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PURPOSE: To describe the clinical, electrophysiological and genetic spectrum of inherited retinal diseases associated with variants in the PRPH2 gene. METHODS: A total of 241 patients from 168 families across 15 sites in 9 countries with pathogenic or likely pathogenic variants in PRPH2 were included. Records were reviewed for age at symptom onset, visual acuity, full-field ERG, fundus colour photography, fundus autofluorescence (FAF), and SD-OCT. Images were graded into six phenotypes. Statistical analyses were performed to determine genotype-phenotype correlations. RESULTS: The median age at symptom onset was 40 years (range, 4-78 years). FAF phenotypes included normal (5%), butterfly pattern dystrophy, or vitelliform macular dystrophy (11%), central areolar choroidal dystrophy (28%), pseudo-Stargardt pattern dystrophy (41%), and retinitis pigmentosa (25%). Symptom onset was earlier in retinitis pigmentosa as compared with pseudo-Stargardt pattern dystrophy (34 vs 44 years; P = 0.004). The median visual acuity was 0.18 logMAR (interquartile range, 0-0.54 logMAR) and 0.18 logMAR (interquartile range 0-0.42 logMAR) in the right and left eyes, respectively. ERG showed a significantly reduced amplitude across all components (P < 0.001) and a peak time delay in the light-adapted 30-Hz flicker and single-flash b-wave (P < 0.001). Twenty-two variants were novel. The central areolar choroidal dystrophy phenotype was associated with 13 missense variants. The remaining variants showed marked phenotypic variability. CONCLUSIONS: We described six distinct FAF phenotypes associated with variants in the PRPH2 gene. One FAF phenotype may have multiple ERG phenotypes, demonstrating a discordance between structure and function. Given the vast spectrum of PRPH2 disease our findings are useful for future clinical trials.

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion.

Carbon nanotubes (CNTs) possess exceptional mechanical properties, surpassing stiffness and strength metrics of common materials such as steel alloys by 100× at the nanoscale. However, when myriads of individual CNTs are bundled together into macroscopic ensembles like fibers or sheets, the result is a 100-fold drop in strength compared to its individual components. Here we present a general strategy aimed to close this gap in property scaling. By using vapor-phase polymerization of a crosslinkable polymer, we reinforced the weak interlinkages among individual CNTs within both yarns and sheets to promote a better transference of mechanical load across the structure. After the treatment, dry-spun, low-density 2.3 μm thin yarns increased their elastic moduli by at least 300%, and free-standing CNT sheets exhibited a 10× boost. In-situ synchrotron small-angle X-ray scattering revealed that polymer-reinforced yarns undergo limited CNT bundle rearrangement when subjected to tensile loads compared to pristine yarns. This evidence supports the hypothesis that the polymer hinders CNTs slippage, the root cause of the poor scaling of mechanical properties in these materials. While we demonstrated this reinforcement method for CNT structures, it is not specific to CNTs and could be used in a wide variety of other hierarchical nanostructured ensembles.

IntroductionStructured medication reviews (SMRs), introduced in the United Kingdom (UK) in 2020, aim to enhance shared decision-making in medication optimisation, particularly for patients with multimorbidity and polypharmacy. Despite its potential, there is limited empirical evidence on the implementation of SMRs, and the challenges faced in the process. This study is part of a larger DynAIRx (Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity) project which aims to introduce Artificial Intelligence (AI) to SMRs and develop machine learning models and visualisation tools for patients with multimorbidity. Here, we explore how SMRs are currently undertaken and what barriers are experienced by those involved in them.MethodsQualitative focus groups and semi-structured interviews took place between 2022-2023. Six focus groups were conducted with doctors, pharmacists and clinical pharmacologists (n = 21), and three patient focus groups with patients with multimorbidity (n = 13). Five semi-structured interviews were held with 2 pharmacists, 1 trainee doctor, 1 policy-maker and 1 psychiatrist. Transcripts were analysed using thematic analysis.ResultsTwo key themes limiting the effectiveness of SMRs in clinical practice were identified: 'Medication Reviews in Practice' and 'Medication-related Challenges'. Participants noted limitations to the efficient and effectiveness of SMRs in practice including the scarcity of digital tools for identifying and prioritising patients for SMRs; organisational and patient-related challenges in inviting patients for SMRs and ensuring they attend; the time-intensive nature of SMRs, the need for multiple appointments and shared decision-making; the impact of the healthcare context on SMR delivery; poor communication and data sharing issues between primary and secondary care; difficulties in managing mental health medications and specific challenges associated with anticholinergic medication.ConclusionSMRs are complex, time consuming and medication optimisation may require multiple follow-up appointments to enable a comprehensive review. There is a need for a prescribing support system to identify, prioritise and reduce the time needed to understand the patient journey when dealing with large volumes of disparate clinical information in electronic health records. However, monitoring the effects of medication optimisation changes with a feedback loop can be challenging to establish and maintain using current electronic health record systems.

Purpose: To conduct a costing study comparing orthoptist-led with consultant-led clinics screening for optic pathway gliomas (OPGs) in children with neurofibromatosis Type 1 (NF1) attending the Royal Children’s Hospital (RCH), Melbourne. Methods: Patients with NF1 examined in the orthoptist-led NF1 screening clinic and/or consultant-led clinics during the study period were identified. The workflow management software Q-Flow 6® provided data documenting patient’s time spent with the orthoptist, nurse, and ophthalmologist. Time points were converted into minutes and multiplied by the cost-per-minute for each profession. A bottom-up micro-costing approach was used to estimate appointment level costs. Bootstrap simulations with 1000 replications were used to estimate 95% confidence intervals (CIs) for the difference in mean appointment time and cost between clinics. Results: Data for 130 consultant-led clinic appointments and 234 orthoptist-led clinic appointments were extracted for analysis. The mean time per appointment for the consultant-led clinic was 45.11 minutes, and the mean time per appointment for the orthoptist-led clinic was 25.85 minutes. The mean cost per appointment for the consultant-led clinic was A $84.15 (GBP £39.60) compared to the orthoptist-led clinic at A $20.40 (GBP £9.60). This represents a mean reduction of 19.25 minutes per appointment (95% CI, –24.85 to –13.66) and a mean reduction of A $63.75 (GBP £30.00) per appointment (95% CI, (A $-75.40 to $-52.10 [GBP £ -35.48 to £ -24.52]). Conclusion: An orthoptist-led clinic screening for OPGs in patients with NF1 can be a more cost-efficient model of care for ophthalmic screening in this patient group.

Background Structured Medication Reviews (SMRs) are intended to help deliver the NHS Long Term Plan for medicines optimisation in people living with multiple long-term conditions and polypharmacy. It is challenging to gather the information needed for these reviews due to poor integration of health records across providers and there is little guidance on how to identify those patients most urgently requiring review. Objective To extract information from scattered clinical records on how health and medications change over time, apply interpretable artificial intelligence (AI) approaches to predict risks of poor outcomes and overlay this information on care records to inform SMRs. We will pilot this approach in primary care prescribing audit and feedback systems, and co-design future medicines optimisation decision support systems. Design DynAIRx will target potentially problematic polypharmacy in three key multimorbidity groups, namely, people with (a) mental and physical health problems, (b) four or more long-term conditions taking ten or more drugs and (c) older age and frailty. Structured clinical data will be drawn from integrated care records (general practice, hospital, and social care) covering an ∼11m population supplemented with Natural Language Processing (NLP) of unstructured clinical text. AI systems will be trained to identify patterns of conditions, medications, tests, and clinical contacts preceding adverse events in order to identify individuals who might benefit most from an SMR. Discussion By implementing and evaluating an AI-augmented visualisation of care records in an existing prescribing audit and feedback system we will create a learning system for medicines optimisation, co-designed throughout with end-users and patients.

Glaucoma is a highly heritable disease that is a leading cause of blindness worldwide. Here, we identified heterozygous thrombospondin 1 (THBS1) missense alleles altering p.Arg1034, a highly evolutionarily conserved amino acid, in 3 unrelated and ethnically diverse families affected by congenital glaucoma, a severe form of glaucoma affecting children. Thbs1R1034C-mutant mice had elevated intraocular pressure (IOP), reduced ocular fluid outflow, and retinal ganglion cell loss. Histology revealed an abundant, abnormal extracellular accumulation of THBS1 with abnormal morphology of juxtacanalicular trabecular meshwork (TM), an ocular tissue critical for aqueous fluid outflow. Functional characterization showed that the THBS1 missense alleles found in affected individuals destabilized the THBS1 C-terminus, causing protein misfolding and extracellular aggregation. Analysis using a range of amino acid substitutions at position R1034 showed that the extent of aggregation was correlated with the change in protein-folding free energy caused by variations in amino acid structure. Extracellular matrix (ECM) proteins, especially fibronectin, which bind to THBS1, also accumulated within THBS1 deposits. These results show that missense variants altering THBS1 p.Arg1034 can cause elevated IOP through a mechanism involving impaired TM fluid outflow in association with accumulation of aggregated THBS1 in the ECM of juxtacanalicular meshwork with altered morphology.

Objectives Missing data is the most common data quality issue in electronic health records (EHRs). Missing data checks implemented in common analytical software are typically limited to counting the number of missing values in individual fields, but researchers and organisations also need to understand multifield missing data patterns to better inform advanced missing data strategies for which counts or numerical summaries are poorly suited. This study shows how set-based visualisation enables multifield missing data patterns to be discovered and investigated.Design Development and evaluation of interactive set visualisation techniques to find patterns of missing data and generate actionable insights. The visualisations comprised easily interpretable bar charts for sets, heatmaps for set intersections and histograms for distributions of both sets and intersections.Setting and participants Anonymised admitted patient care health records for National Health Service (NHS) hospitals and independent sector providers in England. The visualisation and data mining software was run over 16 million records and 86 fields in the dataset.Results The dataset contained 960 million missing values. Set visualisation bar charts showed how those values were distributed across the fields, including several fields that, unexpectedly, were not complete. Set intersection heatmaps revealed unexpected gaps in diagnosis, operation and date fields because diagnosis and operation fields were not filled up sequentially and some operations did not have corresponding dates. Information gain ratio and entropy calculations allowed us to identify the origin of each unexpected pattern, in terms of the values of other fields.Conclusions Our findings show how set visualisation reveals important insights about multifield missing data patterns in large EHR datasets. The study revealed both rare and widespread data quality issues that were previously unknown, and allowed a particular part of a specific hospital to be pinpointed as the origin of rare issues that NHS Digital did not know exist.

Objective Paediatric (childhood or congenital) cataract is an opacification of the normally clear lens of the eye and has a genetic basis in at least 18% of cases in Australia. This study aimed to replicate clinical gene screening to identify variants likely to be causative of disease in an Australian patient cohort.Methods and analysis Sixty-three reported isolated cataract genes were screened for rare coding variants in 37 Australian families using genome sequencing.Results Disease-causing variants were confirmed in eight families with variant classification as ‘likely pathogenic’. This included novel variants PITX3 p.(Ter303LeuextTer100), BFSP1 p.(Glu375GlyfsTer2), and GJA8 p.(Pro189Ser), as well as, previously described variants identified in genes GJA3, GJA8, CRYAA, BFSP1, PITX3, COL4A1 and HSF4. Additionally, eight variants of uncertain significance with evidence towards pathogenicity were identified in genes: GJA3, GJA8, LEMD2, PRX, CRYBB1, BFSP2, and MIP.Conclusion These findings expand the genotype–phenotype correlations of both pathogenic and benign variation in cataract-associated genes. They further emphasise the need to develop additional evidence such as functional assays and variant classification criteria specific to paediatric cataract genes to improve interpretation of variants and molecular diagnosis in patients.

Abstract Background Secondary use of data via integrated health information technology is fundamental to many healthcare policies and processes worldwide. However, repurposing data can be problematic and little research has been undertaken into the everyday practicalities of inter-system data sharing that helps explain why this is so, especially within (as opposed to between) organisations. In response, this article reports one of the most detailed empirical examinations undertaken to date of the work involved in repurposing healthcare data for National Clinical Audits. Methods Fifty-four semi-structured, qualitative interviews were carried out with staff in five English National Health Service hospitals about their audit work, including 20 staff involved substantively with audit data collection. In addition, ethnographic observations took place on wards, in ‘back offices’ and meetings (102 h). Findings were analysed thematically and synthesised in narratives. Results Although data were available within hospital applications for secondary use in some audit fields, which could, in theory, have been auto-populated, in practice staff regularly negotiated multiple, unintegrated systems to generate audit records. This work was complex and skilful, and involved cross-checking and double data entry, often using paper forms, to assure data quality and inform quality improvements. Conclusions If technology is to facilitate the secondary use of healthcare data, the skilled but largely hidden labour of those who collect and recontextualise those data must be recognised. Their detailed understandings of what it takes to produce high quality data in specific contexts should inform the further development of integrated systems within organisations.

Abstract\nPLAIN LANGUAGE SUMMARYHigher education leaders sometimes transgress norms of political involvement. Despite some norm-violating behaviors, legal consequences are sparse. Some argue that this is based on concerns over taxpayers impugning regulators’ motives as partisan. Public skepticism is warranted, especially as university officials engage in unlawful forms of political activism that can go unenforced. What explains citizens’ tolerance for norm-violating political activities within higher education institutions? Furthermore, what drives citizens to blame some leaders for engaging in legally precarious political behaviors while providing more latitude for others who act similarly? Drawing from research on citizen accountability as well as partisan cue-led attitudes, authors argue that tolerance for political involvement in higher education contexts is explained by an institutional leader’s partisanship and sectoral type, that is, private versus public institution. To test these claims, authors fielded a survey experiment drawing on a Lucid panel. Findings show evidence that a leader’s partisanship and the institution’s sectoral type influence individuals’ acceptance or rejection of a university president’s endorsement of a political candidate, dependent upon the respondent’s partisan characteristics. Findings also confirm the emerging politicization of higher educational spaces, highlighting the implications for understanding public perceptions of higher education leaders’ political involvement and the impact on the sector.College and university presidents may become involved in politics in ways that may not follow the law or fall in line with norms. Often leaders who cross the line are not punished or held accountable, potentially because punishment may look politically biased. While there are times when public doubt is justified, there are also times when college and university leaders push political agendas without consequences. Why do citizens sometimes ignore these transgressions? Why do citizens criticize some college and university leaders for political actions but not others? The answer might have to do with the leaders’ political affiliations and whether a private or public institution is connected to a scandal. To better understand this phenomenon, authors conducted a survey experiment with 1,403 participants. Results showed that citizens’ reactions to a university president supporting a political candidate are influenced by both the leader’s and the participant’s political affiliations as well as whether the institution is private or public. This research supports the idea that politics is becoming more prominent in higher education and that enforcement of laws is a difficult challenge. [ABSTRACT FROM AUTHOR]

Abstract Autosomal dominant optic atrophy (ADOA) is a neuro-ophthalmic condition characterized by bilateral degeneration of the optic nerves. Although heterozygous mutations in OPA1 represent the most common genetic cause of ADOA, a significant number of cases remain undiagnosed. Here, we describe a family with a strong ADOA history with most family members spanning three generation having childhood onset of visual symptoms. The proband, in addition to optic atrophy, had neurological symptoms consistent with relapsing remitting multiple sclerosis. Clinical exome analysis detected a novel mutation in the AFG3L2 gene (NM_006796.2:c.1010G > A; p.G337E), which segregated with optic atrophy in family members. AFG3L2 is a metalloprotease of the AAA subfamily which exerts quality control in the inner mitochondrial membrane. Interestingly, the identified mutation localizes close to the AAA domain of AFG3L2, while those localized in the proteolytic domain cause dominant spinocerebellar ataxia type 28 (SCA28) or recessive spastic ataxia with epilepsy (SPAX5). Functional studies in patient fibroblasts demonstrate that the p.G337E AFG3L2 mutation strongly destabilizes the long isoforms of OPA1 via OMA hyper-activation and leads to mitochondrial fragmentation, thus explaining the family phenotype. This study widens the clinical spectrum of neurodegenerative diseases caused by AFG3L2 mutations, which shall be considered as genetic cause of ADOA.