Clinical and biological landscape of constitutional mismatch-repair deficiency syndrome: an International Replication Repair Deficiency Consortium cohort study.

BACKGROUND: Constitutional mismatch repair deficiency (CMMRD) syndrome is a rare and aggressive cancer predisposition syndrome. Because a scarcity of data on this condition contributes to management challenges and poor outcomes, we aimed to describe the clinical spectrum, cancer biology, and impact of genetics on patient survival in CMMRD. METHODS: In this cohort study, we collected cross-sectional and longitudinal data on all patients with CMMRD, with no age limits, registered with the International Replication Repair Deficiency Consortium (IRRDC) across more than 50 countries. Clinical data were extracted from the IRRDC database, medical records, and physician-completed case record forms. The primary objective was to describe the clinical features, cancer spectrum, and biology of the condition. Secondary objectives included estimations of cancer incidence and of the impact of the specific mismatch-repair gene and genotype on cancer onset and survival, including after cancer surveillance and immunotherapy interventions. FINDINGS: We analysed data from 201 patients (103 males, 98 females) enrolled between June 5, 2007 and Sept 9, 2022. Median age at diagnosis of CMMRD or a related cancer was 8·9 years (IQR 5·9-12·6), and median follow-up from diagnosis was 7·2 years (3·6-14·8). Endogamy among minorities and closed communities contributed to high homozygosity within countries with low consanguinity. Frequent dermatological manifestations (117 [93%] of 126 patients with complete data) led to a clinical overlap with neurofibromatosis type 1 (35 [28%] of 126). 339 cancers were reported in 194 (97%) of 201 patients. The cumulative cancer incidence by age 18 years was 90% (95% CI 80-99). Median time between cancer diagnoses for patients with more than one cancer was 1·9 years (IQR 0·8-3·9). Neoplasms developed in 15 organs and included early-onset adult cancers. CNS tumours were the most frequent (173 [51%] cancers), followed by gastrointestinal (75 [22%]), haematological (61 [18%]), and other cancer types (30 [9%]). Patients with CNS tumours had the poorest overall survival rates (39% [95% CI 30-52] at 10 years from diagnosis; log-rank p<0·0001 across four cancer types), followed by those with haematological cancers (67% [55-82]), gastrointestinal cancers (89% [81-97]), and other solid tumours (96% [88-100]). All cancers showed high mutation and microsatellite indel burdens, and pathognomonic mutational signatures. MLH1 or MSH2 variants caused earlier cancer onset than PMS2 or MSH6 variants, and inferior survival (overall survival at age 15 years 63% [95% CI 55-73] for PMS2, 49% [35-68] for MSH6, 19% [6-66] for MLH1, and 0% for MSH2; p<0·0001). Frameshift or truncating variants within the same gene caused earlier cancers and inferior outcomes compared with missense variants (p<0·0001). The greater deleterious effects of MLH1 and MSH2 variants as compared with PMS2 and MSH6 variants persisted despite overall improvements in survival after surveillance or immune checkpoint inhibitor interventions. INTERPRETATION: The very high cancer burden and unique genomic landscape of CMMRD highlight the benefit of comprehensive assays in timely diagnosis and precision approaches toward surveillance and immunotherapy. These data will guide the clinical management of children and patients who survive into adulthood with CMMRD. FUNDING: The Canadian Institutes for Health Research, Stand Up to Cancer, Children's Oncology Group National Cancer Institute Community Oncology Research Program, Canadian Cancer Society, Brain Canada, The V Foundation for Cancer Research, BioCanRx, Harry and Agnieszka Hall, Meagan's Walk, BRAINchild Canada, The LivWise Foundation, St Baldrick Foundation, Hold'em for Life, and Garron Family Cancer Center.

Safety and effectiveness of SGLT2 inhibitors in a UK population with type 2 diabetes and aged over 70 years: an instrumental variable approach.

AIMS/HYPOTHESIS: Older adults are under-represented in trials, meaning the benefits and risks of glucose-lowering agents in this age group are unclear. The aim of this study was to assess the safety and effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in people with type 2 diabetes aged over 70 years using causal analysis. METHODS: Hospital-linked UK primary care data (Clinical Practice Research Datalink, 2013-2020) were used to compare adverse events and effectiveness in individuals initiating SGLT2i compared with dipeptidyl peptidase-4 inhibitors (DPP4i). Analysis was age-stratified: <70 years (SGLT2i n=66,810, DPP4i n=76,172), ≥70 years (SGLT2i n=10,419, DPP4i n=33,434). Outcomes were assessed using the instrumental variable causal inference method and prescriber preference as the instrument. RESULTS: Risk of diabetic ketoacidosis was increased with SGLT2i in those aged ≥70 (incidence rate ratio compared with DPP4i: 3.82 [95% CI 1.12, 13.03]), but not in those aged <70 (1.12 [0.41, 3.04]). However, incidence rates with SGLT2i in those ≥70 was low (29.6 [29.5, 29.7]) per 10,000 person-years. SGLT2i were associated with similarly increased risk of genital infection in both age groups (incidence rate ratio in those <70: 2.27 [2.03, 2.53]; ≥70: 2.16 [1.77, 2.63]). There was no evidence of an increased risk of volume depletion, poor micturition control, urinary frequency, falls or amputation with SGLT2i in either age group. In those ≥70, HbA1c reduction was similar between SGLT2i and DPP4i (-0.3 mmol/mol [-1.6, 1.1], -0.02% [0.1, 0.1]), but in those <70, SGLT2i were more effective (-4 mmol/mol [4.8, -3.1], -0.4% [-0.4, -0.3]). CONCLUSIONS/INTERPRETATION: Causal analysis suggests SGLT2i are effective in adults aged ≥70 years, but increase risk for genital infections and diabetic ketoacidosis. Our study extends RCT evidence to older adults with type 2 diabetes.

Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.

AIMS/HYPOTHESIS: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA). METHODS: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA1c) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events. RESULTS: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications. CONCLUSIONS/INTERPRETATION: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries.

Dirichlet process mixture models to impute missing predictor data in counterfactual prediction models: an application to predict optimal type 2 diabetes therapy.

BACKGROUND: The handling of missing data is a challenge for inference and regression modelling. A particular challenge is dealing with missing predictor information, particularly when trying to build and make predictions from models for use in clinical practice. METHODS: We utilise a flexible Bayesian approach for handling missing predictor information in regression models. This provides practitioners with full posterior predictive distributions for both the missing predictor information (conditional on the observed predictors) and the outcome-of-interest. We apply this approach to a previously proposed counterfactual treatment selection model for type 2 diabetes second-line therapies. Our approach combines a regression model and a Dirichlet process mixture model (DPMM), where the former defines the treatment selection model, and the latter provides a flexible way to model the joint distribution of the predictors. RESULTS: We show that DPMMs can model complex relationships between predictor variables and can provide powerful means of fitting models to incomplete data (under missing-completely-at-random and missing-at-random assumptions). This framework ensures that the posterior distribution for the parameters and the conditional average treatment effect estimates automatically reflect the additional uncertainties associated with missing data due to the hierarchical model structure. We also demonstrate that in the presence of multiple missing predictors, the DPMM model can be used to explore which variable(s), if collected, could provide the most additional information about the likely outcome. CONCLUSIONS: When developing clinical prediction models, DPMMs offer a flexible way to model complex covariate structures and handle missing predictor information. DPMM-based counterfactual prediction models can also provide additional information to support clinical decision-making, including allowing predictions with appropriate uncertainty to be made for individuals with incomplete predictor data.

The impact of population-level HbA1c screening on reducing diabetes diagnostic delay in middle-aged adults: a UK Biobank analysis.

AIMS/HYPOTHESIS: Screening programmes can detect cases of undiagnosed diabetes earlier than symptomatic or incidental diagnosis. However, the improvement in time to diagnosis achieved by screening programmes compared with routine clinical care is unclear. We aimed to use the UK Biobank population-based study to provide the first population-based estimate of the reduction in time to diabetes diagnosis that could be achieved by HbA1c-based screening in middle-aged adults. METHODS: We studied UK Biobank participants aged 40-70 years with HbA1c measured at enrolment (but not fed back to participants/clinicians) and linked primary and secondary healthcare data (n=179,923) and identified those with a pre-existing diabetes diagnosis (n=13,077, 7.3%). Among the remaining participants (n=166,846) without a diabetes diagnosis, we used an elevated enrolment HbA1c level (≥48 mmol/mol [≥6.5%]) to identify those with undiagnosed diabetes. For this group, we used Kaplan-Meier analysis to assess the time between enrolment HbA1c measurement and subsequent clinical diabetes diagnosis up to 10 years, and Cox regression to identify clinical factors associated with delayed diabetes diagnosis. RESULTS: In total, 1.0% (1703/166,846) of participants without a diabetes diagnosis had undiagnosed diabetes based on calibrated HbA1c levels at UK Biobank enrolment, with a median HbA1c level of 51.3 mmol/mol (IQR 49.1-57.2) (6.8% [6.6-7.4]). These participants represented an additional 13.0% of diabetes cases in the study population relative to the 13,077 participants with a diabetes diagnosis. The median time to clinical diagnosis for those with undiagnosed diabetes was 2.2 years, with a median HbA1c at clinical diagnosis of 58.2 mmol/mol (IQR 51.0-80.0) (7.5% [6.8-9.5]). Female participants with lower HbA1c and BMI measurements at enrolment experienced the longest delay to clinical diagnosis. CONCLUSIONS/INTERPRETATION: Our population-based study shows that HbA1c screening in adults aged 40-70 years can reduce the time to diabetes diagnosis by a median of 2.2 years compared with routine clinical care. The findings support the use of HbA1c screening to reduce the time for which individuals are living with undiagnosed diabetes.

E-cigarette aerosols of propylene glycol impair BK channel activity and parameters of mucociliary function.

Propylene glycol (PG) is a common delivery vehicle for nicotine and flavorings in e-cigarette (e-cig) liquids and is largely considered safe for ingestion. However, little is known about its effects as an e-cig aerosol on the airway. Here, we investigated whether pure PG e-cig aerosols in realistic daily amounts impact parameters of mucociliary function and airway inflammation in a large animal model (sheep) in vivo and primary human bronchial epithelial cells (HBECs) in vitro. Five-day exposure of sheep to e-cig aerosols of 100% PG increased mucus concentrations (% mucus solids) of tracheal secretions. PG e-cig aerosols further increased the activity of matrix metalloproteinase-9 (MMP-9) in tracheal secretions. In vitro exposure of HBECs to e-cig aerosols of 100% PG decreased ciliary beating and increased mucus concentrations. PG e-cig aerosols further reduced the activity of large conductance, Ca2+-activated, and voltage-dependent K+ (BK) channels. We show here for the first time that PG can be metabolized to methylglyoxal (MGO) in airway epithelia. PG e-cig aerosols increased levels of MGO and MGO alone reduced BK activity. Patch-clamp experiments suggest that MGO can disrupt the interaction between the major pore-forming BK subunit human Slo1 (hSlo1) and the gamma regulatory subunit LRRC26. PG exposures also caused a significant increase in mRNA expression levels of MMP9 and interleukin 1 beta (IL1B). Taken together, these data show that PG e-cig aerosols cause mucus hyperconcentration in sheep in vivo and HBECs in vitro, likely by disrupting the function of BK channels important for airway hydration.

Recent UK type 2 diabetes treatment guidance represents a near whole population indication for SGLT2-inhibitor therapy.

Recent type 2 diabetes guidance from the UK's National Institute for Health and Care Excellence (NICE) proposes offering SGLT2-inhibitor therapy to people with established atherosclerotic cardiovascular disease (ASCVD) or heart failure, and considering SGLT2-inhibitor therapy for those at high-risk of cardiovascular disease defined as a 10-year cardiovascular risk of > 10% using the QRISK2 algorithm. We used a contemporary population-representative UK cohort of people with type 2 diabetes to assess the implications of this guidance. 93.1% of people currently on anti-hyperglycaemic treatment are now recommended or considered for SGLT2-inhibitor therapy under the new guidance, with the majority (59.6%) eligible on the basis of QRISK2 rather than established ASCVD or heart failure (33.6%). Applying these results to the approximately 2.20 million people in England currently on anti-hyperglycaemic medication suggests 1.75 million people will now be considered for additional SGLT2-inhibitor therapy, taking the total cost of SGLT2-inhibitor therapy in England to over £1 billion per year. Given that older people, those of non-white ethnic groups, and those at lower cardiovascular disease risk were underrepresented in the clinical trials which were used to inform this guidance, careful evaluation of the impact and safety of increased SGLT2-inhibitor prescribing across different populations is urgently required. Evidence of benefit should be weighed against the major cost implications for the UK National Health Service.

Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine.

OBJECTIVE: Precision medicine requires reliable identification of variation in patient-level outcomes with different available treatments, often termed treatment effect heterogeneity. We aimed to evaluate the comparative utility of individualized treatment selection strategies based on predicted individual-level treatment effects from a causal forest machine learning algorithm and a penalized regression model. METHODS: Cohort study characterizing individual-level glucose-lowering response (6 month reduction in HbA1c) in people with type 2 diabetes initiating SGLT2-inhibitor or DPP4-inhibitor therapy. Model development set comprised 1,428 participants in the CANTATA-D and CANTATA-D2 randomised clinical trials of SGLT2-inhibitors versus DPP4-inhibitors. For external validation, calibration of observed versus predicted differences in HbA1c in patient strata defined by size of predicted HbA1c benefit was evaluated in 18,741 patients in UK primary care (Clinical Practice Research Datalink). RESULTS: Heterogeneity in treatment effects was detected in clinical trial participants with both approaches (proportion predicted to have a benefit on SGLT2-inhibitor therapy over DPP4-inhibitor therapy: causal forest: 98.6%; penalized regression: 81.7%). In validation, calibration was good with penalized regression but sub-optimal with causal forest. A strata with an HbA1c benefit > 10 mmol/mol with SGLT2-inhibitors (3.7% of patients, observed benefit 11.0 mmol/mol [95%CI 8.0-14.0]) was identified using penalized regression but not causal forest, and a much larger strata with an HbA1c benefit 5-10 mmol with SGLT2-inhibitors was identified with penalized regression (regression: 20.9% of patients, observed benefit 7.8 mmol/mol (95%CI 6.7-8.9); causal forest 11.6%, observed benefit 8.7 mmol/mol (95%CI 7.4-10.1). CONCLUSIONS: Consistent with recent results for outcome prediction with clinical data, when evaluating treatment effect heterogeneity researchers should not rely on causal forest or other similar machine learning algorithms alone, and must compare outputs with standard regression, which in this evaluation was superior.

Atopic dermatitis and risk of autoimmune conditions: Population-based cohort study.

BACKGROUND: Atopic dermatitis (AD) is associated with immune dysregulation, but epidemiologic data on the pattern of autoimmune comorbidity in people with AD are limited. OBJECTIVE: We sought to determine the risk of autoimmune conditions in people newly diagnosed with AD. METHODS: Retrospective cohort analysis (January 2009 to December 2018), using the UK-based Oxford-Royal College of General Practitioners Research and Surveillance Centre primary care database. We compared baseline prevalence and incidence after diagnosis of autoimmune conditions in 173,709 children and adults with new-onset AD and 694,836 age-, sex-, and general practitioner practice-matched controls. Outcomes were a composite of any autoimmune condition (Crohn disease, ulcerative colitis, celiac disease, pernicious anemia, type 1 diabetes, autoimmune hypothyroidism, Graves disease, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus, Sjögren syndrome, vitiligo, alopecia areata, and multiple sclerosis) and each individual autoimmune condition. RESULTS: Preexisting autoimmune conditions were more common in people diagnosed with AD compared to controls (composite 5.8% vs 4.3%). Excluding people with preexisting autoimmune disease, there was an association between AD and incidence of new-onset autoimmune disease (composite adjusted hazard ratio [aHR] 1.28; 95% confidence interval [CI] 1.23-1.34). Risk was highest for more severe AD (aHR 1.99; 95% CI 1.77-2.23) than moderate AD (aHR 1.33; 95% CI 1.19-1.49) or mild AD (aHR 1.22; 95% CI 1.16-1.28). People with AD were at significantly increased risk of developing psoriatic arthritis, Sjögren syndrome, Crohn disease, vitiligo, alopecia areata, pernicious anemia, ulcerative colitis, rheumatoid arthritis, and hypothyroidism (aHR range 1.17-2.06), but not other autoimmune conditions. CONCLUSION: People with AD have an increased risk of multiple autoimmune conditions, especially those with more severe AD.

Nebulized Menthol Impairs Mucociliary Clearance via TRPM8 and MUC5AC/MUC5B in Primary Airway Epithelial Cells.

Flavorings enhance the palatability of e-cigarettes (e-cigs), with menthol remaining a popular choice among e-cig users. Menthol flavor remains one of the only flavors approved by the United States FDA for use in commercially available, pod-based e-cigs. However, the safety of inhaled menthol at the high concentrations used in e-cigs remains unclear. Here, we tested the effects of menthol on parameters of mucociliary clearance (MCC) in air-liquid interface (ALI) cultures of primary airway epithelial cells. ALI cultures treated with basolateral menthol (1 mM) showed a significant decrease in ciliary beat frequency (CBF) and airway surface liquid (ASL) volumes after 24 h. Menthol nebulized onto the surface of ALI cultures similarly reduced CBF and increased mucus concentrations, resulting in decreased rates of mucociliary transport. Nebulized menthol further increased the expression of mucin 5AC (MUC5AC) and mRNA expression of the inflammatory cytokines IL1B and TNFA. Menthol activated TRPM8, and the effects of menthol on MCC and inflammation could be blocked by a specific TRPM8 antagonist. These data provide further evidence that menthol at the concentrations used in e-cigs could cause harm to the airways.

A Review of Current Trends on Polyvinyl Alcohol (PVA)-Based Solid Polymer Electrolytes.

Presently, the rising concerns about the fossil fuel crisis and ecological deterioration have greatly affected the world economy and hence have attracted attention to the utilization of renewable energies. Among the renewable energy being developed, supercapacitors hold great promise in broad applications such as electric vehicles. Presently, the main challenge facing supercapacitors is the amount of energy stored. This, however, does not satisfy the increasing demand for higher energy storage devices, and therefore, intensive research is being undertaken to overcome the challenges of low energy density. The purpose of this review is to report on solid polymer electrolytes (SPEs) based on polyvinyl alcohol (PVA). The review discussed the PVA as a host polymer in SPEs followed by a discussion on the influence of conducting salts. The formation of SPEs as well as the ion transport mechanism in PVA SPEs were discussed. The application and development of PVA-based polymer electrolytes on supercapacitors and other energy storage devices were elucidated. The fundamentals of electrochemical characterization for analyzing the mechanism of supercapacitor applications, such as EIS, LSV and dielectric constant, are highlighted. Similarly, thermodynamic transport models of ions and their mechanism about temperature based on Arrhenius and Vogel-Tammann-Fulcher (VTF) are analyzed. Methods for enhancing the electrochemical performance of PVA-based SPEs were reported. Likely challenges facing the current electrolytes are well discussed. Finally, research directions to overcome the present challenges in producing SPEs are proposed. Therefore, this review is expected to be source material for other researchers concerned with the development of PVA-based SPE material.

Insight into the Effect of Glycerol on Dielectric Relaxation and Transport Properties of Potassium-Ion-Conducting Solid Biopolymer Electrolytes for Application in Solid-State Electrochemical Double-Layer Capacitor.

The increased interest in the transition from liquid to solid polymer electrolytes (SPEs) has driven enormous research in the area polymer electrolyte technology. Solid biopolymer electrolytes (SBEs) are a special class of SPEs that are obtained from natural polymers. Recently, SBEs have been generating much attention because they are simple, inexpensive, and environmentally friendly. In this work, SBEs based on glycerol-plasticized methylcellulose/pectin/potassium phosphate (MC/PC/K3PO4) are investigated for their potential application in an electrochemical double-layer capacitor (EDLC). The structural, electrical, thermal, dielectric, and energy moduli of the SBEs were analyzed via X-ray diffractometry (XRD), Fourier transforms infrared spectroscopy (FTIR), electrochemical impedance spectroscopy (EIS), transference number measurement (TNM), and linear sweep voltammetry (LSV). The plasticizing effect of glycerol in the MC/PC/K3PO4/glycerol system was confirmed by the change in the intensity of the samples' FTIR absorption bands. The broadening of the XRD peaks demonstrates that the amorphous component of SBEs increases with increasing glycerol concentration, while EIS plots demonstrate an increase in ionic conductivity with increasing plasticizer content owing to the formation of charge-transfer complexes and the expansion of amorphous domains in polymer electrolytes (PEs). The sample containing 50% glycerol has a maximal ionic conductivity of about 7.5 × 10-4 scm-1, a broad potential window of 3.99 V, and a cation transference number of 0.959 at room temperature. Using the cyclic voltammetry (CV) test, the EDLC constructed from the sample with the highest conductivity revealed a capacitive characteristic. At 5 mVs-1, a leaf-shaped profile with a specific capacitance of 57.14 Fg-1 was measured based on the CV data.

Priming the self as an agent influences causal, spatial, and temporal events: implications for animacy, cultural differences, and clinical settings.

People intentionally engage in goal-directed actions-i.e., set goals, create plans, and execute volitional control, which are fundamental for our understanding of ourselves, others, and events. In three experiments we created a novel sentence unscrambling task that was used to prime the self-as-agent (i.e., sentences that contain the pronoun "I"), the self-as-patient (i.e., sentences that contain the pronoun "me"), or no prime (i.e., sentences that contain proper names only), and tested whether that priming would influence the interpretation of causal, spatial, and temporal events. Results demonstrated that the self-as-agent primed participants were more likely to attribute causal influence to a kayaker in a river (Study 1), to assign spatial directionality consistent with an agent moving through space (Study 2), and to assign temporal directionality consistent with an agent moving through time (Study 3). Taken together, these three studies demonstrate that situated conceptualizations of the self as an agent can be a springboard for relevant empirical and theoretical contributions to a broad range of ideas and approaches-from theories of agency to embodied cognition, from language systems to metaphoric representation frameworks, with some potentials even in the clinical and mental health field. Along these lines, implications for animacy, cultural differences, and clinical settings are discussed.

The CFTR Amplifier Nesolicaftor Rescues TGF-ß1 Inhibition of Modulator-Corrected F508del CFTR Function.

Highly effective cystic fibrosis transmembrane conductance regulator (CFTR) modulators have led to dramatic improvements in lung function in many people with cystic fibrosis (PwCF). However, the efficacy of CFTR modulators may be hindered by persistent airway inflammation. The cytokine transforming growth factor-beta1 (TGF-ß1) is associated with worse pulmonary disease in PwCF and can diminish modulator efficacy. Thus, strategies to augment the CFTR response to modulators in an inflammatory environment are needed. Here, we tested whether the CFTR amplifier nesolicaftor (or PTI-428) could rescue the effects of TGF-ß1 on CFTR function and ciliary beating in primary human CF bronchial epithelial (CFBE) cells. CFBE cells homozygous for F508del were treated with the combination of elexacaftor/tezacaftor/ivacaftor (ETI) and TGF-ß1 in the presence and absence of nesolicaftor. Nesolicaftor augmented the F508del CFTR response to ETI and reversed TGF-ß1-induced reductions in CFTR conductance by increasing the expression of CFTR mRNA. Nesolicaftor further rescued the reduced ciliary beating and increased expression of the cytokines IL-6 and IL-8 caused by TGF-ß1. Finally, nesolicaftor augmented the F508del CFTR response to ETI in CFBE cells overexpressing miR-145, a negative regulator of CFTR expression. Thus, CFTR amplifiers, but only when used with highly effective modulators, may provide benefit in an inflamed environment.

Effective Removal of Methylene Blue from Simulated Wastewater Using ZnO-Chitosan Nanocomposites: Optimization, Kinetics, and Isotherm Studies.

Successful synthesis of ZnO-chitosan nanocomposites was conducted for the removal of methylene blue from an aqueous medium. Remarkable performance of the nanocomposites was demonstrated for the effective uptake of the dye, thereby achieving 83.77, 93.78 and 97.93 mg g-1 for the chitosan, 5 wt.% ZnO-Chitosan and 10 wt.% ZnO-Chitosan, respectively. The corresponding adsorption efficiency was 88.77, 93.78 and 97.95 for the chitosan, 5 wt.% ZnO-Chitosan and 10 wt.% ZnO-Chitosan, respectively. Upon regeneration, good reusability of the nanocomposites was manifested for the continuous removal of the dye up to six consecutive cycles. The adsorption process was kinetically described by a pseudo-first order model, while the isotherms were best fitted by the Langmuir model.

Effect of ZnO Nanofiller on Structural and Electrochemical Performance Improvement of Solid Polymer Electrolytes Based on Polyvinyl Alcohol-Cellulose Acetate-Potassium Carbonate Composites.

In this study, a solution casting method was used to prepare solid polymer electrolytes (SPEs) based on a polymer blend comprising polyvinyl alcohol (PVA), cellulose acetate (CA), and potassium carbonate (K2CO3) as a conducting salt, and zinc oxide nanoparticles (ZnO-NPs) as a nanofiller. The prepared electrolytes were physicochemically and electrochemically characterized, and their semi-crystalline nature was established using XRD and FESEM. The addition of ZnO to the polymer-salt combination resulted in a substantial increase in ionic conductivity, which was investigated using impedance analysis. The size of the semicircles in the Cole-Cole plots shrank as the amount of nanofiller increased, showing a decrease in bulk resistance that might be ascribed to an increase in ions due to the strong action of the ZnO-NPs. The sample with 10 wt % ZnO-NPs was found to produce the highest ionic conductivity, potential window, and lowest activation energy (Ea) of 3.70 × 10-3 Scm-1, 3.24 V, and 6.08 × 10-4 eV, respectively. The temperature-frequency dependence of conductivity was found to approximately follow the Arrhenius model, which established that the electrolytes in this study are thermally activated. Hence, it can be concluded that, based on the improved conductivity observed, SPEs based on a PVA-CA-K2CO3/ZnO-NPs composite could be applicable in all-solid-state energy storage devices.

DR15-DQ6 remains dominantly protective against type 1 diabetes throughout the first five decades of life.

AIMS/HYPOTHESIS: Among white European children developing type 1 diabetes, the otherwise common HLA haplotype DR15-DQ6 is rare, and highly protective. Adult-onset type 1 diabetes is now known to represent more overall cases than childhood onset, but it is not known whether DR15-DQ6 is protective in older-adult-onset type 1 diabetes. We sought to quantify DR15-DQ6 protection against type 1 diabetes as age of onset increased. METHODS: In two independent cohorts we assessed the proportion of type 1 diabetes cases presenting through the first 50 years of life with DR15-DQ6, compared with population controls. In the After Diabetes Diagnosis Research Support System-2 (ADDRESS-2) cohort (n = 1458) clinician-diagnosed type 1 diabetes was confirmed by positivity for one or more islet-specific autoantibodies. In UK Biobank (n = 2502), we estimated type 1 diabetes incidence rates relative to baseline HLA risk for each HLA group using Poisson regression. Analyses were restricted to white Europeans and were performed in three groups according to age at type 1 diabetes onset: 0-18 years, 19-30 years and 31-50 years. RESULTS: DR15-DQ6 was protective against type 1 diabetes through to age 50 years (OR < 1 for each age group, all p < 0.001). The following ORs for type 1 diabetes, relative to a neutral HLA genotype, were observed in ADDRESS-2: age 5-18 years OR 0.16 (95% CI 0.08, 0.31); age 19-30 years OR 0.10 (0.04, 0.23); and age 31-50 years OR 0.37 (0.21, 0.68). DR15-DQ6 also remained highly protective at all ages in UK Biobank. Without DR15-DQ6, the presence of major type 1 diabetes high-risk haplotype (either DR3-DQ2 or DR4-DQ8) was associated with increased risk of type 1 diabetes. CONCLUSIONS/INTERPRETATION: HLA DR15-DQ6 confers dominant protection from type 1 diabetes across the first five decades of life.

Hyperglycaemia in cystic fibrosis adversely affects BK channel function critical for mucus clearance.

Large-conductance, Ca2+-activated, voltage-dependent K+ (BK) channel function is critical for adequate airway hydration and mucociliary function. In airway epithelia, BK function is regulated by its γ-subunit, leucine-rich repeat-containing protein 26 (LRRC26). Since patients with cystic fibrosis (CF)-related diabetes mellitus (CFRD) have worse lung function outcomes, this study determined the effects of hyperglycaemia on BK function in CF bronchial epithelial (CFBE) cells in vitro and evaluated the correlation between glycaemic excursions and mRNA expression of LRRC26 in the upper airways of CF and CFRD patients.CFBE cells were redifferentiated at the air-liquid interface (ALI) in media containing either 5.5 mM or 12.5 mM glucose. BK activity was measured in an Ussing chamber. Airway surface liquid (ASL) volume was estimated by meniscus scanning and inflammatory marker expression was measured by quantitative real-time PCR and enzyme-linked immunosorbent assay (ELISA). CF patients were assessed by 7 days of continuous glucose monitoring (CGM). LRRC26 mRNA expression was measured by quantitative real-time PCR from nasal cells obtained at the end of glucose monitoring.BK currents were significantly decreased in CFBE cells cultured under high glucose. These cells revealed significantly lower ASL volumes and increased inflammation, including the receptor for advanced glycation endproducts (RAGE), compared to cells cultured in normal glucose. In vivo, nasal cell expression of LRRC26 mRNA was inversely correlated with hyperglycaemic excursions, consistent with the in vitro results.Our findings demonstrate that hyperglycaemia induces inflammation and impairs BK channel function in CFBE cells in vitro These data suggest that declining lung function in CFRD patients may be related to BK channel dysfunction.

Choice of HbA1c threshold for identifying individuals at high risk of type 2 diabetes and implications for diabetes prevention programmes: a cohort study.

BACKGROUND: Type 2 diabetes (T2D) is common and increasing in prevalence. It is possible to prevent or delay T2D using lifestyle intervention programmes. Entry to these programmes is usually determined by a measure of glycaemia in the 'intermediate' range. This paper investigated the relationship between HbA1c and future diabetes risk and determined the impact of varying thresholds to identify those at high risk of developing T2D. METHODS: We studied 4227 participants without diabetes aged ≥ 40 years recruited to the Exeter 10,000 population cohort in South West England. HbA1c was measured at study recruitment with repeat HbA1c available as part of usual care. Absolute risk of developing diabetes within 5 years, defined by HbA1c ≥ 48 mmol/mol (6.5%), according to baseline HbA1c, was assessed by a flexible parametric survival model. RESULTS: The overall absolute 5-year risk (95% CI) of developing T2D in the cohort was 4.2% (3.6, 4.8%). This rose to 7.1% (6.1, 8.2%) in the 56% (n = 2358/4224) of participants classified 'high-risk' with HbA1c ≥ 39 mmol/mol (5.7%; ADA criteria). Under IEC criteria, HbA1c ≥ 42 mmol/mol (6.0%), 22% (n = 929/4277) of the cohort was classified high-risk with 5-year risk 14.9% (12.6, 17.2%). Those with the highest HbA1c values (44-47 mmol/mol [6.2-6.4%]) had much higher 5-year risk, 26.4% (22.0, 30.5%) compared with 2.1% (1.5, 2.6%) for 39-41 mmol/mol (5.7-5.9%) and 7.0% (5.4, 8.6%) for 42-43 mmol/mol (6.0-6.1%). Changing the entry criterion to prevention programmes from 39 to 42 mmol/mol (5.7-6.0%) reduced the proportion classified high-risk by 61%, and increased the positive predictive value (PPV) from 5.8 to 12.4% with negligible impact on the negative predictive value (NPV), 99.6% to 99.1%. Increasing the threshold further, to 44 mmol/mol (6.2%), reduced those classified high-risk by 59%, and markedly increased the PPV from 12.4 to 23.2% and had little impact on the NPV (99.1% to 98.5%). CONCLUSIONS: A large proportion of people are identified as high-risk using current thresholds. Increasing the risk threshold markedly reduces the number of people that would be classified as high-risk and entered into prevention programmes, although this must be balanced against cases missed. Raising the entry threshold would allow limited intervention opportunities to be focused on those most likely to develop T2D.

The association between mechanical ventilator compatible bed occupancy and mortality risk in intensive care patients with COVID-19: a national retrospective cohort study.

BACKGROUND: The literature paints a complex picture of the association between mortality risk and ICU strain. In this study, we sought to determine if there is an association between mortality risk in intensive care units (ICU) and occupancy of beds compatible with mechanical ventilation, as a proxy for strain. METHODS: A national retrospective observational cohort study of 89 English hospital trusts (i.e. groups of hospitals functioning as single operational units). Seven thousand one hundred thirty-three adults admitted to an ICU in England between 2 April and 1 December, 2020 (inclusive), with presumed or confirmed COVID-19, for whom data was submitted to the national surveillance programme and met study inclusion criteria. A Bayesian hierarchical approach was used to model the association between hospital trust level (mechanical ventilation compatible), bed occupancy, and in-hospital all-cause mortality. Results were adjusted for unit characteristics (pre-pandemic size), individual patient-level demographic characteristics (age, sex, ethnicity, deprivation index, time-to-ICU admission), and recorded chronic comorbidities (obesity, diabetes, respiratory disease, liver disease, heart disease, hypertension, immunosuppression, neurological disease, renal disease). RESULTS: One hundred thirty-five thousand six hundred patient days were observed, with a mortality rate of 19.4 per 1000 patient days. Adjusting for patient-level factors, mortality was higher for admissions during periods of high occupancy (> 85% occupancy versus the baseline of 45 to 85%) [OR 1.23 (95% posterior credible interval (PCI): 1.08 to 1.39)]. In contrast, mortality was decreased for admissions during periods of low occupancy (< 45% relative to the baseline) [OR 0.83 (95% PCI 0.75 to 0.94)]. CONCLUSION: Increasing occupancy of beds compatible with mechanical ventilation, a proxy for operational strain, is associated with a higher mortality risk for individuals admitted to ICU. Further research is required to establish if this is a causal relationship or whether it reflects strain on other operational factors such as staff. If causal, the result highlights the importance of strategies to keep ICU occupancy low to mitigate the impact of this type of resource saturation.