The usefulness of a new high-performance liquid chromatography/small-angle X-ray scattering (HPLC-SAXS) data analysis module within the multi-resolution modeling suite US-SOMO is illustrated with size-exclusion small-angle X-ray scattering (SE-SAXS) data of a crude bovine serum albumin sample. The module is then applied to the SE-SAXS study of a human plasma fibrinogen high-molecular-weight fraction presenting severe aggregation problems and a split non-symmetrical main elution peak probably resulting from in-column degradation.

Purpose Using a recently developed matrix‐assisted laser desorption/ionization imaging mass spectrometry (MALDI‐IMS) method, human breast cancer formalin‐fixed paraffin‐embedded (FFPE) tissue sections and tissue microarrays (TMA) are evaluated for N‐linked glycan distribution in the tumor microenvironment. Experimental design Tissue sections representing multiple human epidermal growth factor receptor 2 (HER2) receptor–positive and triple‐negative breast cancers (TNBC) in both TMA and FFPE slide format are processed for high resolution N‐glycan MALDI‐IMS. An additional FFPE tissue cohort of primary and metastatic breast tumors from the same donors are also evaluated. Results The cumulative N‐glycan MALDI‐IMS analysis of breast cancer FFPE tissues and TMAs indicate the distribution of specific glycan structural classes to stromal, necrotic, and tumor regions. A series of high‐mannose, branched and fucosylated glycans are detected predominantly within tumor regions. Additionally, a series of polylactosamine glycans are detected in advanced HER2+, TNBC, and metastatic breast cancer tissues. Comparison of tumor N‐glycan species detected in paired primary and metastatic tissues indicate minimal changes between the two conditions. Conclusions and clinical relevance The prevalence of tumor‐associated polylactosamine glycans in primary and metastatic breast cancer tissues indicates new mechanistic insights into the development and progression of breast cancers. The presence of these glycans could be targeted for therapeutic strategies and further evaluation as potential prognostic biomarkers.

The Carr−Hermans method [Macromolecules 1978, 11, 46−50], often used for determining the fibers diameter d and density ρ in fibrin or other filamentous networks from turbidity data, is found to be remarkably inaccurate when the system's mass fractal dimension D m is >1. An expanded approach based on the knowledge of the system D m and pore size ξ, which can be accurately recovered from low-angle elastic light scattering data or estimated from confocal microscopy, is proposed. By fitting the turbidity data with a function obtained by numerically integrating the fibrin-optimized scattering form factor of a network of cylindrical elements, both d and ρ can be independently recovered. Numerical simulations were employed to validate the reliability and accuracy of the method, which is then applied to evolving fibrin gels data. More in general, this method is extendible to the analysis of other filamentous networks that can be represented as ensembles of cylindrical elements.

The formation of a fibrin network following fibrinogen enzymatic activation is the central event in blood coagulation and has important biomedical and biotechnological implications. A non-covalent polymerization reaction between macromolecular monomers, it consists basically of two complementary processes: elongation/branching generates an interconnected 3D scaffold of relatively thin fibrils, and cooperative lateral aggregation thickens them more than 10-fold. We have studied the early stages up to the gel point by fast fibrinogen:enzyme mixing experiments using simultaneous small-angle X-ray scattering and wide-angle, multi-angle light scattering detection. The coupled evolutions of the average molecular weight, size, and cross section of the solutes during the fibrils growth phase were thus recovered. They reveal that extended structures, thinner than those predicted by the classic halfstaggered, double-stranded mechanism, must quickly form. Following extensive modeling, an initial phase is proposed in which single-bonded "Y-ladder" polymers rapidly elongate before undergoing a delayed transition to the double-stranded fibrils. Consistent with the data, this alternative mechanism can intrinsically generate frequent, random branching points in each growing fibril. The model predicts that, as a consequence, some branches in these expanding "lumps" eventually interconnect, forming the pervasive 3D network. While still growing, other branches will then undergo a Ca 2+ /length-dependent cooperative collapse on the resulting network scaffolding filaments, explaining their sudden thickening, low final density, and basic mechanical properties.

Fibrin gels are biological networks that play a fundamental role in blood coagulation and other patho/physiological processes, such as thrombosis and cancer. Electron and confocal microscopies show a collection of fibers that are relatively monodisperse in diameter, not uniformly distributed, and connected at nodal points with a branching order of ∼3-4. Although in the confocal images the hydrated fibers appear to be quite straight (mass fractal dimension D(m) = 1), for the overall system 1, joined at randomly distributed nodal points. The resulting 3D network strikingly resembles real fibrin gels and can be sketched as an assembly of densely packed fractal blobs, i.e., regions of size ξ, where the fiber concentration is higher than average. The blobs are placed at a distance ξ0 between their centers of mass so that they are overlapped by a factor η =ξ/ξ0 and have D(m) ∼1.2-1.6. The in silico gels' structure is quantitatively analyzed by its 3D spatial correlation function g(3D)(r) and corresponding power spectrum I(q) = FFT(3D[g3D(r)]), from which ρ, d, D(m), η, and ξ0 can be extracted. In particular, ξ0 provides an excellent estimate of the gel mesh size. The in silico gels' I(q) compares quite well with real gels' elastic light-scattering measurements. We then derived an analytical form factor for accurately fitting the scattering data, which allowed us to directly recover the gels' structural parameters.