Baseline TAPSE/PASP ratio is associated with all-cause mortality in TAVI patients as it evaluates RV systolic performance at a given degree of afterload. Incorporation of right-side unit into the risk stratification may improve optimal selection of patients for TAVI.

Objectives To determine the prevalence and factors associated with persistent pulmonary hypertension (PH) following transcatheter aortic valve replacement (TAVR) and its relationship with long-term mortality. Methods Consecutive patients who underwent TAVR from July 2011 through January 2016 were studied. The prevalence of baseline PH (mean pulmonary artery pressure ≥25 mm Hg on right heart catheterisation) and the prevalence and the predictors of persistent≥moderate PH (pulmonary artery systolic pressure (PASP)>45 mm Hg on 1 month post-TAVR transthoracic Doppler echocardiography) were collected. Cox models quantified the effect of persistent PH on subsequent mortality while adjusting for confounders. Results Of the 407 TAVR patients, 273 (67%) had PH at baseline. Of these, 102 (25%) had persistent≥moderate PH. Mortality at 2 years in patients with no baseline PH versus those with PH improvement (follow-up PASP≤45 mm Hg) versus those with persistent≥moderate PH was 15.4%, 16.6% and 31.3%, respectively (p=0.049). After adjusting for Society of Thoracic Surgeons Predicted Risk of Mortality and baseline right ventricular function (using tricuspid annular plane systolic excursion), persistent≥moderate PH remained associated with all-cause mortality (HR=1.82, 95% CI 1.06 to 3.12, p=0.03). Baseline characteristics associated with increased likelihood of persistent≥moderate PH were ≥moderate tricuspid regurgitation, ≥moderate mitral regurgitation, atrial fibrillation/flutter, early (E) to late (A) ventricular filling velocities (E/A ratio) and left atrial volume index. Conclusions Persistency of even moderate or greater PH at 1 month post-TAVR is common and associated with higher all-cause mortality.

Background Emicizumab is a subcutaneously administered humanized, bispecific, monoclonal antibody approved for prophylaxis in people with hemophilia A. Methods HAVEN 5 (NCT03315455) is a randomized, open‐label, phase 3 study of individuals aged ≥12 years with severe hemophilia A without factor VIII (FVIII) inhibitors, or hemophilia A of any severity with FVIII inhibitors, across the Asia‐Pacific region. Participants were randomly assigned (2:2:1) to receive emicizumab 1.5 mg/kg once weekly (arm A), emicizumab 6 mg/kg every 4 weeks (arm B), or no prophylaxis (arm C). The primary end point was annualized bleeding rate (ABR) for treated bleeds; ABRs were compared between people receiving emicizumab prophylaxis versus those with no prophylaxis. Secondary end points included ABR for treated target joint bleeds. Safety was also evaluated. Results From April 26, 2018, to January 4, 2019, 70 of 76 screened participants were enrolled and randomized (arm A, n = 29; arm B, n = 27; arm C, n = 14). ABRs (95% confidence interval) for treated bleeds and treated target joint bleeds, respectively, were: arm A, 1.0 (0.53‐1.85) and 0.4 (0.18‐1.09); arm B, 1.0 (0.50‐1.84) and 0.3 (0.12‐0.85); arm C, 27.0 (13.29‐54.91) and 8.6 (3.15‐23.42). The most common adverse event, upper respiratory tract infection, was reported for 14 of 56 (25.0%; emicizumab) and 2 of 14 (14.3%; no prophylaxis) participants. No thrombotic events, thrombotic microangiopathies, or deaths were reported. Conclusion Emicizumab 1.5 mg/kg once weekly and 6 mg/kg every 4 weeks demonstrated bleed control in this study population, was well tolerated, and could improve use of prophylaxis in people with hemophilia A.

No abstract

Recent studies have shown that ultrafast enzymatic digestion of proteins can be achieved in microdroplet within 250 μs. Further investigation of peptides resulting from microdroplet digestion (MD) would be necessary to evaluate it as an alternative to the conventional bulk digestion for bottom-up and biotherapeutic protein characterization. Herein we examined and compared protein tryptic digestion in both MD and bulk solution. In the case of MD of β-lactoglobulin B, the preservation of long peptides was observed due to the short digestion time. In addition, MD is applicable to digest both high- and low-abundance proteins in mixture. In the case of digesting NIST 8671 mAb antibody containing a low level of commonly encountered host cell protein (HCP) PLBL2 (mAb:PLBL2 = 100:1 by weight), MD produced lower levels of digestion-induced chemical modifications of asparagine/glutamine deamidation, compared with overnight digestion. No significant difference between MD and bulk digestion was observed in terms of trypsin digestion specificity based on examination of semi- and unspecific-cleaved peptides. Our study suggests that MD, a fast digestion approach, could be adopted for bottom-up proteomics research and for peptide mapping of mAbs to characterize site-specific deamidation and glycosylation, for the purpose of development of biopharmaceuticals.

No abstract

Inequality in cities is a phenomenon arising from the complex interactions among urban systems and population activities. Conventional statistics and mathematical models like multiple regression models require assumptions of feature interactions with specified mathematical forms that may fail to fully capture complex interactions of heterogeneous urban components, creating challenges in systematically assessing socio‐economic inequality in cities. To overcome the limitations of these conventional mathematical models, in this work, we propose an interpretable machine learning model to capture the complex interactions of urban variables and the main interaction effects on socio‐economic statuses. We extract urban features from high‐resolution anonymized mobile phone data with billions of activity records related to people and facilities in 47 US metropolitan areas and predict the attributes of urban areas from six income and race groups. We show that socio‐economic inequality in cities can be effectively measured by the predictability of trained machine learning models in controlled experiments. We also examine the tradeoff between spatial resolution, sample size, and model accuracy; test the presence of influential features; and measure the transferability of the trained models to identify the optimal values for controlled factors. The results show that metropolitan areas share similar patterns of inequality, which could be moderated by improved polycentric facility distribution and road density. The generality of associated factors and transferability of machine learning models can help bridge data gaps between cities and inform about inequality alleviation strategies. Despite similarities, 50% to 90% of variations among cities are still present, which shows the need for localized policies for inequality alleviation and mitigation. Our study shows that machine learning models could be an effective approach to examine inequality, which opens avenues for more data‐centric and complexity‐informed planning, design, policymaking, and engineering toward equitable cities.

No abstract