Numerical analysis of flow non-uniformity in the hot gas manifold of the Space Shuttle main engine

Three-dimensional viscous flow in a conceptual hot gas manifold (HGM) for the Space Shuttle Main Engine High Pressure Fuel Turbopump (SSME HPFTP) was numerically analyzed. A finite difference scheme was used to solve the Navier-Stokes equations. The exact geometry of the SSME HGM was modeled using boundary fitted curvilinear coordinates and the General Interpolants Method (GIM) code. Slight compressibility of the subsonic flow was modeled using a linearized equation of state with artificial compressibility. A time relaxation method was used to obtain a steady state solution. The feasibility and potential usefulness of computational methods in assisting the design of SSME components which involves the flow of fluids within complex geometrical shapes is demonstrated

Narrative review of the role of artificial intelligence to improve aortic valve disease management

Valvular heart disease (VHD) is a chronic progressive condition with an increasing prevalence in the Western world due to aging populations. VHD is often diagnosed at a late stage when patients are symptomatic and the outcomes of therapy, including valve replacement, may be sub-optimal due the development of secondary complications, including left ventricular (LV) dysfunction. The clinical application of artificial intelligence (AI), including machine learning (ML), has promise in supporting not only early and more timely diagnosis, but also hastening patient referral and ensuring optimal treatment of VHD. As physician auscultation lacks accuracy in diagnosis of significant VHD, computer-aided auscultation (CAA) with the help of a commercially available digital stethoscopes improves the detection and classification of heart murmurs. Although used little in current clinical practice, CAA can screen large populations at low cost with high accuracy for VHD and faciliate appropriate patient referral. Echocardiography remains the next step in assessment and planning management and AI is delivering major changes in speeding training, improving image quality by pattern recognition and image sorting, as well as automated measurement of multiple variables, thereby improving accuracy. Furthermore, AI then has the potential to hasten patient disposal, by automated alerts for red-flag findings, as well as decision support in dealing with results. In management, there is great potential in ML-enabled tools to support comprehensive disease monitoring and individualized treatment decisions. Using data from multiple sources, including demographic and clinical risk data to image variables and electronic reports from electronic medical records, specific patient phenotypes may be identified that are associated with greater risk or modeled to the estimate trajectory of VHD progression. Finally, AI algorithms are of proven value in planning intervention, facilitating transcatheter valve replacement by automated measurements of anatomical dimensions derived from imaging data to improve valve selection, valve size and method of delivery

Electronic health records to facilitate clinical research

Electronic health records (EHRs) provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Concerns have been raised about the increasing recruitment challenges in trials, burdensome and obtrusive data collection, and uncertain generalizability of the results. Leveraging electronic health records to counterbalance these trends is an area of intense interest. The initial applications of electronic health records, as the primary data source is envisioned for observational studies, embedded pragmatic or post-marketing registry-based randomized studies, or comparative effectiveness studies. Advancing this approach to randomized clinical trials, electronic health records may potentially be used to assess study feasibility, to facilitate patient recruitment, and streamline data collection at baseline and follow-up. Ensuring data security and privacy, overcoming the challenges associated with linking diverse systems and maintaining infrastructure for repeat use of high quality data, are some of the challenges associated with using electronic health records in clinical research. Collaboration between academia, industry, regulatory bodies, policy makers, patients, and electronic health record vendors is critical for the greater use of electronic health records in clinical research. This manuscript identifies the key steps required to advance the role of electronic health records in cardiovascular clinical research

Generation of a set of isogenic iPSC lines carrying all APOE genetic variants (Ɛ2/Ɛ3/Ɛ4) and knock-out for the study of APOE biology in health and disease

APOE genotype is the strongest genetic risk factor for Alzheimer’s Disease (AD). The low degree of homology between mouse and human APOE is a concerning issue in preclinical models currently used to study the role of this gene in AD pathophysiology. A key objective of ADAPTED (Alzheimer’s Disease Apolipoprotein Pathology for Treatment Elucidation and Development) project was to generate in vitro models that better recapitulate human APOE biology. We describe a new set of induced pluripotent stem cells (iPSC) lines carrying common APOE variants (Ɛ2, Ɛ3, and Ɛ3/Ɛ4) and a knock-out isogenic to the parental APOE Ɛ4/Ɛ4 line (UKBi011-A).This study was funded by the ADAPTED (Alzheimer’s Disease Apolipoprotein Pathology for Treatment Elucidation and Development) consortium which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No 115975. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Associations

OSBPL2 encodes a protein of inner and outer hair cell stereocilia and is mutated in autosomal dominant hearing loss (DFNA67)

Background: Early-onset hearing loss is mostly of genetic origin. The complexity of the hearing process is reflected by its extensive genetic heterogeneity, with probably many causative genes remaining to be identified. Here, we aimed at identifying the genetic basis for autosomal dominant non-syndromic hearing loss (ADNSHL) in a large German family. Methods: A panel of 66 known deafness genes was analyzed for mutations by next-generation sequencing (NGS) in the index patient. We then conducted genome-wide linkage analysis, and whole-exome sequencing was carried out with samples of two patients. Expression of Osbpl2 in the mouse cochlea was determined by immunohistochemistry. Because Osbpl2 has been proposed as a target of miR-96, we investigated homozygous Mir96 mutant mice for its upregulation. Results: Onset of hearing loss in the investigated ADNSHL family is in childhood, initially affecting the high frequencies and progressing to profound deafness in adulthood. However, there is considerable intrafamilial variability. We mapped a novel ADNSHL locus, DFNA67, to chromosome 20q13.2-q13.33, and subsequently identified a co-segregating heterozygous frameshift mutation, c.141-142delTG (p.Arg50Alafs∗103), in OSBPL2, encoding a protein known to interact with the DFNA1 protein, DIAPH1. In mice, Osbpl2 was prominently expressed in stereocilia of cochlear outer and inner hair cells. We found no significant Osbpl2 upregulation at the mRNA level in homozygous Mir96 mutant mice. Conclusion: The function of OSBPL2 in the hearing process remains to be determined. Our study and the recent description of another frameshift mutation in a Chinese ADNSHL family identify OSBPL2 as a novel gene for progressive deafness.</p

IMPULSE: The impact of gender on the presentation and management of aortic stenosis across Europe

Aims There is an increasing awareness of gender-related differences in patients with severe aortic stenosis and their outcomes after surgical aortic valve replacement (SAVR) and transcatheter aortic valve implantation (TAVI). Methods Data from the IMPULSE registry were analysed. Patients with severe aortic stenosis (AS) were enrolled between March 2015 and April 2017 and stratified by gender. A subgroup analysis was performed to assess the impact of age. Results Overall, 2171 patients were enrolled, and 48.0% were female. Women were characterised by a higher rate of renal impairment (31.7 vs 23.3%; p&lt;0.001), were at higher surgical risk (EuroSCORE II: 4.5 vs 3.6%; p=0.001) and more often in a critical preoperative state (7.0vs 4.2%; p=0.003). Men had an increased rate of previous cardiac surgery (9.4 vs 4.7%; p&lt;0.001) and a reduced left ventricular ejection fraction (4.9 vs 1.3%; p&lt;0.001). Concomitant mitral and tricuspid valve disease was substantially more common among women. Symptoms were highly prevalent in both women and men (83.6 vs 77.3%; p&lt;0.001). AVR was planned in 1379 cases. Women were more frequently scheduled to undergo TAVI (49.3 vs 41.0%; p&lt;0.001) and less frequently for SAVR (20.3 vs 27.5%; p&lt;0.001). Conclusions The present data show that female patients with severe AS have a distinct patient profile and are managed in a different way to males. Gender-based differences in the management of patients with severe AS need to be taken into account more systematically to improve outcomes, especially for women

Impact of selected comorbidities on the presentation and management of aortic stenosis

Background Contemporary data regarding the impact of comorbidities on the clinical presentation and management of patients with severe aortic stenosis (AS) are scarce. Methods Prospective registry of severe patients with AS across 23 centres in nine European countries. Results Of the 2171 patients, chronic kidney disease (CKD 27.3%), left ventricular ejection fraction (LVEF) &lt;50% (22.0%), atrial fibrillation (15.9%) and chronic obstructive pulmonary disease (11.4%) were the most prevalent comorbidities (49.3% none, 33.9% one and 16.8% ≥2 of these). The decision to perform aortic valve replacement (AVR) was taken in a comparable proportion (67%, 72% and 69%, in patients with 0, 1 and ≥2 comorbidities; p=0.186). However, the decision for TAVI was more common with more comorbidities (35.4%, 54.0% and 57.0% for no, 1 and ≥2; p&lt;0.001), while the decision for surgical AVR (SAVR) was decreased with increasing comorbidity burden (31.9%, 17.4% and 12.3%; p&lt;0.001). The proportion of patients with planned AVRs that were performed within 3 months was significantly higher in patients with 1 or ≥2 comorbidities than in those without (8.7%, 10.0% and 15.7%; p&lt;0.001). Furthermore, the mean time to AVR was significantly shorter in patients with one (30.5 days) or ≥2 comorbidities (30.8 days) than in those without (35.7 days; p=0.012). Patients with reduced LVEF tended to be offered an AVR more frequently and with a shorter delay while patients with CKD were less frequently treated. Conclusions Comorbidities in severe patients with AS affect the presentation and management of patients with severe AS. TAVI was offered more often than SAVR and performed within a shorter time period

Management of patients with severe aortic stenosis in the TAVI-era: How recent recommendations are translated into clinical practice

Objective Approximately 3.4% of adults aged &gt;75 years suffer from aortic stenosis (AS). Guideline indications for aortic valve replacement (AVR) distinguish between patients with symptomatic and asymptomatic severe AS. The present analysis aims to assess contemporary practice in the treatment of severe AS across Europe and identify characteristics associated with treatment decisions, namely denial of AVR in symptomatic patients and assignment of asymptomatic patients to AVR. Methods Participants of the prospective, multinational IMPULSE database of patients with severe AS were grouped according to AS symptoms, and stratified into subgroups based on assignment to/denial of AVR. Results Of 1608 symptomatic patients, 23.8% did not undergo AVR and underwent medical treatment. Denial was independently associated with multiple factors, including severe frailty (p=0.024); mitral (p=0.002) or tricuspid (p=0.004) regurgitation grade III/IV, and the presence of renal impairment (p=0.017). Of 392 asymptomatic patients, 86.5% had no prespecified indication for AVR. Regardless, 36.3% were assigned to valve replacement. Those with an indexed aortic valve area (AVA; p=0.045) or left ventricular ejection fraction (LVEF; p&lt;0.001) below the study median; or with a left ventricular end systolic diameter above the study median (p=0.007) were more likely to be assigned to AVR. Conclusions There may be considerable discrepancies between guideline-based recommendations and clinical practice decision-making in the treatment of AS. It appears that guidelines may not fully capture the complete clinical spectrum of patients with AS. Thus, there is a need to find ways to increase their acceptance and the rate of adoption

Symptoms, disease severity and treatment of adults with a new diagnosis of severe aortic stenosis

Objective Contemporary data on patients with previously undiagnosed severe aortic stenosis (AS) are scarce. We aimed to address this gap by gathering data from consecutive patients diagnosed with severe AS on echocardiography. Methods This was a prospective, multicentre, multinational, registry in 23 tertiary care hospitals across 9 European countries. Patients with a diagnosis of severe AS were included using echocardiography (aortic valve area (AVA) &lt;1 cm 2, indexed AVA &lt;0.6 cm 2 /m 2, maximum jet-velocity (V max) &gt;4 m/s and/or mean transvalvular gradient &gt;40 mm Hg). Results The 2171 participants had a mean age of 77.9 years and 48.0% were female. The mean AVA was 0.73 cm 2, V max 4.3 m/s and mean gradient 47.1 mm Hg; 62.1% had left ventricular hypertrophy and 27.3% an ejection fraction (EF) &lt;50%. 1743 patients (80.3%) were symptomatic (shortness-of-breath 91.0%; dizziness 30.2%, chest pain 28.9%). Patients had a EuroSCORE II of 4.0; 25.3% had a creatinine clearance &lt;50 mL/min, and 3.2% had an EF &lt;30%. Symptomatic patients were older and had more comorbidities than asymptomatic patients. Despite European Society of Cardiology 2017 valvular heart disease guideline class I recommendation, in only 76.2% a decision was made for an intervention (transcatheter 50.4%, surgical aortic valve replacement 25.8%). In asymptomatic patients, 57.7% with a class I/IIa indication were scheduled for a procedure, while 36.3% patients without an indication had their valve replaced. Conclusions The majority of patients with severe AS presented at an advanced disease stage. Management of severe AS remained suboptimal in a significant proportion of contemporary patients with severe AS. Trial registration number NCT02241447;Results

Facilitated Data Relay and Effects on Treatment of Severe Aortic Stenosis in Europe

Background: Many patients with severe aortic stenosis are referred late with advanced symptoms or inappropriately denied intervention. The objective was to investigate whether a structured communication to referring physicians (facilitated data relay) might improve the rate and timeliness of intervention. Methods and Results: A prospective registry of consecutive patients with severe aortic stenosis at 23 centers in 9 European countries with transcatheter as well as surgical aortic valve replacement being available was performed. The study included a 3-month documentation of the status quo (phase A), a 6-month intervention phase (implementing facilitated data relay), and a 3-month documentation of a legacy effect (phase-B). Two thousand one hundred seventy-one patients with severe aortic stenoses were enrolled (phase A: 759; intervention: 905; phase-B: 507). Mean age was 77.9±10.0&nbsp;years, and 80% were symptomatic, including 52% with severe symptoms. During phase A, intervention was planned in 464/696 (67%), 138 (20%) were assigned to watchful waiting, 8 (1%) to balloon aortic valvuloplasty, 60 (9%) were listed as not for active treatment, and in 26 (4%), no decision was made. Three hundred sixty-three of 464 (78%) patients received the planned intervention within 3&nbsp;months. Timeliness of the intervention improved as shown by the higher number of aortic valve replacements performed within 3&nbsp;months (59% versus 51%, P=0.002) and a significant decrease in the time to intervention (36±38 versus 30±33&nbsp;days, P=0.002). Conclusions: A simple, low-cost, facilitated data relay improves timeliness of treatment for patients diagnosed with severe aortic stenosis, resulting in a shorter time to transcatheter aortic valve replacement. This effect was mainly driven by a significant improvement in timeliness of intervention in transcatheter aortic valve replacement but not surgical aortic valve replacement. Clinical Trial Registration: URL: https://www.clinicaltrials.gov/. Unique identifier: NCT02241447