Using the ELF test, FIB-4 and NAFLD fibrosis score to screen the population for liver disease.

BACKGROUND & AIMS: There is a need for accurate biomarkers of fibrosis for population screening of alcohol-related and non-alcoholic fatty liver disease (ALD, NAFLD). We compared the performance of the enhanced liver fibrosis (ELF) test to the fibrosis-4 index (FIB-4) and NAFLD fibrosis score (NFS), using transient elastography as the reference standard. METHODS: We prospectively included participants from the general population, and people at risk of ALD or NAFLD. Screening positive participants (TE ≥8 kPa) were offered a liver biopsy. We measured concomitant ELF, FIB-4, and NFS using validated cut-offs: ≥9.8, ≥1.3, ≥-1.45, respectively. RESULTS: We included 3,378 participants (1,973 general population, 953 at risk of ALD, 452 at risk of NAFLD), with a median age of 57 years (IQR: 51-63). Two hundred-and-forty-two were screening positive (3.4% in the general population, 12%/14% who were at-risk of ALD/NAFLD, respectively). Most participants with TE <8 kPa also had ELF <9.8 (88%) despite a poor overall correlation between ELF and TE (Spearman´s rho = 0.207). ELF was associated with significantly fewer false positives (11%) than FIB-4 and NFS (35% and 45%), while retaining a low rate of false negatives (<8%). A screening strategy of FIB-4 followed by ELF in indeterminate cases resulted in false positives in 8%, false negatives in 4% and the correct classification in 88% of cases. We performed a liver biopsy in 155/242 (64%) patients who screened positive, of whom 54 (35%) had advanced fibrosis (≥F3). ELF diagnosed advanced fibrosis with significantly better diagnostic accuracy than FIB-4 and NFS: AUROC 0.85 (95% CI 0.79-0.92) vs. 0.73 (0.64-0.81) and 0.66 (0.57-0.76), respectively. CONCLUSION: The ELF test alone or combined with FIB-4 for liver fibrosis screening in the general population and at-risk groups reduces the number of futile referrals compared to FIB-4 and NFS, without overlooking true cases. IMPACT AND IMPLICATIONS: We need referral pathways that are efficient at detecting advanced fibrosis from alcohol-related and non-alcoholic fatty liver disease in the population, but without causing futile referrals or excessive use of resources. This study indicates that a sequential test strategy of FIB-4 followed by the ELF test in indeterminate cases leads to few patients referred for confirmatory liver stiffness measurement, while retaining a high rate of detected cases, and at low direct costs. This two-step referral pathway could be used by primary care for mass, targeted, or opportunistic screening for liver fibrosis in the population. CLINICAL TRIAL NUMBER: Clinicaltrials.gov number NCT03308916.

Single-spin vector analysis of strongly coupled nuclei in TOCSY NMR experiments.

This paper presents a new way to represent the effect of complex radio-frequency (rf) pulse sequences on J-coupled nuclear spin systems. The model uses a vector representation of the single-spin interactions (chemical-shift and rf interactions) and provides a simple route to gain analytical insight into multipulse NMR experiments. The single-spin Hamiltonian is expressed in an interaction representation as Fourier components. These Fourier components are combined for the two spins to establish the averaged coupling term of the Hamiltonian. This effective Hamiltonian is fast to calculate as only single-spin rotations are used and followed by simple summation of numbers for reconstruction of given coupling interactions. The present method is used to gain analytical insight into the performance of the J-coupling transfer sequence DIPSI-2 through two figures of merit (FOM) providing useful information for optimization of such pulse sequences. The first FOM (ΞAB) reports the efficiency of the desired total correlation spectroscopy transfer and should be as large as possible, while the second (ΞHet) reports the potential leakage of coherence to a heteronuclear spin and should be as small as possible.

An Algebro-topological description of protein domain structure.

The space of possible protein structures appears vast and continuous, and the relationship between primary, secondary and tertiary structure levels is complex. Protein structure comparison and classification is therefore a difficult but important task since structure is a determinant for molecular interaction and function. We introduce a novel mathematical abstraction based on geometric topology to describe protein domain structure. Using the locations of the backbone atoms and the hydrogen bonds, we build a combinatorial object--a so-called fatgraph. The description is discrete yet gives rise to a 2-dimensional mathematical surface. Thus, each protein domain corresponds to a particular mathematical surface with characteristic topological invariants, such as the genus (number of holes) and the number of boundary components. Both invariants are global fatgraph features reflecting the interconnectivity of the domain by hydrogen bonds. We introduce the notion of robust variables, that is variables that are robust towards minor changes in the structure/fatgraph, and show that the genus and the number of boundary components are robust. Further, we investigate the distribution of different fatgraph variables and show how only four variables are capable of distinguishing different folds. We use local (secondary) and global (tertiary) fatgraph features to describe domain structures and illustrate that they are useful for classification of domains in CATH. In addition, we combine our method with two other methods thereby using primary, secondary, and tertiary structure information, and show that we can identify a large percentage of new and unclassified structures in CATH.