A Learnable Prior Improves Inverse Tumor Growth Modeling

Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a substantial challenge, either due to the high computational requirements of model-based approaches or the limited robustness of deep learning (DL) methods. We propose a novel framework that leverages the unique strengths of both approaches in a synergistic manner. Our method incorporates a DL ensemble for initial parameter estimation, facilitating efficient downstream evolutionary sampling initialized with this DL-based prior. We showcase the effectiveness of integrating a rapid deep-learning algorithm with a high-precision evolution strategy in estimating brain tumor cell concentrations from magnetic resonance images. The DL-Prior plays a pivotal role, significantly constraining the effective sampling-parameter space. This reduction results in a fivefold convergence acceleration and a Dice-score of 95.

Testing quantum electrodynamics in extreme fields using helium-like uranium

Quantum electrodynamics (QED), the quantum field theory that describes the interaction between light and matter, is commonly regarded as the best-tested quantum theory in modern physics. However, this claim is mostly based on extremely precise studies performed in the domain of relatively low field strengths and light atoms and ions1-6. In the realm of very strong electromagnetic fields such as in the heaviest highly charged ions (with nuclear charge Z ≫ 1), QED calculations enter a qualitatively different, non-perturbative regime. Yet, the corresponding experimental studies are very challenging, and theoretical predictions are only partially tested. Here we present an experiment sensitive to higher-order QED effects and electron-electron interactions in the high-Z regime. This is achieved by using a multi-reference method based on Doppler-tuned X-ray emission from stored relativistic uranium ions with different charge states. The energy of the 1s1/22p3/2 J = 2 → 1s1/22s1/2 J = 1 intrashell transition in the heaviest two-electron ion (U90+) is obtained with an accuracy of 37 ppm. Furthermore, a comparison of uranium ions with different numbers of bound electrons enables us to disentangle and to test separately the one-electron higher-order QED effects and the bound electron-electron interaction terms without the uncertainty related to the nuclear radius. Moreover, our experimental result can discriminate between several state-of-the-art theoretical approaches and provides an important benchmark for calculations in the strong-field domain.

Solving inverse problems in physics by optimizing a discrete loss: Fast and accurate learning without neural networks

In recent years, advances in computing hardware and computational methods have prompted a wealth of activities for solving inverse problems in physics. These problems are often described by systems of partial differential equations (PDEs). The advent of machine learning has reinvigorated the interest in solving inverse problems using neural networks (NNs). In these efforts, the solution of the PDEs is expressed as NNs trained through the minimization of a loss function involving the PDE. Here, we show how to accelerate this approach by five orders of magnitude by deploying, instead of NNs, conventional PDE approximations. The framework of optimizing a discrete loss (ODIL) minimizes a cost function for discrete approximations of the PDEs using gradient-based and Newton's methods. The framework relies on grid-based discretizations of PDEs and inherits their accuracy, convergence, and conservation properties. The implementation of the method is facilitated by adopting machine-learning tools for automatic differentiation. We also propose a multigrid technique to accelerate the convergence of gradient-based optimizers. We present applications to PDE-constrained optimization, optical flow, system identification, and data assimilation. We compare ODIL with the popular method of physics-informed neural networks and show that it outperforms it by several orders of magnitude in computational speed while having better accuracy and convergence rates. We evaluate ODIL on inverse problems involving linear and nonlinear PDEs including the Navier-Stokes equations for flow reconstruction problems. ODIL bridges numerical methods and machine learning and presents a powerful tool for solving challenging, inverse problems across scientific domains.

Flow reconstruction by multiresolution optimization of a discrete loss with automatic differentiation

We present a potent computational method for the solution of inverse problems in fluid mechanics. We consider inverse problems formulated in terms of a deterministic loss function that can accommodate data and regularization terms. We introduce a multigrid decomposition technique that accelerates the convergence of gradient-based methods for optimization problems with parameters on a grid. We incorporate this multigrid technique to the Optimizing a DIscrete Loss (ODIL) framework. The multiresolution ODIL (mODIL) accelerates by an order of magnitude the original formalism and improves the avoidance of local minima. Moreover, mODIL accommodates the use of automatic differentiation for calculating the gradients of the loss function, thus facilitating the implementation of the framework. We demonstrate the capabilities of mODIL on a variety of inverse and flow reconstruction problems: solution reconstruction for the Burgers equation, inferring conductivity from temperature measurements, and inferring the body shape from wake velocity measurements in three dimensions. We also provide a comparative study with the related, popular Physics-Informed Neural Networks (PINNs) method. We demonstrate that mODIL has three to five orders of magnitude lower computational cost than PINNs in benchmark problems including simple PDEs and lid-driven cavity problems. Our results suggest that mODIL is a very potent, fast and consistent method for solving inverse problems in fluid mechanics.

Computing foaming flows across scales: From breaking waves to microfluidics

Crashing ocean waves, cappuccino froths, and microfluidic bubble crystals are examples of foamy flows. Foamy flows are critical in numerous natural and industrial processes and remain notoriously difficult to compute as they involve coupled, multiscale physical processes. Computations need to resolve the interactions of the bubbles separated by stable thin liquid films. We present the multilayer volume-of-fluid method (Multi-VOF) that advances the state of the art in simulation capabilities of foamy flows. The method introduces a scheme to handle multiple bubbles that do not coalesce. Multi-VOF is verified and validated with experimental results and complemented with open-source software. We demonstrate capturing of crystalline structures of bubbles in realistic microfluidics devices and foamy flows involving tens of thousands of bubbles in a waterfall. The present technique extends the classical volume-of-fluid methodology and allows for large-scale predictive simulations of flows with multiple interfaces.

Structural Variability, Expression Profile, and Pharmacogenetic Properties of TMPRSS2 Gene as a Potential Target for COVID-19 Therapy

The human serine protease serine 2 TMPRSS2 is involved in the priming of proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and represents a possible target for COVID-19 therapy. The TMPRSS2 gene may be co-expressed with SARS-CoV-2 cell receptor genes angiotensin-converting enzyme 2 (ACE2) and Basigin (BSG), but only TMPRSS2 demonstrates tissue-specific expression in alveolar cells according to single-cell RNA sequencing data. Our analysis of the structural variability of the TMPRSS2 gene based on genome-wide data from 76 human populations demonstrates that a functionally significant missense mutation in exon 6/7 in the TMPRSS2 gene is found in many human populations at relatively high frequencies, with region-specific distribution patterns. The frequency of the missense mutation encoded by rs12329760, which has previously been found to be associated with prostate cancer, ranged between 10% and 63% and was significantly higher in populations of Asian origin compared with European populations. In addition to single-nucleotide polymorphisms, two copy number variants were detected in the TMPRSS2 gene. A number of microRNAs have been predicted to regulate TMPRSS2 and BSG expression levels, but none of them is enriched in lung or respiratory tract cells. Several well-studied drugs can downregulate the expression of TMPRSS2 in human cells, including acetaminophen (paracetamol) and curcumin. Thus, the interactions of TMPRSS2 with SARS-CoV-2, together with its structural variability, gene–gene interactions, expression regulation profiles, and pharmacogenomic properties, characterize this gene as a potential target for COVID-19 therapy.

Determination of the phylogenetic origins of the Árpád Dynasty based on Y chromosome sequencing of Béla the Third

We set out to identify the origins of the Árpád Dynasty based on genome sequencing of DNA derived from the skeletal remains of Hungarian King Béla III (1172–1196) and eight additional individuals (six males, two females) originally interred at the Royal Basilica of Székesfehérvár. Y-chromosome analysis established that two individuals, Béla III and HU52 assign to haplogroups R-Z2125 whose distribution centres near South Central Asia with subsidiary expansions in the regions of modern Iran, the Volga Ural region and the Caucasus. Out of a cohort of 4340 individuals from these geographic areas, we acquired whole-genome data from 208 individuals derived for the R-Z2123 haplogroup. From these data we have established that the closest living kin of the Árpád Dynasty are R-SUR51 derived modern day Bashkirs predominantly from the Burzyansky and Abzelilovsky districts of Bashkortostan in the Russian Federation. Our analysis also reveals the existence of SNPs defining a novel Árpád Dynasty specific haplogroup R-ARP. Framed within the context of a high resolution R-Z2123 phylogeny, the ancestry of the first Hungarian royal dynasty traces to the region centering near Northern Afghanistan about 4500 years ago and identifies the Bashkirs as their closest kin, with a separation date between the two populations at the beginning of the first millennium CE.

Shifts in the Genetic Landscape of the Western Eurasian Steppe Associated with the Beginning and End of the Scythian Dominance

The Early Iron Age nomadic Scythians have been described as a confederation of tribes of different origins, based on ancient DNA evidence [1-3]. It is still unclear how much of the Scythian dominance in the Eurasian Steppe was due to movements of people and how much reflected cultural diffusion and elite dominance. We present new whole-genome sequences of 31 ancient Western and Eastern Steppe individuals, including Scythians as well as samples pre- and postdating them, allowing us to set the Scythians in a temporal context (in the Western, i.e., Ponto-Caspian Steppe). We detect an increase of eastern (Altaian) affinity along with a decrease in eastern hunter-gatherer (EHG) ancestry in the Early Iron Age Ponto-Caspian gene pool at the start of the Scythian dominance. On the other hand, samples of the Chernyakhiv culture postdating the Scythians in Ukraine have a significantly higher proportion of Near Eastern ancestry than other samples of this study. Our results agree with the Gothic source of the Chernyakhiv culture and support the hypothesis that the Scythian dominance did involve a demic component.

Refining wet lab experiments with in silico searches: A rational quest for diagnostic peptides in visceral leishmaniasis

Background

The search for diagnostic biomarkers has been profiting from a growing number of high quality sequenced genomes and freely available bioinformatic tools. These can be combined with wet lab experiments for a rational search. Improved, point-of-care diagnostic tests for visceral leishmaniasis (VL), early case detection and surveillance are required. Previous investigations demonstrated the potential of IgG1 as a biomarker for monitoring clinical status in rapid diagnostic tests (RDTs), although using a crude lysate antigen (CLA) as capturing antigen. Replacing the CLA by specific antigens would lead to more robust RDTs.

Methodology

Immunoblots revealed L. donovani protein bands detected by IgG1 from VL patients. Upon confident identification of these antigens by mass spectrometry (MS), we searched for evidence of constitutive protein expression and presence of antigenic domains or high accessibility to B-cells. Selected candidates had their linear epitopes mapped with in silico algorithms. Multiple high-scoring predicted epitopes from the shortlisted proteins were screened in peptide arrays. The most promising candidate was tested in RDT prototypes using VL and nonendemic healthy control (NEHC) patient sera.

Results

Over 90% of the proteins identified from the immunoblots did not satisfy the selection criteria and were excluded from the downstream epitope mapping. Screening of predicted epitope peptides from the shortlisted proteins identified the most reactive, for which the sensitivity for IgG1 was 84% (95% CI 60—97%) with Sudanese VL sera on RDT prototypes. None of the sera from NEHCs were positive.

Conclusion

We employed in silico searches to reduce drastically the output of wet lab experiments, focusing on promising candidates containing selected protein features. By predicting epitopes in silico we screened a large number of peptides using arrays, identifying the most promising one, for which IgG1 sensitivity and specificity, with limited sample size, supported this proof of concept strategy for diagnostics discovery, which can be applied to the development of more robust IgG1 RDTs for monitoring clinical status in VL.

Visceral leishmaniasis (VL) is a neglected tropical disease caused by protozoan parasites of the Leishmania donovani complex. Without treatment, VL is fatal. Although diagnostic techniques, mainly based on the detection of anti-Leishmania antibodies are available, invasive procedures such as microscopy from spleen or bone marrow aspirates are still required for the diagnosis of seronegative VL suspects, for the detection of recurrent cases and to confirm cure after successful treatment. Previous investigations showed the potential of IgG1 as a biomarker of post-chemotherapeutic relapse for VL in rapid diagnostic tests (RDTs) sensitised with crude lysate antigen (CLA). Here we employed in silico tools to search for desired protein features in a large number of L. donovani antigens detected by human IgG1 in western blots. We then employed prediction algorithms to profile epitopes from the shortlisted proteins. We screened a panel of high-scoring peptides in a high-throughput manner using arrays, with low reagent consumption. The most reactive peptide was adapted to RDTs, showing promising results of both sensitivity and specificity. This peptide has the potential of replacing the CLAs in IgG1 RDTs. Thus we believe that in silico tools can be used to optimise wet lab experiments for a rational search of biomarkers.

Y-chromosomal analysis of clan structure of Kalmyks, the only European Mongol people, and their relationship to Oirat-Mongols of Inner Asia

Kalmyks, the only Mongolic-speaking population in Europe, live in the southeast of the European Plain, in Russia. They adhere to Buddhism and speak a dialect of the Mongolian language. Historical and linguistic evidence, as well a shared clan names, suggests a common origin with Oirats of western Mongolia; yet, only a limited number of genetic studies have focused on this topic. Here we compare the paternal genetic relationship of Kalmyk clans with ethnographically related groups from Mongolia, Kyrgyzstan and China, within the context of their neighbouring populations. A phylogeny of 37 high-coverage Y-chromosome sequences, together with further genotyping of larger sample sets, reveals that all the Oirat-speaking populations studied here, including Kalmyks, share, as a dominant paternal lineage, Y-chromosomal haplogroup C3c1-M77, which is also present in several geographically distant native Siberian populations. We identify a subset of this clade, C3c1b-F6379, specifically enriched in Kalmyks as well as in Oirat-speaking clans in Inner Asia. This sub-clade coalesces at around 1500 years before present, before the Genghis Khan era, and significantly earlier than the split between Kalmyks and other Oirat speakers about 400 years ago. We also show that split between the dominant hg C variant among Buryats—C3-M407—and that of C3-F6379, took place in the Early Upper Palaeolithic, suggesting an extremely long duration for the dissipation of hg C3-M217 carriers across northern Eurasia, which cuts through today’s major linguistic phyla.

Approaching the Gamow Window with Stored Ions: Direct Measurement of ^{124}Xe(p,γ) in the ESR Storage Ring

We report the first measurement of low-energy proton-capture cross sections of ^{124}Xe in a heavy-ion storage ring. ^{124}Xe^{54+} ions of five different beam energies between 5.5 and 8 AMeV were stored to collide with a windowless hydrogen target. The ^{125}Cs reaction products were directly detected. The interaction energies are located on the high energy tail of the Gamow window for hot, explosive scenarios such as supernovae and x-ray binaries. The results serve as an important test of predicted astrophysical reaction rates in this mass range. Good agreement in the prediction of the astrophysically important proton width at low energy is found, with only a 30% difference between measurement and theory. Larger deviations are found above the neutron emission threshold, where also neutron and γ widths significantly impact the cross sections. The newly established experimental method is a very powerful tool to investigate nuclear reactions on rare ion beams at low center-of-mass energies.

Genes reveal traces of common recent demographic history for most of the Uralic-speaking populations

BACKGROUND

The genetic origins of Uralic speakers from across a vast territory in the temperate zone of North Eurasia have remained elusive. Previous studies have shown contrasting proportions of Eastern and Western Eurasian ancestry in their mitochondrial and Y chromosomal gene pools. While the maternal lineages reflect by and large the geographic background of a given Uralic-speaking population, the frequency of Y chromosomes of Eastern Eurasian origin is distinctively high among European Uralic speakers. The autosomal variation of Uralic speakers, however, has not yet been studied comprehensively.

RESULTS

Here, we present a genome-wide analysis of 15 Uralic-speaking populations which cover all main groups of the linguistic family. We show that contemporary Uralic speakers are genetically very similar to their local geographical neighbours. However, when studying relationships among geographically distant populations, we find that most of the Uralic speakers and some of their neighbours share a genetic component of possibly Siberian origin. Additionally, we show that most Uralic speakers share significantly more genomic segments identity-by-descent with each other than with geographically equidistant speakers of other languages. We find that correlated genome-wide genetic and lexical distances among Uralic speakers suggest co-dispersion of genes and languages. Yet, we do not find long-range genetic ties between Estonians and Hungarians with their linguistic sisters that would distinguish them from their non-Uralic-speaking neighbours.

CONCLUSIONS

We show that most Uralic speakers share a distinct ancestry component of likely Siberian origin, which suggests that the spread of Uralic languages involved at least some demic component.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

BACKGROUND

The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia.

RESULTS

We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts.

CONCLUSIONS

Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Identification of the Lowest T=2, J^{π}=0^{+} Isobaric Analog State in ^{52}Co and Its Impact on the Understanding of β-Decay Properties of ^{52}Ni

Masses of ^{52g,52m}Co were measured for the first time with an accuracy of ∼10  keV, an unprecedented precision reached for short-lived nuclei in the isochronous mass spectrometry. Combining our results with the previous β-γ measurements of ^{52}Ni, the T=2, J^{π}=0^{+} isobaric analog state (IAS) in ^{52}Co was newly assigned, questioning the conventional identification of IASs from the β-delayed proton emissions. Using our energy of the IAS in ^{52}Co, the masses of the T=2 multiplet fit well into the isobaric multiplet mass equation. We find that the IAS in ^{52}Co decays predominantly via γ transitions while the proton emission is negligibly small. According to our large-scale shell model calculations, this phenomenon has been interpreted to be due to very low isospin mixing in the IAS.

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that of other non-Africans.

Determination of macroscopic transport coefficients of a dissipative particle dynamics solvent

We present an approach to determine macroscopic transport coefficients of a dissipative particle dynamics (DPD) solvent. Shear viscosity, isothermal speed of sound, and bulk viscosity result from DPD-model input parameters and can be determined only a posteriori. For this reason approximate predictions of these quantities are desirable in order to set appropriate DPD input parameters. For the purpose of deriving an improved approximate prediction we analyze the autocorrelation of shear and longitudinal modes in Fourier space of a DPD solvent for Kolmogorov flow. We propose a fitting function with nonexponential properties which gives a good approximation to these autocorrelation functions. Given this fitting function we improve significantly the capability of a priori determination of macroscopic solvent transport coefficients in comparison to previously used exponential fitting functions.

POPULATION GENETICS. Genomic evidence for the Pleistocene and recent population history of Native Americans

How and when the Americas were populated remains contentious. Using ancient and modern genome-wide data, we found that the ancestors of all present-day Native Americans, including Athabascans and Amerindians, entered the Americas as a single migration wave from Siberia no earlier than 23 thousand years ago (ka) and after no more than an 8000-year isolation period in Beringia. After their arrival to the Americas, ancestral Native Americans diversified into two basal genetic branches around 13 ka, one that is now dispersed across North and South America and the other restricted to North America. Subsequent gene flow resulted in some Native Americans sharing ancestry with present-day East Asians (including Siberians) and, more distantly, Australo-Melanesians. Putative "Paleoamerican" relict populations, including the historical Mexican Pericúes and South American Fuego-Patagonians, are not directly related to modern Australo-Melanesians as suggested by the Paleoamerican Model.

Ancient human genomes suggest three ancestral populations for present-day Europeans

We sequenced the genomes of a ~7,000 year old farmer from Germany and eight ~8,000 year old hunter-gatherers from Luxembourg and Sweden. We analyzed these and other ancient genomes^1–4 with 2,345 contemporary humans to show that most present Europeans derive from at least three highly differentiated populations: West European Hunter-Gatherers (WHG), who contributed ancestry to all Europeans but not to Near Easterners; Ancient North Eurasians (ANE) related to Upper Paleolithic Siberians³, who contributed to both Europeans and Near Easterners; and Early European Farmers (EEF), who were mainly of Near Eastern origin but also harbored WHG-related ancestry. We model these populations’ deep relationships and show that EEF had ~44% ancestry from a “Basal Eurasian” population that split prior to the diversification of other non-African lineages.

Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans

The origins of the First Americans remain contentious. Although Native Americans seem to be genetically most closely related to east Asians, there is no consensus with regard to which specific Old World populations they are closest to. Here we sequence the draft genome of an approximately 24,000-year-old individual (MA-1), from Mal'ta in south-central Siberia, to an average depth of 1×. To our knowledge this is the oldest anatomically modern human genome reported to date. The MA-1 mitochondrial genome belongs to haplogroup U, which has also been found at high frequency among Upper Palaeolithic and Mesolithic European hunter-gatherers, and the Y chromosome of MA-1 is basal to modern-day western Eurasians and near the root of most Native American lineages. Similarly, we find autosomal evidence that MA-1 is basal to modern-day western Eurasians and genetically closely related to modern-day Native Americans, with no close affinity to east Asians. This suggests that populations related to contemporary western Eurasians had a more north-easterly distribution 24,000 years ago than commonly thought. Furthermore, we estimate that 14 to 38% of Native American ancestry may originate through gene flow from this ancient population. This is likely to have occurred after the divergence of Native American ancestors from east Asian ancestors, but before the diversification of Native American populations in the New World. Gene flow from the MA-1 lineage into Native American ancestors could explain why several crania from the First Americans have been reported as bearing morphological characteristics that do not resemble those of east Asians. Sequencing of another south-central Siberian, Afontova Gora-2 dating to approximately 17,000 years ago, revealed similar autosomal genetic signatures as MA-1, suggesting that the region was continuously occupied by humans throughout the Last Glacial Maximum. Our findings reveal that western Eurasian genetic signatures in modern-day Native Americans derive not only from post-Columbian admixture, as commonly thought, but also from a mixed ancestry of the First Americans.

Numerical simulation of tethered DNA in shear flow

The behavior of tethered DNA in shear flow is investigated numerically by the smoothed dissipative particle dynamics (SDPD) method. Unlike numerical methods used in previous studies, SDPD models the solvent explicitly, takes into account the fully coupled hydrodynamic interactions and is free of the numerical artifact of wall sticking. Based on numerical simulations the static and dynamic properties of a tethered DNA is studied both qualitatively and quantitatively. The observed properties are in general agreement with previous experimental, numerical and theoretical work. Furthermore, the cyclic-motion phenomenon is studied by power spectrum density and cross-correlation function analysis, which suggest that there is only a very weak coherent motion of tethered DNA for a characteristic timescale larger than the relaxation time. Cyclic motion is more likely relevant as an isolated event than a typical mode of DNA motion.

Particle-layering effect in wall-bounded dissipative particle dynamics

Dissipative particle dynamics (DPD) is a mesoscopic simulation method that describes "clusters" of molecules as a single numerical particle. DPD is a very effective method but it introduces numerical artifacts through the coarse-graining procedure, such as particle ordering in the near-wall region. These artifacts can result in nonphysical phenomena during a simulation of a polymer tethered to the wall undergoing shear flow: polymer sticking and overextension for higher shear rates. In this paper we report that a version of DPD with a so-called solidification boundary formulation and conservative-force interactions based on the equation of state allows to reduce number density fluctuations in near-wall region significantly.

Discovery of highly excited long-lived isomers in neutron-rich hafnium and tantalum isotopes through direct mass measurements

A study of cooled ¹⁹⁷Au projectile-fragmentation products has been performed with a storage ring. This has enabled metastable nuclear excitations with energies up to 3 MeV, and half-lives extending to minutes or longer, to be identified in the neutron-rich nuclides ¹⁸³(,)¹⁸⁴(,)¹⁸⁶Hf and ¹⁸⁶(,)¹⁸⁷Ta. The results support the prediction of a strongly favored isomer region near neutron number 116.

Smoothed dissipative particle dynamics model for polymer molecules in suspension

We present a model for a polymer molecule in solution based on smoothed dissipative particle dynamics (SDPD) [Español and Revenga, Phys. Rev. E 67, 026705 (2003)]. This method is a thermodynamically consistent version of smoothed particle hydrodynamics able to discretize the Navier-Stokes equations and, at the same time, to incorporate thermal fluctuations according to the fluctuation-dissipation theorem. Within the framework of the method developed for mesoscopic multiphase flows by Hu and Adams [J. Comput. Phys. 213, 844 (2006)], we introduce additional finitely extendable nonlinear elastic interactions between particles that represent the beads of a polymer chain. In order to assess the accuracy of the technique, we analyze the static and dynamic conformational properties of the modeled polymer molecule in solution. Extensive tests of the method for the two-dimensional (2D) case are performed, showing good agreement with the analytical theory. Finally, the effect of confinement on the conformational properties of the polymer molecule is investigated by considering a 2D microchannel with gap H varying between 1 and 10 microm , of the same order as the polymer gyration radius. Several SDPD simulations are performed for different chain lengths corresponding to N=20-100 beads, giving a universal behavior of the gyration radius R_{G} and polymer stretch X as functions of the channel gap when normalized properly.

Consistent approach to adsorption thermodynamics on heterogeneous surfaces using different empirical energy distribution models

Adsorption on heterogeneous surfaces with three basic energy distribution models (uniform model, exponential model, and normal-like model) is studied. Exact analytical solutions of the adsorption isotherms and the heats of adsorption are derived for the uniform and exponential models, and, with these solutions including a numerical solution for the normal-like model, the behavior of the differential heat of adsorption and the "apparent" standard adsorption entropy concerning the overall surface is described as a function of coverage and temperature. The approximations underlying the isotherms and heats of adsorption in the Temkin, Freundlich, and Langmuir-Freundlich types of adsorption are rationalized. By comparing these empirical formulas to the exact solutions, the level of these approximations is found to be identical, which is similar to the "condensation approximation". Their preconditions are that either the temperature is low enough, or the surface is strongly heterogeneous. Generally, they are suitable for the middle coverage range. The exact solutions provide a method to obtain more information on the heats, entropy, and heterogeneity of the catalyst surface from the calorimetric measurement of the heat of adsorption.

Coverage-Dependent Kinetics and Thermodynamics of Carbon Monoxide Adsorption on a Ternary Copper Catalyst Derived from Static Adsorption Microcalorimetry

A reliable method for adsorption systems in equilibrium is established to derive coverage-dependent kinetics and thermodynamics from the volumetric data obtained during the static microcalorimetric measurement of heats of adsorption. The Wigner-Polanyi equation is applied to analyze the pressure change as a function of time during stepwise dosing of the adsorptive until thermodynamic adsorption-desorption equilibrium is established. For carbon monoxide adsorption on a hydrogen-reduced Cu/ZnO/Al2O3 catalyst, the adsorption rate constant (ka) is found to be in the range from 10(-6) to 10(-4) Pa(-1) s(-1), and the desorption rate constant (kd) from 10(-4) to 10(-2) s(-1), both increasing with fractional coverage theta. The kinetically derived equilibrium constant Ktheta is in good agreement with Ktheta obtained from the adsorption isotherm. RT ln(Kp0) and the differential heat of adsorption (qdiff) were found to decrease in parallel, reflecting a normal Temkin-type heterogeneity.

Microkinetic modeling of CO TPD spectra using coverage dependent microcalorimetric heats of adsorption

CO adsorption on the ternary methanol synthesis Cu/ZnO/Al2O3 catalyst was studied in detail by means of adsorption microcalorimetry and flow temperature-programmed desorption (TPD). Based on these experimental data, we established a microkinetic analysis method, which provides information about the adsorption kinetics of CO on the catalyst surface. Experimentally derived microcalorimetric heats of adsorption were applied in a microkinetic model to simulate TPD curves with varying initial coverage. Two approaches were used: an integral approach based on evaluation of the integral heats of adsorption which predicts the experimental TPD curves roughly and provides first approximations for the preexponential factors. The second, more detailed approach was based on the simulation of the adsorption isotherm taking the experimentally determined coverage-dependence of the heat of adsorption into account. This approach led to a significantly improved agreement between experimental and simulated TPD curves. Moreover, it was possible to derive the standard entropy of adsorption. The general applicability of our approaches is demonstrated by analyzing the CO TPD and microcalorimetry data obtained with a binary ZnO-free Cu/Al2O3 catalyst.

Simultaneous loss of E-cadherin and catenins in invasive lobular breast cancer and lobular carcinoma in situ

Loss of expression of the intercellular adhesion molecule E-cadherin frequently occurs in invasive lobular breast carcinomas as a result of mutational inactivation. Expression patterns of E-cadherin and the molecules comprising the cytoplasmic complex of adherens junctions, alpha-, beta- and gamma-catenin, were studied in a series of 38 lobular breast carcinomas with known E-cadherin mutation status. The effect of loss of E-cadherin by mutational inactivation (or other mechanisms) on the expression of catenins was investigated. Complete loss of plasma membrane-associated E-cadherin expression was observed in 32 out of 38 invasive lobular carcinomas, for which in 21 cases a mutation was found in the extracellular domain of E-cadherin. In total, 15 frameshift mutations of small deletions or insertions, ranging from 1 to 41 bp, three non-sense mutations, and three splice mutations were identified. Mutations were scattered over the whole coding region and no hot spots could be detected. In all cases, simultaneous loss of E-cadherin and alpha- and beta-catenin expression was found; in 50 per cent of these cases, additional loss of gamma-catenin was observed. In six invasive lobular carcinomas, expression of both E-cadherin and catenins was retained. In none of these carcinomas was an E-cadherin mutation detected. Lobular carcinoma in situ adjacent to invasive lobular carcinoma showed simultaneous loss of E-cadherin and catenins in all the cases studied--remarkably, also, in four cases positive for E-cadherin and catenin expression in the invasive component. These results indicate that simultaneous loss of E-cadherin and alpha-, beta- and gamma-catenin may be an important step in the formation of lobular carcinoma in situ, as a precursor of invasive lobular breast cancer. Events additional to E-cadherin inactivation must be involved in the transition of lobular carcinoma in situ to invasive lobular carcinoma.

Tumor heterogeneity and immunotherapy of cancer

Tumor heterogeneity is the presence of intercellular differences, either from clonal origin or present within subpopulations of tumor cells. Recent advances in immuno-histology, flow cytometric analysis, molecular biological techniques, and tissue culture methods makes it possible to investigate tumor heterogeneity in detail. In this review data are presented to document that this hallmark of neoplastic disease results from DNA-instability and the interactions of tumor cells with their environment. The present inability to treat most patients effectively with immunotherapy may partly be due to the occurrence of tumor heterogeneity. Therefore, the heterogeneity of the tumor phenotype is discussed in conjunction with the various immunotherapeutic treatment modalities. In addition to local cytokine production by immune cells and tumor cells, and limited access of either antibodies or immune cells into the tumor, tumor heterogeneity is an important factor that determines the progress of immunotherapy of cancer. Therefore, accurate quantitative methods using antibodies and molecular probes to identify HLA-associated target peptides, tumor-associated antigens and accessory molecules, to predict which patients will have a high probability of responding to treatment, are needed.

The product of the EMS1 gene, amplified and overexpressed in human carcinomas, is homologous to a v-src substrate and is located in cell-substratum contact sites

We have previously identified two genes (EMS1 and PRAD1/cyclin D1) in the chromosome 11q13 region that are frequently coamplified and overexpressed in human breast cancer and in squamous cell carcinomas of the head and neck (E. Schuuring, E. Verhoeven, W.J. Mooi, and R.J.A.M. Michalides, Oncogene 7:355-361, 1992). We now report on the characterization of the 80/85-kDa protein that is encoded by the EMS1 gene. Amino acid sequence comparison shows a high homology (85%) to a chicken protein that was recently identified as a substrate for the src oncogene (H. Wu, A.B. Reynolds, S.B. Kanner, R.R. Vines, and J.T. Parsons, Mol. Cell. Biol. 11:5113-5124, 1991). Immunocytochemistry reveals that in epithelial cells, the human EMS1 protein is localized mainly in the cytoplasm and, to a very low extent, in protruding leading lamellae of the cell. However, in carcinoma cells that constitutively overexpress the protein as a result of amplification of the EMS1 gene, the protein, except in cytoplasm, accumulates in the podosome-like adherens junctions associated with the cell-substratum contact sites. The protein was not found in intercellular adherens junctions. Our findings, and the previously reported observations in src-transformed chicken embryo fibroblasts, suggest that the EMS1 protein is involved in regulating the interactions between components of adherens-type junctions. Since amplification of the 11q13 region has been associated with an enhanced invasive potential of these tumors, overexpression and concomitant accumulation of the EMS1 protein in the cell-substratum contact sites might, therefore, contribute to the invasive potential of these tumor cells.

Antibodies against poliomyelitis and measles viruses in immunized and unimmunized children, Ghana 1976-78

The serological response of children to two doses of live oral poliomyelitis vaccine (the first at age 3-8 months and the second at age 9-14 months) and to one dose of measles vaccine (at age 9-14 months) was determined in two regions of Ghana. The seroconversion rates after two doses of poliomyelitis vaccine were lower than expected-24% for poliovirus type 1, 60% for type 2, and 52% for type 3; 23% of the subjects were triple negative. A third dose of the vaccine increased the seroconversion rates to 36%, 73%, and 61% for poliovirus types 1, 2, and 3, respectively; the rate for triple negatives fell to 8%. In the course of the study it was found that there was an intensive circulation of wild polioviruses and that a high proportion of 3-8 month-old infants had maternal antibodies.The seroconversion rate following one dose of measles vaccine was about 90%, a response similar to that obtained in temperate climates. The two main conclusions drawn from the study were: (1) two doses of poliomyelitis vaccine are inadequate to provide protection against poliomyelitis in developing countries; and (2) in developing countries measles vaccine should be given as soon as possible after the age of 8 months.