bluuebunny/crossref_metadata_2025_split huggingface dataset:
Triclosan-coated barbed sutures in elective laparoscopic colorectal cancer surgery: a propensity score matched cohort study
Authors: Pla-Martí Vicente , Martín-Arévalo José , Moro-Valdezate David , García-Botello Stephanie , Pérez-Santiago Leticia , Izquierdo-Moreno Ana , Muñoz-Sornosa Ernesto , Espí-Macías Alejandro 
Published: August 2022

Abstract
Background
Most of the studies published to date which assess the role of antibacterial sutures in surgical site infection (SSI) prevention include heterogeneous groups of patients, and it is therefore difficult to draw conclusions. The objective of the present study was to investigate whether the use of Triclosan-coated barbed sutures (TCBS) was associated with a lower incidence of incisional SSI and lower duration of hospital stay compared to standard sutures, in elective laparoscopic colorectal cancer surgery.

Method
Observational including patients who underwent elective colorectal cancer laparoscopic surgery between January 2015 and December 2020. The patients were divided into two groups according to the suture used for fascial closure of the extraction incision, TCBS vs conventional non-coated sutures (CNCS), and the rate of SSI was analysed. The TCBS cases were matched to CNCS cases by propensity score matching to obtain comparable groups of patients.

Results
488 patients met the inclusion criteria. After adjusting the patients with the propensity score, two new groups of patients were generated: 143 TCBS cases versus 143 CNCS cases. Overall incisional SSI appeared in 16 (5.6%) of the patients with a significant difference between groups depending on the type of suture used, 9.8% in the group of CNCS and 1.4% in the group of TCBS (OR 0.239 (CI 95%: 0.065–0.880)). Hospital stay was significantly shorter in TCBS group than in CNCS, 5 vs 6 days (p < 0.001).

Conclusion
TCBS was associated with a lower incidence of incisional SSI compared to standard sutures in a cohort of patients undergoing elective laparoscopic colorectal cancer surgery.

Graphical abstract
A genetic programming-based approach for classifying pancreatic adenocarcinoma: the SICED experience
Authors: D’Angelo Gianni , Scoppettuolo Maria Nunzia , Cammarota Anna Lisa , Rosati Alessandra , Palmieri Francesco 
Published: July 2022

AbstractDuctal adenocarcinoma of the pancreas is a cancer with a high mortality rate. Among the main reasons for this baleful prognosis is that, in most patients, this neoplasm is diagnosed at a too advanced stage. Clinical oncology research is now particularly focused on decoding the cancer molecular onset by understanding the complex biological architecture of tumor cell proliferation. In this direction, machine learning has proved to be a valid solution in many sectors of the biomedical field, thanks to its ability to mine useful knowledge by biological and genetic data. Since the major risk factor is represented by genetic predisposition, the aim of this study is to find a mathematical model describing the complex relationship existing between genetic mutations of the involved genes and the onset of the disease. To this end, an approach based on evolutionary algorithms is proposed. In particular, genetic programming is used, which allows solving a symbolic regression problem through the use of genetic algorithms. The identification of these correlations is a typical objective of the diagnostic approach and is one of the most critical and complex activities in the presence of large amounts of data that are difficult to correlate through traditional statistical techniques. The mathematical model obtained highlights the importance of the complex relationship existing between the different gene’s mutations present in the tumor tissue of the group of patients considered.
Omics profiles of fecal and oral microbiota change in irritable bowel syndrome patients with diarrhea and symptom exacerbation
Authors: Tanaka Yukari , Yamashita Riu , Kawashima Junko , Mori Hiroshi , Kurokawa Ken , Fukuda Shinji , Gotoh Yasuhiro , Nakamura Keiji , Hayashi Tetsuya , Kasahara Yoshiyuki , Sato Yukuto , Fukudo Shin 
Published: July 2022

Abstract
Background
Irritable bowel syndrome (IBS) is a disorder of gut–brain interaction, including dysregulation of the hypothalamic–pituitary–adrenal axis with salivary cortisol changes. However, the role of gastrointestinal microbiota during IBS symptom exacerbation remains unclear. We tested the hypothesis that the microbial species, gene transcripts, and chemical composition of fecal and oral samples are altered during the exacerbation of IBS symptoms.

Methods
Fecal, salivary, and dental plaque samples were collected at baseline from 43 men with IBS with diarrhea (IBS-D) and 40 healthy control (HC) men. Samples in the IBS-D patients were also collected during symptom exacerbation. The composition of the fecal microbiota was determined by analyzing the 16S rRNA gene, RNA-based metatranscriptome, and metabolites in samples from HC and IBS patients with and without symptom exacerbation. Oral samples were also analyzed using omics approaches.

Results
The fecal microbiota during IBS symptom exacerbation exhibited significant differences in the phylogenic pattern and short-chain fatty acid compared with fecal samples during defecation when symptoms were not exacerbated. Although there were no significant differences in the phylogenic pattern of fecal microbiota abundance between HCs and IBS-D patients, significant differences were detected in the expression patterns of bacterial transcriptomes related to butyrate production and neuroendocrine hormones, including tryptophan-serotonin-melatonin synthesis and glutamine/GABA. The composition of plaque microbiota was different between HC and IBS-D patients during normal defecation.

Conclusions
Our findings suggest that colonic host-microbial interactions are altered in IBS-D patients during exacerbation of symptoms. There were no overlaps between feces and oral microbiomes.
Recycled aggregates derived from excavation materials—mechanical performance and identification of weak minerals
Authors: Adomako Solomon , Engelsen Christian John , Danner Tobias , Thorstensen Rein Terje , Barbieri Diego Maria 
Published: July 2022

AbstractThe present study investigates the mechanical performance of recycled aggregates derived from excavation materials (REM). REM is blended with different quantities of recycled phyllite materials (RPM) and is investigated by Los Angeles (LA) and micro-Deval (MD) tests. X-ray diffraction (XRD) and acid solubility test are performed on the pulverized fractions < 1.6 mm obtained from the LA and MD tests to assess the respective degree of fragmentation and wear of mineral components. The results of the materials in unblended conditions showed considerable difference between MD performance while similar performance was found for LA. Furthermore, about 40% of RPM was sufficient to blend with REM without disturbing the required performance for blended mixtures. Mechanically weak minerals, i.e., phyllosilicates in RPM, significantly influenced the MD performance in blended and unblended varieties, and limestone minerals seem to disintegrate when mixed with amphibolite -which has the potential to dissolve in acidic environments.
Node connectivity augmentation via iterative randomized rounding
Authors: Angelidakis Haris , Hyatt-Denesik Dylan , Sanità Laura 
Published: August 2022

AbstractMany network design problems deal with the design of low-cost networks that are resilient to the failure of their elements (such as nodes or links). One such problem is Connectivity Augmentation, with the goal of cheaply increasing the (edge- or node-)connectivity of a given network from a valuekto$$k+1$$k+1. The problem is NP-hard for$$k \ge 1$$k≥1, and the most studied setting focuses on the case of edge-connectivity with$$k=1$$k=1. In this work, we give a 1.892-approximation algorithm for the NP-hard problem of augmenting the node-connectivity of any given graph from 1 to 2, which improves upon the state-of-the-art approximation previously developed in the literature. The starting point of our work is a known reduction from Connectivity Augmentation to some specific instances of the Node-Steiner Tree problem, and our result is obtained by developing a new and simple analysis of the iterative randomized rounding technique when applied to such Steiner Tree instances. Our results also imply a 1.892-approximation algorithm for the problem of augmenting the edge-connectivity of a given graph from any valuekto$$k+1$$k+1. While this does not beat the best approximation factor known for this problem, a key point of our work is that the analysis of our approximation factor is less involved when compared to previous results in the literature. In addition, our work gives new insights on the iterative randomized rounding method, that might be of independent interest.
gRosSo: mining statistically robust patterns from a sequence of datasets
Authors: Tonon Andrea , Vandin Fabio 
Published: August 2022

AbstractPattern mining is a fundamental data mining task with applications in several domains. In this work, we consider the scenario in which we have a sequence of datasets generated by potentially different underlying generative processes, and we study the problem of mining statistically robust patterns, which are patterns whose probabilities of appearing in transactions drawn from such generative processes respect well-defined conditions. Such conditions define the patterns of interest, describing the evolution of their probabilities through the datasets in the sequence, which may, for example, increase, decrease, or stay stable, through the sequence. Due to the stochastic nature of the data, one cannot identify the exact set of the statistically robust patterns by analyzing a sequence of samples, i.e., the datasets, taken from the generative processes, and has to resort to approximations. We then propose gRosSo, an algorithm to find rigorous approximations of the statistically robust patterns that do not contain false positives or false negatives with high probability. We apply our framework to the mining of statistically robust sequential patterns and statistically robust itemsets. Our extensive evaluation on pseudo-artificial and real data shows that gRosSo provides high-quality approximations for the problem of mining statistically robust sequential patterns and statistically robust itemsets.
Reducing the basic reproduction number of COVID-19: a model simulation focused on QALYs, hospitalisation, productivity costs and optimal (soft) lockdown
Authors: Robles-Zurita Jose 
Published: August 2022

AbstractEven if public health interventions are successful at reducing the spread of COVID-19, there is no guarantee that they will bring net benefits to the society because of the dynamic nature of the pandemic, e.g., the risk of a second outbreak if those interventions are stopped too early, and the costs of a continued lockdown. In this analysis, a discrete-time dynamic model is used to simulate the effect of reducing the effective reproduction number, driven by lockdowns ordered in March 2020 in four European countries (UK, France, Italy and Spain), on QALYs and hospitalisation costs. These benefits are valued in monetary terms (€30,000 per QALY assumed) and compared to productivity costs due to reduced economic activity during the lockdown. An analysis of the optimal duration of lockdown is performed where a net benefit is maximised. The switch to a soft lockdown is analysed and compared to a continued lockdown or no intervention. Results vary for two assumptions about hospital capacity of the health system: (a) under unlimited capacity, average benefit ranges from 8.21 to 14.21% of annual GDP, for UK and Spain, respectively; (b) under limited capacity, average benefits are higher than 30.32% of annual GDP in all countries. The simulation results imply that the benefits of lockdown are not substantial unless continued until vaccination of high-risk groups is complete. It is illustrated that lockdown may not bring net benefits under some scenarios and a soft lockdown will be a more efficient alternative from mid-June 2020 only if the basic reproduction number is maintained low (not necessarily below 1) and productivity costs are sufficiently reduced.
Automatic detection of airborne pollen: an overview
Authors: Buters Jeroen , Clot Bernard , Galán Carmen , Gehrig Regula , Gilge Stefan , Hentges François , O’Connor David , Sikoparija Branko , Skjoth Carsten , Tummon Fiona , Adams-Groom Beverley , Antunes Célia M. , Bruffaerts Nicolas , Çelenk Sevcan , Crouzy Benoit , Guillaud Géraldine , Hajkova Lenka , Seliger Andreja Kofol , Oliver Gilles , Ribeiro Helena , Rodinkova Victoria , Saarto Annika , Sauliene Ingrida , Sozinova Olga , Stjepanovic Barbara 
Published: July 2022

AbstractPollen monitoring has traditionally been carried out using manual methods first developed in the early 1950s. Although this technique has been recently standardised, it suffers from several drawbacks, notably data usually only being available with a delay of 3–9 days and usually delivered at a daily resolution. Several automatic instruments have come on to the market over the past few years, with more new devices also under development. This paper provides a comprehensive overview of all available and developing automatic instruments, how they measure, how they identify airborne pollen, what impacts measurement quality, as well as what potential there is for further advancement in the field of bioaerosol monitoring.
Reconceptualizing cybersecurity awareness capability in the data-driven digital economy
Authors: Akter Shahriar , Uddin Mohammad Rajib , Sajib Shahriar , Lee Wai Jin Thomas , Michael Katina , Hossain Mohammad Alamgir 
Published: August 2022

AbstractData breaches have become a formidable challenge for business operations in the twenty-first century. The emergence of big data in the ever-growing digital economy has created the necessity to secure critical organizational information. The lack of cybersecurity awareness exposes organizations to potential cyber threats. Thus, this research aims to identify the various dimensions of cybersecurity awareness capabilities. Drawing on the dynamic capabilities framework, the findings of the study show personnel (knowledge, attitude and learning), management (training, culture and strategic orientation) and infrastructure capabilities (technology and data governance) as thematic dimensions to tackle cybersecurity awareness challenges.
The Influence of Flow on Cycle-to-Cycle Variations in a Spark-Ignition Engine: A Parametric Investigation of Increasing Exhaust Gas Recirculation Levels
Authors: Welch Cooper , Schmidt Marius , Illmann Lars , Dreizler Andreas , Böhm Benjamin 
Published: August 2022

AbstractCyclic variability is investigated in an optically accessible single-cylinder spark-ignition research engine by introducing artificial exhaust gas in controlled amounts to the homogenous air–fuel mixture before ignition. A skip-fire scheme ensures the absence of internal exhaust gas recirculation (EGR) and allows the engine to be fired continuously for acquisition of large statistics. Four operating conditions ranging from a stable 0% EGR case up to a highly unstable extreme EGR case are analyzed to examine the increasing effects of homogeneous EGR on the cycle performance. To that end, high-speed measurements of the velocity field via particle image velocimetry and flame imaging in the tumble plane allow the determination of phenomena leading to various flame positions and sizes as well as faster and slower combustion cycles. Through extensive conditional statistical and multivariate correlation techniques, flames are found to be heavily influenced by large-scale velocity motion, especially with the presence of greater EGR which leads to lower flame speeds. The greater sensitivity of slower flames to variations in the velocity field manifests itself in an exponential increase in cyclic variability of the maximum in-cylinder pressure and causes misfire cycles where the flame is blown off or quenched at the cylinder roof. In the most extreme cycles at the highest EGR level, the state of the large-scale velocity structures at the time of ignition determines whether the flame propagates towards the center of the cylinder (and is blown off or quenched) or if the flame sustains growth by propagating within the lingering tumble vortex.
MYC as a therapeutic target for the treatment of triple-negative breast cancer: preclinical investigations with the novel MYC inhibitor, MYCi975
Authors: Tang Minhong , O’Grady Shane , Crown John , Duffy Michael J. 
Published: July 2022

Abstract
Background
MYC is one of the most frequently altered driver genes in triple-negative breast cancer (TNBC). The aim of this study was to evaluate targeting MYC for the treatment of TNBC.

Methods
The anti-proliferative and apoptosis-inducing effects of the recently discovered MYC inhibitor, MYCi975 were investigated in a panel of 14 breast cancer cell lines representing the main molecular forms of breast cancer.

Results
IC50 values for growth inhibition by MYCi975 varied from 2.49 to 7.73 µM. Response was inversely related to endogenous MYC levels as measured by western blotting (p = 0.047, r = − 0.5385) or ELISA (p = 0.001, r = − 0.767), i.e., response to MYCi975 decreased as endogenous MYC levels increased. MYCi975 also induced variable levels of apoptosis across the panel of cell lines, ranging from no detectable induction to 80% induction. Inhibition of proliferation and induction of apoptosis were greater in TNBC than in non-TNBC cell lines (p = 0.041 and p = 0.001, respectively). Finally, combined treatment with MYCi975 and either paclitaxel or doxorubicin resulted in enhanced cell growth inhibition.

Discussion
Our findings open the possibility of targeting MYC for the treatment of TNBC. Based on our results, we suggest that trials use a combination of MYCi975 and either docetaxel or doxorubicin and include MYC as a putative therapy predictive biomarker.
Identifying Thresholds for Observational Indicators of Enhanced Sonic Deposition on Smoke Alarms in Forensic Investigations
Authors: Gorbett Gregory E. , Borth Trevor , Rainey Stephanie , Hicks William 
Published: July 2022

AbstractThe activation status of a smoke alarm in a fire becomes a central question in forensic fire investigations when there are injuries or deaths. Forensic techniques have been developed to answer this question through the evaluation of the presence of enhanced soot deposition on specific locations of a smoke alarm. Testing was conducted to evaluate the thresholds where these observational indicators may be obscured or destroyed. Fifty-four smoke alarms were exposed to simulated fire conditions to create enhanced soot deposition observational indicators. A series of post exposure tests were conducted to determine the threshold(s) of thermal damage to determine when those indicators begin to be obscured. All powered smoke alarms presented observational indicators in locations like those identified in previous research, as well as four additional locations for this smoke alarm geometry. Enhanced soot deposition indicators were found to persist in most cases when the alarm was exposed to high temperatures (up to 325°C to 450°C), when the alarms were exposed to high temperatures and dropped to a floor surface, and when the alarm was exposed to carpet contamination.
Swampland Revisited
Authors: Silk Joseph , Cassé Michel 
Published: July 2022

AbstractThe transcendental expectation of string theory is that the nature of the fundamental forces, particle spectra and masses, together with coupling constants, is uniquely determined by mathematical and logical consistency, non-empirically, that is by pure reason. However pluralism triumphed with the explosive emergence of the multiverse. String theorists have extended a long-sought dream (their unique and final theory) to a landscape or a happy caparnaum. Proponents of string theory try to qualify their arguments via swampland conjectures while cosmologists retreat to their telescopes. We review the current status of the string theory swampland.
Nitrogen budget and critical load determination at a Sahelian grazed grassland site
Authors: Delon Claire , Galy-Lacaux Corinne , Barret Blandine , Ndiaye Ousmane , Serça Dominique , Guérin Frédéric , Gardrat Eric , Mougin Eric , Agbohessou Yélognissè F. , Probst Anne 
Published: August 2022

AbstractBased on rare and original in situ measurements together with published data, we estimate a complete nitrogen (N) budget for a semi-arid Sahelian grazed grassland located in Dahra (Senegal) in 2014 and 2017. Nitrogen inputs include biological fixation, dry and wet atmospheric deposition, and input from livestock manure. Nitrogen outputs include nitric oxide (NO) and nitrous oxide (N2O) emissions from soils, NO and ammonia (NH3) emissions from biomass burning, NH3 volatilization from manure, ingestion from livestock grazing, uptake by trees and soil leaching. Nitrogen inputs ranged between 11.7 ± 0.5 and 34.4 ± 0.5 kg N ha−1 yr−1 for low and high estimates respectively, and N outputs ranged between 16.4 ± 1.5 and 45.7 ± 1.5 kg N ha−1 yr−1 for low and high estimates respectively, on average for both years. Nitrogen depletion was estimated between 4.7 ± 2.0 and 11.3 ± 2.0 kg N ha−1 yr−1, which involves N mining from soils. The budget is dominated by the impact of livestock through grazing (63% of the outputs), NH3 volatilization (15% of the outputs), manure (68% of the inputs) and atmospheric deposition (19% of the inputs). The N critical load (Steady State Mass Balance method) ranged from 16.7 ± 0.8 to 47.5 ± 1.7 kg N ha−1 yr−1, showing that the grazed grassland of Dahra was not yet threatened by an excess of N. The assessment of the critical load in Sahelian landscapes depends heavily on livestock participation to the ecosystem equilibrium.
Entropies of non-positively curved metric spaces
Authors: Cavallucci Nicola 
Published: July 2022

AbstractWe show the equivalences of several notions of entropy, like a version of the topological entropy of the geodesic flow and the Minkowski dimension of the boundary, in metric spaces with convex geodesic bicombings satisfying a uniform packing condition. Similar estimates will be given in case of closed subsets of the boundary of Gromov-hyperbolic metric spaces with convex geodesic bicombings.
Cortically Based Optimal Transport
Authors: Galeotti Mattia , Citti Giovanna , Sarti Alessandro 
Published: July 2022

AbstractWe introduce a model for image morphing in the primary visual cortex V1 to perform completion of missing images in time. We model the output of simple cells through a family of Gabor filters and the propagation of the neural signal accordingly to the functional geometry induced by horizontal connectivity. Then we model the deformation between two images as a path relying two different outputs. This path is obtained by optimal transport considering the Wasserstein distance geodesics associated to some probability measures naturally induced by the outputs on V1. The frame of Gabor filters allows to project back the output path, therefore obtaining an associated image stimulus deformation. We perform a numerical implementation of our cortical model, assessing its ability in reconstructing rigid motions of simple shapes.