gebhart/patrepeval huggingface dataset:
Human lung branching morphogenesis is orchestrated by the spatiotemporal distribution of ACTA2, SOX2, and SOX9 (2017)

Lung morphogenesis relies on a number of important processes, including proximal-distal patterning, cell proliferation, migration and differentiation, as well as epithelial-mesenchymal interactions. In mouse lung development, SOX2<sup>+</sup> cells are localized in the proximal epithelium, whereas SOX9<sup>+</sup> cells are present in the distal epithelium. We show that, in human lung, expression of these transcription factors differs, in that during the pseudoglandular stage distal epithelial progenitors at the tips coexpress SOX2 and SOX9. This double-positive population was no longer present by the canalicular stages of development. As in mouse, the human proximal epithelial progenitors express solely SOX2 and are surrounded by smooth muscle cells (SMCs) both in the proximal airways and at the epithelial clefts. Upon Ras-related C3 botulinum toxin substrate 1 inhibition, we noted decreased branching, as well as increased SMC differentiation, attenuated peristalsis, and a reduction in the distal double-positive SOX2/SOX9 progenitor cell population. Thus, the presence of SOX2/SOX9 double-positive progenitor cells in the distal epithelium during the pseudoglandular stage of human lung development appears to be critical to proximal-distal patterning and lung branching. Moreover, SMCs promote a SOX2 proximal phenotype and seem to suppress the SOX9<sup>+</sup> population.
mRNA expression of the DNA replication-initiation proteins in epithelial dysplasia and squamous cell carcinoma of the tongue (2008)

These proteins can be used as biomarkers to distinguish precancerous dysplasia from SCC and are useful for early detection and diagnosis of SCC as an adjunct to clinicopathological parameters.
Bandwidth resource optimization in video-on-demand network architectures (2002)

It is generally recognized that interactive video-on-demand (IVOD) will become an important residential service of this decade. However, many issues with respect to the way this service has to be offered to the users remain open and me still subject to vigorous research activities. The aim of the paper is to present a VOD network solution based upon the Broadband Integrated Digital Network (B-ISDN) that targets the mass deployment of the IVOD service and offers the ability to cope with future types of multimedia services. By means of a VOD reference network and traffic mode, it is demonstrated that the proposed solution can achieve an optimized use of network (bandwidth), online storage and processing resources while guaranteeing a desired grade of service (GoS) under all circumstances. >
Lymph node metastases detected in the mesorectum distal to carcinoma of the rectum by the clearing method: justification of total mesorectal excision. (1997)

Total mesorectal excision is required for patients with T3 and T4 tumors in the lower rectum, and excision of all mesorectal tissue down to at least 5 cm below the tumor is required for patients with T3 and T4 tumors in the upper rectum.
Infrastructure Assisted Data Dissemination for Vehicular Sensor Networks in Metropolitan Areas (2012)

Vehicular Sensor Networks (VSNs) are an emerging area of research that combines technologies developed in the domains of Intelligent Transport Systems (ITS) and Wireless Sensor Networks. Data dissemination is an important aspect of these networks. It enables vehicles to share relevant sensor data about accidents, traffic load, or pollution. Several protocols are proposed for Vehicle to Vehicle (V2V) communication, but they are prone to intermittent connectivity. In this chapter, the authors propose a roadside infrastructure to ensure stable connectivity by adding vehicle to infrastructure to the V2V communication. They introduce a data dissemination protocol, Hexagonal Cell-Based Data Dissemination, adapting it for VSNs within a metropolitan area. The virtual architecture of the proposed data dissemination protocol exploits the typical radial configuration of main roads in a city, and uses them as the basis for the communication infrastructure where data and queries are stored. The design of the communication infrastructure in accordance with the road infrastructure distributes the network data in locations that are close or easily reachable by most of the vehicles. The protocol performs a geographical routing and is suitable for highly dynamic networks, supporting a high number of mobile sources and destinations of data. It ensures reliable data delivery and fast response. The authors evaluate the performance of the proposed protocol in terms of data delivery ratio and data delivery delay. The simulation results show that HexDD significantly improves the data packet delivery ratio in VANETs.
Reversible molecular pathology of skeletal muscle in spinal muscular atrophy (2011)

Low levels of full-length survival motor neuron (SMN) protein cause the motor neuron disease, spinal muscular atrophy (SMA). Although motor neurons undoubtedly contribute directly to SMA pathogenesis, the role of muscle is less clear. We demonstrate significant disruption to the molecular composition of skeletal muscle in pre-symptomatic severe SMA mice, in the absence of any detectable degenerative changes in lower motor neurons and with a molecular profile distinct from that of denervated muscle. Functional cluster analysis of proteomic data and phospho-histone H2AX labelling of DNA damage revealed increased activity of cell death pathways in SMA muscle. Robust upregulation of voltage-dependent anion-selective channel protein 2 (Vdac2) and downregulation of parvalbumin in severe SMA mice was confirmed in a milder SMA mouse model and in human patient muscle biopsies. Molecular pathology of skeletal muscle was ameliorated in mice treated with the FDA-approved histone deacetylase inhibitor, suberoylanilide hydroxamic acid. We conclude that intrinsic pathology of skeletal muscle is an important and reversible event in SMA and also suggest that muscle proteins have the potential to act as novel biomarkers in SMA.
Effects of a Very Low-Fat, Vegan Diet in Subjects with Rheumatoid Arthritis (2002)

This study showed that patients with moderate-to-severe RA, who switch to a very low-fat, vegan diet can experience significant reductions in RA symptoms.
Analysis of Fluid Extracts Obtained from Papaver rhoeas Petals Contaminated with Papaver bracteatum Petals (2012)

In this paper, we report a case of misidentification of medicinal plants involving dried petals of Papaver rhoeas (red poppy) contaminated with Papaver bracteatum (scarlet poppy) petals. Preliminary TLC analysis indicated the presence of thebaine either in the fluid extracts or in the petals. It was therefore necessary to carry out an accurate botanic examination of the plant material, which revealed contamination of the red poppy petals with scarlet poppy petals. Moreover, to confirm the adulteration, we developed and validated an efficient, reversed-phase ion pair HPLC method for determination of the alkaloids specific for the Papaver species. Six petal batches and five commercial fluid extracts were analyzed. Only one petal batch from Iran contained thebaine and its analogue oripavine while the alkaloids typical for the Papaver bracteatum species were identified in all fluid extracts, meaning that they were all prepared with contaminated petals.
Taxonomic notes on the Acanthopsis disperma-hoffmannseggiana complex (Acanthaceae, tribe Acantheae), with an interim key to members of the genus (2015)

Acanthopsis is a taxonomically poorly understood genus confined to arid parts of southern Africa. This contribution is the first detailed assessment of the diversity within the Acanthopsis disperma-hoffmannseggiana complex, the latter of which comprises the bulk of the specimens of the genus represented in herbaria. Species concepts are resolved and the misapplication of names is noted. In addition to the recognition of A. disperma and A. hoffmannseggiana, five new species of Acanthopsis formerly treated under these two names, are described, namely A. tuba and A. ludoviciana (both confined to the Richtersveld, Northern Cape, South Africa), A. adamanticola (endemic to southern Namibia), A. villosa (endemic to Bushmanland, Northern Cape) and A. dispermoides (endemic to the Western Cape, South Africa). The names A. disperma and A. hoffmannseggiana are lectotypified here. An identification key to the members of the Acanthopsis disperma-hoffmannseggiana complex is provided, as well as an interim key to the major artificial groupings in the genus, the taxonomy of some which still needs to be resolved.
A particle swarm optimization based algorithm for primary user emulation attack detection (2018)

Security in cognitive radio networks is considered as an important problem that is attracting a lot of interest from researchers. One of the main security threats is the Primary User Emulation (PUE) attack, which aims to gain illicit access to the licensed channels. A PUE can mimic the same signal as the real primary user (PU) which requires secondary users (SUs) to free immediately the channel. This attack can result in service degradation, deny of service (DoS), and a considerable impact on the cognitive network. To identify the attacker, nodes need to precisely locate the source of the PU and identify the authenticity of the PU. In the literature, most of localization of unknown signal sources are based on ranging schemes, which measure the distance between the blind node and the anchors. These anchors are static with known positions and are located near the signal source for accurate position detection. The challenge is to have limited number of anchor nodes that can detect the location of the signal. In this paper, we propose a technique based on particle swarm optimization algorithm and the received signal strength indicator (RSSI) for the PU/PUE position detection to increase the detection accuracy and decrease the probability of false alarms.
Mathematical modeling of growth and production of alcohol oxidase by Hansenula polymorpha grown on methanol–glucose mixtures (1989)

The modeling of growth and production of methanol oxidase (MOX) by Hansenula polymorpha CBS 4732 has been studied to provide a mathematical description of such production processes. Two kinds of mathematical models were constructed for growth on methanol and on mixtures of methanol and glucose. The model for growth on methanol as the sole carbon source consists of kinetics expressions, a limited number of key steps incorporating substrate and production inhibition. This model was used to predict and simulate the culture dynamics at the start-up, the most critical step in continuous cultivation. The growth on mixtures of methanol and glucose was modeled assuming virtually independent metabolic pathways. The induction and production of MOX could be described by adaptation of various repression equations for various data from the literature. The models describe both experimental data and literature data on growth of H. polymorpha CBS 4732 on glucose-methanol mixtures satisfactorily. All parameters for the induction-repression model for growth of H. polymorpha CBS 4732 on glucose-methanol mixtures yielded evidence that a similar induction-repression pattern is involved in MOX production. Catalase, however, is repressed by a different mechanism.
Utilization of radar backscattering coefficient from sea surface in rainfall rate retrieval algorithms (1997)

The surface-referenced algorithm, referred as kZS, performs at its best when uncertainty related to sea surface normalized radar cross section (NRCS) is limited. The kZS algorithm is upgraded based on the prediction of the NRCS of the water surface roughened by both wind and rainfall. Such prediction relies on the full wave model (FWM). Improved performance of the rainfall profile retrieval scheme is demonstrated via simulations carried out at 13.75 GHz for different rainfall rates over the sea surface and different rainfall profiles. All of them showed that the rainfall profile retrieval accuracy can greatly benefit from a more accurate prediction of NRCS.
Visualization of Altered Replication Dynamics after DNA Damage in Human Cells (2004)

Eukaryotic cells respond to DNA damage within the S phase by activating an intra-S checkpoint: a response that includes reducing the rate of DNA synthesis. In yeast cells this can occur via checkpoint-dependent inhibition of origin firing and stabilization of ongoing forks, together with a checkpoint-independent slowing of fork movement. In higher eukaryotes, however, the mechanism by which DNA synthesis is reduced is less clear. We have developed strategies based on DNA fiber labeling that allow the quantitative assessment of rates of replication fork movement, origin firing, and fork stalling throughout the genome by examining large numbers of individually labeled replication forks. We show that exposing S phase cells to ionizing radiation induces a transient block to origin firing but does not affect fork rate or fork stalling. Alkylation damage by methyl methane sulfonate causes a slowing of fork movement and a high rate of fork stalling, in addition to inducing a block to new origin firing. Nucleotide depletion by hydroxyurea also reduces replication fork rate and increases stalling; moreover, in contrast to a recent report, we show that hydroxyurea induces a strong block to new origin firing. The DNA fiber labeling strategy provides a powerful new approach to analyze the dynamics of DNA replication in a perturbed S phase.
State‐Space Methods (2006)

Abstract The state space model provides an unifying framework for analyzing time series. For the classical Box–Jenkins analysis, state space methods are useful when estimating the autoregressive and moving average coefficients by exact maximum likelihood and when missing values are present. In the case of unobserved components time series models with interpretable components such as trend, seasonal, cycle and irregular, state space methods provide the tools for estimation, signal extraction and diagnostic checking. Indeed, all linear time series models can be cast into state space including dynamic regression models and cubic spline smoothing models.
Behavioral Patterns in Smartphone Usage Predict Big Five Personality Traits (2019)

The understanding, quantification and evaluation of individual differences in behavior, feelings and thoughts have always been central topics in psychological science. An enormous amount of previous work on individual differences in behavior is exclusively based on data from self-report questionnaires. To date, little is known about how individuals actually differ in their objectively quantifiable behaviors and how differences in these behaviors relate to big five personality traits. Technological advances in mobile computer and sensing technology have now created the possiblity to automatically record large amounts of data about humans' natural behavior. The collection and analysis of these records makes it possible to analyze and quantify behavioral differences at unprecedented scale and efficiency. In this study, we analyzed behavioral data obtained from 743 participants in 30 consecutive days of smartphone sensing (25,347,089 logging-events). We computed variables (15,692) about individual behavior from five semantic categories (communication &amp;amp; social behavior, music listening behavior, app usage behavior, mobility, and general day- &amp;amp; nighttime activity). Using a machine learning approach (random forest, elastic net), we show how these variables can be used to predict self-assessments of the big five personality traits at the factor and facet level. Our results reveal distinct behavioral patterns that proved to be differentially-predictive of big five personality traits. Overall, this paper shows how a combination of rich behavioral data obtained with smartphone sensing and the use of machine learning techniques can help to advance personality research and can inform both practitioners and researchers about the different behavioral patterns of personality.
Artificial intelligence-enabled event adjudication: estimating delayed cardiovascular effects of respiratory viruses (2020)

Abstract Healthcare systems ideally should be able to draw lessons from historical data, including whether common exposures are associated with adverse clinical outcomes. Unfortunately, structured clinical data, such as encounter diagnostic codes in electronic health records, suffer from multiple limitations and biases, limiting effective learning. We hypothesized that a machine learning approach to automate ascertainment of clinical events and disease history from medical notes would improve upon using structured data and enable the estimation of real-world risks. We sought to test this approach to address a timely goal: estimating the delayed risk of adverse cardiovascular events (i.e. after the index infection) in patients infected with respiratory viruses. Using 4,151 cardiologist-labeled notes as gold standard, we trained a series of neural network models to automate event adjudication for heart failure hospitalization, acute coronary syndrome, stroke, and coronary revascularization and to identify past medical history for heart failure. Though performance varied by task, in nearly all cases, our models surpassed the use of structured data in terms of sensitivity for a given specificity level and enabled principled evaluation of classification thresholds, which is typically impossible to do with diagnostic codes. Deploying our models on more than 17 million notes for 267,596 patients across an extensive integrated delivery network, we found that patients infected with respiratory syncytial virus had a 23% increased risk of delayed heart failure hospitalization over a subsequent 4-year period compared with propensity-score matched patients who had the same test but with negative results (p = 0.003, log-rank). In contrast, we found no such increased risk in patients with a positive influenza viral test compared with a negative test (rate ratio 0.98, p = 0.71). We conclude that convolutional neural network-based models enable accurate clinical labeling at scale, thereby unlocking timely insights from unstructured clinical data.
Direct fed microbial supplementation repartitions host energy to the immune system1 (2012)

Direct fed microbials and probiotics are used to promote health in livestock and poultry; however, their mechanism of action is still poorly understood. We previously reported that direct fed microbial supplementation in young broilers reduced ileal respiration without changing whole-body energy expenditure. The current studies were conducted to further investigate the effects of a direct fed microbial on energy metabolism in different tissues of broilers. One hundred ninety-two 1-d-old broiler chicks (16 chicks/pen) were randomly assigned to 2 dietary groups: standard control starter diet (CSD) and CSD plus direct fed microbial (DFMD; 0.3%) with 6 pens/treatment. Body weight, feed consumption, whole-body energy expenditure, organ mass, tissue respiration rates, and peripheral blood mononuclear cell (PBMC) ATP concentrations were measured to estimate changes in energy metabolism. No differences in whole body energy expenditure or BW gain were observed; however, decreased ileal O(2) respiration (P < 0.05) was measured in DFMD fed broilers. In contrast, the respiration rate of the thymus in those broilers was increased (P < 0.05). The PBMC from DFMD fed broilers had increased ATP concentrations and exhibited increased ATP turnover (P < 0.01). To determine if the increased energy consumption by PBMC corresponded with an altered immune response, broilers were immunized with sheep red blood cells (SRBC) and assayed for differences in their humoral response. The DFMD-fed broilers had a faster rate of antigen specific IgG production (P < 0.05) and an increase in total IgA (P < 0.05). Collectively, these data indicate that supplementation with the direct fed microbial used in this study resulted in energy re-partitioning to the immune system and an increase in antibody production independent of changes in whole body metabolism or growth performance.
SPEQTACLE: A new fuzzy clustering algorithm for fully automatic delineation of tumors in PET images (2014)

International audience
Preferred Phosphorus Ylide Formation Upon Alkylation of Lithiobis(diphenylphosphanyl)acetonitrile (2007)

Abstract Deprotonation of the readily available chelate phosphane bis(diphenylphosphanyl)acetonitrile ( 6 ) leads to stabilized carbanion system 7 . Lithiobis(diphenylphosphanyl)acetonitrile ( 7 ) features a unique thf‐stabilized monomeric structure in the crystal form with a short cyanonitrogen–Li contact. Alkylation of 7 with n ‐alkyl bromides (R–Br, R = ethyl, n ‐propyl, n ‐butyl, n ‐hexyl) takes place selectively at one phosphorus atom to yield stabilized ylides 8a – d (two examples characterized by X‐ray diffraction). Treatment of 7 with the more reactive alkylation agents methyl iodide or benzyl bromide results in alkylation at both phosphorus atoms to give delocalized bis(phosphonium)ylides 9a , b (both characterized by X‐ray diffraction). Similarly, the reaction of 7 with 1,3‐dibromopropane or 1,4‐dibromobutane yields six‐ and seven‐membered heterocyclic bis(phosphonium)ylides 10a , b , respectively. The spectroscopic characterization and X‐ray crystal structure analysis again indicate the presence of delocalized Ph 2 RP–C(CN)–PRPh 2 substructures. (© Wiley‐VCH Verlag GmbH &amp; Co. KGaA, 69451 Weinheim, Germany, 2007)
Understanding nanocellulose chirality and structure–properties relationship at the single fibril level (2015)

Nanocellulose fibrils are ubiquitous in nature and nanotechnologies but their mesoscopic structural assembly is not yet fully understood. Here we study the structural features of rod-like cellulose nanoparticles on a single particle level, by applying statistical polymer physics concepts on electron and atomic force microscopy images, and we assess their physical properties via quantitative nanomechanical mapping. We show evidence of right-handed chirality, observed on both bundles and on single fibrils. Statistical analysis of contours from microscopy images shows a non-Gaussian kink angle distribution. This is inconsistent with a structure consisting of alternating amorphous and crystalline domains along the contour and supports process-induced kink formation. The intrinsic mechanical properties of nanocellulose are extracted from nanoindentation and persistence length method for transversal and longitudinal directions, respectively. The structural analysis is pushed to the level of single cellulose polymer chains, and their smallest associated unit with a proposed 2 × 2 chain-packing arrangement.
Microsomal metabolism of nitrosoureas. (1975)

N, N-Bis (2-chloroethyl)-N-nitrosourea (BCNU) is a substrate for a microsomal enzyme of mouse liver. The reaction requires NADPH, and the product is 1, 3-bis (2-chloroethyl) urea. This activity is also found in mouse lungs but not in several other tissues. With reaction conditions under which BCNU is not chemically degraded, the Km for BCNU with liver microsomes is 1.7 mM; nicotine is a competitive inhibitor with a Ki of 0.6 mM. N-Methyl-N-nitrosourea is denitrosated in a similar reaction. N- (2-Chloroetyhy)- N-cyclohexyl-N-nitrosourea and N-(2-chloroethyl)-N-(trans-4-methylcyclohexyl)-N-nitrosourea are also substrates for microsomal enzymes, but the products of these reactions are ring-hydroxylated derivatives. The Km value for N-(2-CHLOROETHYL)-N-cyclohexyl-N-nitrosourea is 3.0 mM and that for N-(2-chloroethyl)-N-(trans-4-methylcyclohexyl)-N-nitrosourea is 1.0 mM. The hydroxylase activity is also present in lungs, but not in the other mouse tissues. The rates of microsomal metabolism of BCNU, N-(2-chloroethyl)-N-cyclohexyl-N-nitrosourea, and N-(2-chloroethyl)-N-cyclohexyl-N-nitrosourea, and N-(2-chloroethyl-N-(trans-4-methylcyclohexyl)-N-nitrosourea are fast enough to allow metabolism of large portions of administered doses before chemical decomposition of the drugs occurs.