted for significant amounts of variance in DBS improvements across the cohort. The signature was characterised by negative peaks within the supplementary motor area and the motor cortex as well as positive peaks in prefrontal and cerebellar areas.

Interpretation: Our study sheds light on the cortical and cerebellar effects of pallidal DBS on a whole-cortex level and puts emphasis on low-frequency power modulation as a mechanism of effective stimulation beyond the basal ganglia in patients with cervical dystonia. Our findings might inform DBS programming and targeting as well as non-invasive stimulation strategies in the future.

Funding: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-Project-ID 424778381-TRR 295.