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Until about a decade ago, laser-induced ionization was considered instantaneous. Since then, applications of attosecond laser pulses have shown multiple subtle and complex factors that influence the precise timing of electron ejection from atoms and surfaces. Vos et al. measured the corresponding attosecond dynamics of dissociative photoionization in a diatomic molecule, carbon monoxide. By imaging the charged fragments, the timing could be correlated with the specific spatial portion of the molecule from which the electron wave packet emerged. Science , this issue p. 1326 The precise timing of ionization in CO varies with respect to the portion of the molecule from which the electron emerges. Attosecond metrology of atoms has accessed the time scale of the most fundamental processes in quantum mechanics. Transferring the time-resolved photoelectric effect from atoms to molecules considerably increases experimental and theoretical challenges. Here we show that orientation- and energy-resolved measurements characterize the molecular stereo Wigner time delay. This observable provides direct information on the localization of the excited electron wave packet within the molecular potential. Furthermore, we demonstrate that photoelectrons resulting from the dissociative ionization process of the CO molecule are preferentially emitted from the carbon end for dissociative 2 Σ states and from the center and oxygen end for the 2 Π states of the molecular ion. Supported by comprehensive theoretical calculations, this work constitutes a complete spatially and temporally resolved reconstruction of the molecular photoelectric effect.

The basic concept, that specialized extracellular matrices rich in hyaluronan, chondroitin sulfate proteoglycans (aggrecan, versican, neurocan, brevican, phosphacan), link proteins and tenascins (Tn-R, Tn-C) can regulate cellular migration and axonal growth and thus, actively participate in the development and maturation of the nervous system, has in recent years gained rapidly expanding experimental support. The swift assembly and remodeling of these matrices have been associated with axonal guidance functions in the periphery and with the structural stabilization of myelinated fiber tracts and synaptic contacts in the maturating central nervous system. Particular interest has been focused on the putative role of chondroitin sulfate proteoglycans in suppressing central nervous system regeneration after lesions. The axon growth inhibitory properties of several of these chondroitin sulfate proteoglycans in vitro, and the partial recovery of structural plasticity in lesioned animals treated with chondroitin sulfate degrading enzymes in vivo have significantly contributed to the increased awareness of this long time neglected structure.

Pancreatic cancer is characterized by abundant desmoplasia, a dense stroma composed of extra-cellular and cellular components, with cancer associated fibroblasts (CAFs) being the major cellular component. However, the tissue(s) of origin for CAFs remains controversial. Here we determine the tissue origin of pancreatic CAFs through comprehensive lineage tracing studies in mice. We find that the splanchnic mesenchyme, the fetal cell layer surrounding the endoderm from which the pancreatic epithelium originates, gives rise to the majority of resident fibroblasts in the normal pancreas. In a genetic mouse model of pancreatic cancer, resident fibroblasts expand and constitute the bulk of CAFs. Single cell RNA profiling identifies gene expression signatures that are shared among the fetal splanchnic mesenchyme, adult fibroblasts and CAFs, suggesting a persistent transcriptional program underlies splanchnic lineage differentiation. Together, this study defines the phylogeny of the mesenchymal component of the pancreas and provides insights into pancreatic morphogenesis and tumorigenesis. Cancer-associated fibroblasts (CAFs) are the main component of the stroma in pancreatic cancer, but their tissue of origin remains to be defined. Here the authors perform lineage tracing and single cell RNA sequencing in mice and suggest the splanchnic mesenchyme as the tissue of origin for CAFs.

Artificial Intelligence (AI)-based deep learning methods for predicting protein structures are reshaping knowledge development and scientific discovery. Recent large-scale application of AI models for protein structure prediction has changed perceptions about complicated biological problems and empowered a new generation of structure-based hypothesis testing. It is well-recognized that proteins have a modular organization according to archetypal folds. However, it is yet to be determined if predicted structures are tuned to one conformation of flexible proteins or if they represent average conformations. Further, whether or not the answer is protein fold-dependent. Therefore, in this study, we analyzed 2878 proteins with at least ten distinct experimental structures available, from which we can estimate protein topological rigidity verses heterogeneity from experimental measurements. We found that AlphaFold v2 (AF2) predictions consistently return one specific form to high accuracy, with 99.68% of distinct folds (n = 623 out of 628) having an experimental structure within 2.5Å RMSD from a predicted structure. Yet, 27.70% and 10.82% of folds (174 and 68 out of 628 folds) have at least one experimental structure over 2.5Å and 5Å RMSD, respectively, from their AI-predicted structure. This information is important for how researchers apply and interpret the output of AF2 and similar tools. Additionally, it enabled us to score fold types according to how homogeneous versus heterogeneous their conformations are. Importantly, folds with high heterogeneity are enriched among proteins which regulate vital biological processes including immune cell differentiation, immune activation, and metabolism. This result demonstrates that a large amount of protein fold flexibility has already been experimentally measured, is vital for critical cellular processes, and is currently unaccounted for in structure prediction databases. Therefore, the structure-prediction revolution begets the protein dynamics revolution!

Failure to achieve a protected state after influenza vaccination is poorly understood but occurs commonly among aged populations experiencing greater immunosenescence. In order to better understand immune response in the elderly, we studied epigenetic and transcriptomic profiles and humoral immune response outcomes in 50-74 year old healthy participants. Associations between DNA methylation and gene expression reveal a system-wide regulation of immune-relevant functions, likely playing a role in regulating a participant's propensity to respond to vaccination. Our findings show that sites of methylation regulation associated with humoral response to vaccination impact known cellular differentiation signaling and antigen presentation pathways. We performed our analysis using per-site and regionally average methylation levels, in addition to continuous or dichotomized outcome measures. The genes and molecular functions implicated by each analysis were compared, highlighting different aspects of the biologic mechanisms of immune response affected by differential methylation. Both cis-acting (within the gene or promoter) and trans-acting (enhancers and transcription factor binding sites) sites show significant associations with measures of humoral immunity. Specifically, we identified a group of CpGs that, when coordinately hypo-methylated, are associated with lower humoral immune response, and methylated with higher response. Additionally, CpGs that individually predict humoral immune responses are enriched for polycomb-group and FOXP2 transcription factor binding sites. The most robust associations implicate differential methylation affecting gene expression levels of genes with known roles in immunity (e.g. HLA-B and HLA-DQB2) and immunosenescence. We believe our data and analysis strategy highlight new and interesting epigenetic trends affecting humoral response to vaccination against influenza; one of the most common and impactful viral pathogens.

Water-redispersible, nanofibrillated cellulose (NFC) in powder form was prepared from refined, bleached beech pulp (RBP) by carboxymethylation (c) and mechanical disintegration (m). Two routes were examined by altering the sequence of the chemical and mechanical treatment, leading to four different products: RBP-m and RBP-mc (route 1), and RBP-c and RBP-cm (route 2). The occurrence of the carboxymethylation reaction was confirmed by FT-IR spectrometry and ¹³C solid state NMR (¹³C CP-MAS) spectroscopy with the appearance of characteristic signals for the carboxylate group at 1,595 cm⁻¹ and 180 ppm, respectively. The chemical modification reduced the crystallinity of the products, especially for those of route 2, as shown by XRD experiments. Also, TGA showed a decrease in the thermal stability of the carboxymethylated products. However, sedimentation tests revealed that carboxymethylation was critical to obtain water-redispersible powders: the products of route 2 were easier to redisperse in water and their aqueous suspensions were more stable and transparent than those from route 1. SEM images of freeze-dried suspensions from redispersed RBP powders confirmed that carboxymethylation prevented irreversible agglomeration of cellulose fibrils during drying. These results suggest that carboxymethylated and mechanically disintegrated RBP in dry form is a very attractive alternative to conventional NFC aqueous suspensions as starting material for derivatization and compounding with (bio)polymers.

Oat straw cellulose pulp was cationized in an etherification reaction with chlorocholine chloride. The cationized cellulose pulp was then mechanically disintegrated in two process steps to obtain trimethylammonium-modified nanofibrillated cellulose (TMA-NFC). The materials thus obtained were analyzed by elemental analysis, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), scanning electron microscopy (SEM) and other techniques. A higher nitrogen content of TMA-NFC samples was found by XPS analysis than by elemental analysis, which indicates that the modification occurred mainly on the surface of cellulose fibrils. XPS also confirmed the existence of ammonium groups in the samples. SEM provided images of very fine network structures of TMA-NFC, which affirmed the positive effect of ionic charge on mechanical disintegration process. According to XRD and SEM results, no severe degradation of the cellulose occurred, even at high reaction temperatures. Because of the different properties of the cationic NFC compared to negatively charged native cellulose fibers, TMA-NFC may find broad applications in technical areas, for instance in combination with anionic species, such as fillers or dyes. Indeed, TMA-NFC seems to improve the distribution of clay fillers in NFC matrix.

A novel, fast and reliable sample preparation procedure for the simultaneous separation of Sr, Pb, and Nd has been developed for subsequent isotope ratio analysis of sediment digests. The method applying a fully automated, low-pressure chromatographic system separates all three analytes in a single-stage extraction step using self-packed columns filled with DGA Resin. The fully automated set-up allows the unattended processing of three isotopic systems from one sediment digest every 2 h, offering high sample throughput of up to 12 samples per day and reducing substantially laboratory manpower as compared to conventional manual methods. The developed separation method was validated using the marine sediment GBW-07313 as matrix-matched certified reference material and combines quantitative recoveries (>90% for Sr, >93% for Pb, and >91% for Nd) with low procedural blank levels following the sample separation (0.07 μg L −1 Sr, 0.03 μg L −1 Pb, and 0.57 μg L −1 Nd). The average δ values for Sr, Pb, and Nd of the separated reference standards were within the certified ranges ( δ ( 87 Sr/ 86 Sr) NIST SRM 987 of −0.05(28) ‰, δ ( 208 Pb/ 206 Pb) NIST SRM 981 of −0.21(14) ‰, and δ ( 143 Nd/ 144 Nd) JNdi-1 of 0.00(7) ‰). The DGA Resin proved to be reusable for the separation of >10 sediment digests with no significant carry-over or memory effects, as well as no significant on-column fractionation of Sr, Pb, and Nd isotope ratios. Additional spike experiments of NIST SRM 987 with Pb, NIST SRM 981 with Sr, and JNdi-1 with Ce revealed no significant impact on the measured isotopic ratios, caused by potential small analyte peak overlaps during the separation of Sr and Pb, as well as Ce and Nd.

Genetic variants in low-density lipoprotein receptor (LDLR) are known to cause familial hypercholesterolemia (FH), occurring in up to 1 in 200 people (Youngblom E. et al. 1993 and Nordestgaard BG et al. 34:3478–3490a, 2013) and leading to significant risk for heart disease. Clinical genomics testing using high-throughput sequencing is identifying novel genomic variants of uncertain significance (VUS) in individuals suspected of having FH, but for whom the causal link to the disease remains to be established (Nordestgaard BG et al. 34:3478–3490a, 2013). Unfortunately, experimental data about the atomic structure of the LDL binding domains of LDLR at extracellular pH does not exist. This leads to an inability to apply protein structure-based methods for assessing novel variants identified through genetic testing. Thus, the ambiguities in interpretation of LDLR variants are a barrier to achieving the expected clinical value for personalized genomics assays for management of FH. In this study, we integrated data from the literature and related cellular receptors to develop high-resolution models of full-length LDLR at extracellular conditions and use them to predict which VUS alter LDL binding. We believe that the functional effects of LDLR variants can be resolved using a combination of structural bioinformatics and functional assays, leading to a better correlation with clinical presentation. We have completed modeling of LDLR in two major physiologic conditions, generating detailed hypotheses for how each of the 1007 reported protein variants may affect function.Key messages• Hundreds of variants are observed in the LDLR, but most lack interpretation.• Molecular modeling is aided by biochemical knowledge.• We generated context-specific 3D protein models of LDLR.• Our models allowed mechanistic interpretation of many variants.• We interpreted both rare and common genomic variants in their physiologic context.• Effects of genomic variants are often context-specific.

The validity of the adiabatic approximation in strong field ionization under typical experimental conditions has recently become a topic of great interest. Experimental results have been inconclusive, in part, due to the uncertainty in experimental calibration of intensity. Here we turn to the time-dependent Schrödinger equation, where all the laser parameters are known exactly. We find that the centre of the electron momentum distribution (typically used for calibration of elliptically and circularly polarized light) is sensitive to non-adiabatic effects, leading to intensity shifts in experimental data that can significantly affect the interpretation of results. On the other hand, the transverse momentum spread in the plane of polarization is relatively insensitive to such effects, even in the Keldysh parameter regime approaching γ 3 . This suggests the transverse momentum spread in the plane of polarization as a good alternative to the usual calibration method, particularly for experimental investigation of non-adiabatic effects using circularly polarized light.