Miracle-dz/UniFAR-FTUs huggingface dataset:
Methylation status of p16 and p14 genes in locally advanced rectal cancer: potential clinical implication

Paper description: Patients’ response to standard treatment of locally advanced rectal cancer is variable. Many tested molecular parameters have failed to become reliable predictive biomarkers. Promotor hypermethylation of p16 and p14 genes has been frequently reported as an early event in colorectal cancer, but its clinical relevance in rectal cancer, as a distinct entity, has not been established. Combined analysis of p16 and p14 methylation and VEGF expression status could potentially predict a more aggressive phenotype of locally advanced rectal cancer. Aberrant p16 or p14 methylation, together with high vascular endothelial growth factor (VEGF) expression, is significantly associated with a worse treatment response. Abstract: Methylation of p16 and p14 genes is a common event in colorectal cancers; however, their exact role in the prediction of patients’ outcome is unclear. We conducted this retrospective study to evaluate their potential predictive and/or prognostic roles. Methylation-specific PCR was used to examine the methylation status of p16 and p14 in pretherapeutic and preoperative biopsy specimens of 60 patients with locally advanced rectal cancer. The methylation status of the examined genes did not affect the response to preoperative chemoradiotherapy (CRT), recurrence rate and overall survival. However, patients with a simultaneous presence of either p16 or p14 methylation and high vascular endothelial growth factor (VEGF) expression showed a significantly worse response to CRT ( p =0.005 and p =0.038, respectively). Moreover, patients with both p16 methylation and high VEGF expression had significantly shorter overall survival ( p =0.010), while no such association was found in patients with p14 methylation and high VEGF expression. On the other hand, a subgroup of patients with p16 methylation and low VEGF and high epidermal growth factor receptor (EGFR) expression showed a significantly better response to CRT ( p =0.024). The obtained results point to the importance of p16 and p14 methylation analyses in combination with VEGF and EGFR expression, aimed at better predicting treatment response and patient outcome. https://doi.org/10.2298/ABS180316030K Received: March 16, 2018; Revised: June 13, 2018; Accepted: June 13, 2018; Published online: June 19, 2018 How to cite this article: Kožik B, Kokanov N, Kneževic-Usaj S, Nikolic I, Davidovic R, Jovanovic-Cupic S, Krajnovic M. Methylation status of p16 and p14 genes in locally advanced rectal cancer: Potential clinical implication. Arch Biol Sci. 2018;70(4):681-90.
Large-Scale Influences on Atmospheric River–Induced Extreme Precipitation Events along the Coast of Washington State

Transient, narrow plumes of strong water vapor transport, referred to as atmospheric rivers (ARs), are responsible for much of the precipitation along the West Coast of the United States. The most intense precipitation events are almost always induced by an AR on the coast of Oregon and Washington and can result in detrimental impacts on society due to mudslides and flooding. To accurately predict AR events on numerical weather prediction, subseasonal, and seasonal time scales, it is important to understand the large-scale impacts on extreme AR events. Here, characteristics of ARs that result in an extreme precipitation event are compared to typical ARs on the coast of Washington State. In addition to more intense water vapor transport, notable differences in the synoptic forcing are present during extreme precipitation events that are not present during typical AR events. Subseasonal and seasonal teleconnection patterns are known to influence the weather in the Pacific Northwest and are investigated here. The Madden–Julian oscillation (MJO) plays a role in determining the strength of precipitation associated with an AR on the Washington coast. Phase 5 of the MJO (convection centered over the Maritime Continent) is the most common phase during an extreme precipitation event, while phase 2 (convection over the Indian Ocean) discourages an extreme event from occurring. Interactions between El Niño–Southern Oscillation (ENSO) and the propagation speed of the MJO result in extreme events during phase 1 of the MJO and El Niño but phase 8 during neutral ESNO conditions.
Elaborating on modular interfaces in multi-provider contexts

PurposeThis study examines how modular interfaces manifest in multi-provider contexts and how they can improve coordination and customization of services. The aim of the study is to describe interfaces in multi-provider contexts and elaborate on how they support the delivery of integrated patient care.Design/methodology/approachA qualitative, multiple case study was conducted in two multi-provider contexts in healthcare services: one representing paediatric Down syndrome care in the Netherlands and one representing home care for the elderly in Finland. Data collection involved semi-structured interviews in both contexts.FindingsThis study provides insight into several types of interfaces and their role in multi-provider contexts. Several inter- and intra-organizational situations were identified in which the delivery of integrated patient care was jeopardized. This study describes how interfaces can help to alleviate these situations.Originality/valueThis study deepens the understanding of interfaces in service modularity by describing interfaces in multi-provider contexts. The multi-provider contexts studied inspired to incorporate the inter-organizational aspect into the literature on interfaces in service modularity. This study further develops the typology for interfaces in modular services by adding a third dimension to the typology, that is, the orientation of interfaces.
Secure Key Agreement and Authentication Protocol for Message Confirmation in Vehicular Cloud Computing

With the development of vehicular ad-hoc networks (VANETs) and Internet of vehicles (IoVs), a large amount of useful information is generated for vehicle drivers and traffic management systems. The amount of vehicle and traffic information is as large as the number of vehicles and it is enormous when compared to vehicle calculation and storage performance. To resolve this problem, VANET uses a combined cloud computing technology, called vehicular cloud computing (VCC), which controls vehicle-related data, and helps vehicle drivers directly or indirectly. However, VANETs remain vulnerable to attacks such as tracking, masquerade and man-in-the-middle attacks because VANETs communicate via open networks. To overcome these issues, many researchers have proposed secure authentication protocols for message confirmation with vehicular cloud computing. However, many researchers have pointed out that some proposed protocols use ideal tamper-proof devices (TPDs). They demonstrated that realistic TPDs cannot prevent adversaries attack. Limbasiya et al. presented a message confirmation scheme for vehicular cloud computing using a realistic TPD in order to prevent these problems. However, their proposed scheme still has security weaknesses over a TPD and does not guarantee mutual authentication. This paper proposes a secure key agreement and authentication protocol to address the security weaknesses inherent in the protocol of Limbasiya et al. The suggested protocol withstands malicious attacks and ensures secure mutual authentication for privacy-preserving. We prove that the proposed protocol can provide session key security using Real-Or-Random (ROR) model. We also employed Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool to show that the proposed protocol is able to defeat replay and man-in-the-middle attacks. Furthermore, we established that the proposed protocol can resist other malicious attacks by conducting the informal security analysis. We proved that our proposed protocol is lightweight and suitable for VCC environments.
A Comparative Study of the Physical Changes of Two Soluble Fibers during In Vitro Digestion

This research aimed to compare the apparent viscosity and the degree of fragmentation/aggregation produced in dispersions of xanthan gum and chia mucilage during the gastrointestinal tract by using an in vitro digestion. Both soluble fibers exhibited pseudoplastic behavior, independent of the concentration and stage of digestion (oral, gastric or intestinal). The viscosity decreased from the oral to intestinal stage in all the concentrations, produced mainly by the “dilution effect” by the addition of digestive fluids. The particle size of xanthan gum increased drastically in the gastric stage mainly due to the decrease in pH, but at intestinal level returned to its original pattern, while particle size and pattern of mucilage during all the stages of digestion remained unchanged, maintaining its integrity. In general terms, since chia mucilage and xanthan gum maintain their viscosity and integrity through the gastrointestinal tract, they could be used as functional ingredients improving the functionality of foods.
A perfect functional marker for the gene of intermediate amylose content Wx-in in rice (Oryza sativa L.)

The amylose content (AC) of rice is a key determinant of the grain cooking and eating quality. The Waxy (Wx) gene, which encodes granulebound starch synthase I (GBSSI), is the major gene controlling AC in rice. The A C substitution in exon 6 (Ex6A/C) alters the amino acid codon from serine to tyrosine and is associated with intermediate-AC rice (Wx-in). In this paper, we reported a perfect functional marker for the SNP Ex6A/C of Wx-in based on polymerase chain reaction with confronting two-pair primers (PCR-CTPP) in a single-tube PCR assay. Specificity and applicability of the PCR assay were verified in a Chinese mini core collection (MCC) of Oryza sativa L. and a breeding population. We recommend the use of the simple, inexpensive assay for routine genotyping for intermediate AC in the breeding population or discrimination of Wx-in genotypes in rice germplasm.
Recent Approaches to Chiral 1,4-Dihydropyridines and their Fused Analogues

The purpose of this review is to highlight recent developments in the synthesis of chiral 1,4-dihydropyridines and their fused analogues. 1,4-Dihydropyridines are among the most active calcium antagonists that are used for the treatment of hypertension. Enantiomers of unsymmetrical 1,4-dihydropyridines often show different biological activities and may have even an opposite action profile. Hantzsch synthesis usually produces racemic mixtures of unsymmetrical 1,4-dihydropyridines. Therefore, the development of stereoselective synthesis of 1,4-dihydropyridines is one of the priorities of medicinal chemistry. Over the years, numerous methodologies have been developed for the production of enantiopure 1,4-dihydropyridines, such as stereoselective synthesis using chiral auxiliaries and chiral cyclocondensation partners, chromatographical methods, resolution of diastereomeric 1,4-dihydropyridine salts, enzyme catalysed kinetic resolution, or asymmetrisation of ester groups of 1,4-dihydropyridines. These approaches have been studied in detail and are relatively well established. The catalytic asymmetric approach holds the greatest promise in delivering the most practical and widely applicable methods. Substantial progress has been made toward the development of enantioselective organocatalytic methods for the construction of the chiral dihydropyridines. However, most of them do not provide a convenient way to pharmacologically important 1,4-dihydropyridine-3,5-dicarboxylates. Organocatalytic enantioselective desymmetrisation of prochiral 1,4-dihydropyridine-3,5-dicarbaldehydes also has great promise in the synthesis of pharmacologically important 1,4-dihydropyridine-3,5-dicarboxylates.
Modeling Indoor Particulate Matter and Small Ion Concentration Relationship—A Comparison of a Balance Equation Approach and Data Driven Approach

In this work we explore the relationship between particulate matter (PM) and small ion (SI) concentration in a typical indoor elementary school environment. A range of important air quality parameters (radon, PM, SI, temperature, humidity) were measured in two elementary schools located in urban background and suburban area in Belgrade city, Serbia. We focus on an interplay between concentrations of radon, small ions (SI) and particulate matter (PM) and for this purpose, we utilize two approaches. The first approach is based on a balance equation which is used to derive approximate relation between concentration of small ions and particulate matter. The form of the obtained relation suggests physics based linear regression modelling. The second approach is more data driven and utilizes machine learning techniques, and in this approach, we develop a more complex statistical model. This paper attempts to put together these two methods into a practical statistical modelling approach that would be more useful than either approach alone. The artificial neural network model enabled prediction of small ion concentration based on radon and particulate matter measurements. Models achieved median absolute error of about 40 ions/cm3 and explained variance of about 0.7. This could potentially enable more simple measurement campaigns, where a smaller number of parameters would be measured, but still allowing for similar insights.
A bioinspired piezocomposite propulsor: An electromechanical model

This article presents an experimentally validated electromechanical beam model for a representative cymbal-like piezocomposite active segment of a bioinspired piezocomposite aquatic propulsor/pump. The proposed concept is a self-contained propulsion/pumping system involving a series of piezoactive soft cymbal-like segments that are connected by passive soft connective segments. A series of phased excitations in expansion and contraction applied to active segments create a traveling wave along the axis of the pump, which in return propels the fluid. A parametric analysis is conducted using the proposed model to understand the effectiveness of the cymbal-like piezocomposite active segment as a function of critical structural parameters. Area change of the cymbal-like actuators, which is correlated to the propulsion power, is studied based on the analysis of the induced moment, curvature, and area change due to piezoelectric excitation. Objective functions and criteria are proposed and evaluated to understand the effectiveness, and to identify the optimal structural parameters of the piezocomposite pump. The influence of a sealant layer for waterproofing is also examined. Both bimorph and unimorph configurations are analyzed, and the results are compared.
Automatic extraction of sophisticated qualitative trajectory relationships between two moving objects in space‐time

A comparison of moving objects’ trajectories in space‐time based on descriptive and qualitative interpretations is useful in many GIS‐related studies. Qualitative relationships help to answer questions such as “Do the objects meet each other? ” or “Do the objects move towards or away from each other? ” Questions about moving objects can be efficiently addressed using quantitative and computational techniques such as data mining of trajectory datasets but expressed in terms of qualitative relationships. It is, however, difficult to recognize these qualitative relationships when the trajectories are large and consist of many parts, where a sophisticated qualitative relationship can be formed from the aggregation of simple ones. For this reason, this study introduces two classes of trajectory relationships: initial qualitative trajectory relationships (IQTR) and combinatory qualitative trajectory relationships (CQTR). It also suggests effective algorithmic approaches to automatically retrieve them. The proposed algorithm for IQTR using min‐heap and linked‐list data structure could effectively reduce the time complexity from O(n2) to O(n log n). For CQTRs, a divide‐and‐conquer and recursive technique and a linked‐path structure again managed to reduce the time complexity from O(n2) to O(n log n). Finally, experiments on large datasets suggest the capability of the proposed methods in terms of performance and stability.
Laboratory examination of the physical properties of ordinary chondrites

Meteorites provide vast amounts of information on the makeup and history of the solar system. The physical properties help to understand meteor behavior in the atmosphere, model characteristics of parent bodies, and determine methods to deflect potentially hazardous objects. Density and porosity are two of the most important physical properties. All the examined ordinary chondrite falls have bulk densities and porosities near their respected class averages. Most of the studied Antarctic ordinary chondrites have porosities around 12% or higher caused by weathering, placing them near the top of the range of values for chondritic falls. A trend is observed in acoustic velocity, where any meteorite with porosity over 10% has a longitudinal velocity near half the value of the class average. Low porosity meteorites such as Tenham, Chelyabinsk impact melt, and MIL07036 have velocities well above their class averages. Emissivities across all meteorites follow the trend of decreasing emissivity with increasing temperature.
Impact of Irrigation Frequency and Planting Density on Bean’s Morpho-Physiological and Productive Traits

The correct irrigation frequency relies on the plant population density to increase yield and efficiency in water use. A field experiment was carried out in 2019 to study the effect of three irrigation frequencies, one (F1), four (F2), and eight (F3) days, and four planting densities, 20 (D1), 24 (D2), 28 (D3), and 30 (D4) plants per m2, on the variables: soil moisture, actual water consumption, growth, grain yield, and water productivity of beans (Phaseolus vulgaris L.). The soil water balance was calculated based on the soil moisture, which was measured by tensiometers. The irrigation was done by a drip tape. The variation in soil moisture was greatly influenced by irrigation frequencies and planting densities in F3. Plant growth was not affected by treatments. Irrigation frequencies and planting densities have deeply affected the biometric and chlorophyll synthesis traits of beans. The highest yields were found in the treatments F1D3 (2968 kg ha−1), F1D4 (2997 kg ha−1), and F3D3 (2946 kg ha−1). For water productivity, treatments with F1 irrigation frequency and the higher planting densities were more efficient in water use. Overall, the results are useful for technicians and farmers who work with irrigation management on beans.
Deep learning–based roadway crack classification with heterogeneous image data fusion

By providing accurate and efficient crack detection and localization, image-based crack detection methodologies can facilitate the decision-making and rehabilitation of the roadway infrastructure. Deep convolutional neural network, as one of the most prevailing image-based methodologies on object recognition, has been extensively adopted for crack classification tasks in the recent decade. For most of the current deep convolutional neural network–based techniques, either intensity or range image data are utilized to interpret the crack presence. However, the complexities in real-world data may impair the robustness of deep convolutional neural network architecture in its ability to analyze image data with various types of disturbances, such as low contrast in intensity images and shallow cracks in range images. The detection performance under these disturbances is important to protect the investment in infrastructure, as it can reveal the trend of crack evolution and provide information at an early stage to promote precautionary measures. This article proposes novel deep convolutional neural network–based roadway classification tools and investigates their performance from the perspective of using heterogeneous image fusion. A vehicle-mounted laser imaging system is adopted for data acquisition (DAQ) on concrete roadways with a depth resolution of 0.1 mm and an accuracy of 0.4 mm. In total, four types of image data including raw intensity, raw range, filtered range, and fused raw image data are utilized to train and test the deep convolutional neural network architectures proposed in this study. The experimental cases demonstrate that the proposed data fusion approach can reduce false detections and thus results in an improvement of 4.5%, 1.2%, and 0.7% in the F-measure value, respectively, compared to utilizing the raw intensity, raw range, and filtered range image data for analysis. Furthermore, in another experimental case, two novel deep convolutional neural network architectures proposed in this study are compared to exploit the fused raw image data, and the one leading to better classification performance is determined.
COMPARATIVE ANALYSIS OF SPLIT-WINDOW AND SINGLE-CHANNEL ALGORITHMS FOR LAND SURFACE TEMPERATURE RETRIEVAL OF A PSEUDO-INVARIANT TARGET

Land surface temperature (LST) acquired from remote sensing observations is essential to monitor surface energy and water exchange processes at the land-atmosphere interface. Most LST retrieval methodologies are developed focusing on Northern hemisphere. Consequently, Southern hemisphere has a great need for investigating the performance of LST retrieval algorithms already consolidated in the literature. In this paper, we compared a Splitwindow (SW) and a Single-channel (SC) method to retrieve LST from Landsat 8 OLI/TIRS images in a dune field, Southern Brazil. To validate the results, the Atmospheric Correction Parameter Calculator (ACPC) tool and Radiative Transfer Equation (RTE) were used. Results demonstrated that both methodologies are in accordance with the RTE, despite they overestimated the LST. Analysis of variance (ANOVA) indicated that the means are not statistically significant (0.05 level). The correlations between LST retrieved and RTE were strong, producing R² of 0.984 and 0.973 for the SW and SC, respectively, and RMSE values of 1.18 and 1.6. SW also exhibited the best values of MSD (±0.983) and Bias (0.773), thus reinforcing its superior performance. SW can be applied with an accuracy of 1.18 K in Southern Brazil, without needing complex modeling or specific radiosonde.
A study to determine the value of pre operative hyperbilirubinemia as a predictor of complicated appendicitis

Acute appendicitis is the commonest cause of ‘acute surgical abdomen’. Appendicectomy is the most frequently performed urgent abdominal operation and is often the first major procedure performed by a surgeon in training. Diagnosis of appendicitis is based on history, examination, laboratory values and imaging. In some cases, the signs and symptoms are variable and a diagnosis can be difficult to make. Delay in diagnosis of acute appendicitis leads to perforation and peritonitis and increased mortality. Incidence of perforation ranges 5090% in various series.