bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unraveling the relationship between autoimmune pancreatitis type 2 and inflammatory bowel disease: Results from two centers and systematic review of the literature
Authors: Nikolic Sara , Lanzillotta Marco , Panic Nikola , Brismar Torkel B. , Moro Carlos Fernández , Capurso Gabriele , Della Torre Emanuel , Löhr J.‐Matthias , Vujasinovic Miroslav 
Published: May 2022

AbstractIntroductionThe relationship between autoimmune pancreatitis (AIP) type 2 and inflammatory bowel disease (IBD) has been established and previously described within International Consensus Diagnostic Criteria. However, it is unknown if the presence of IBD changes the natural disease course of AIP type 2. Our aim was to investigate the association between AIP type 2 and IBD as well as to systematically summarize all the existing evidence in the literature.MethodsElectronic medical record analysis was conducted in two centers (in Stockholm, Sweden, and Milan, Italy; records dated between January 2001 and June 2021). Additionally, we conducted a systematic review of the literature.ResultsA total of 35 patients (18 females, 51.4%) fulfilled the diagnostic criteria of AIP type 2 and were included in the study. A diagnosis of IBD was established in 29 patients (82.8%), ulcerative colitis in 17 (58.6%) and Crohn's disease in 11 (37.9%). Median follow‐up was 54 months. AIP patients with IBD commonly presented with abdominal pain and/or acute pancreatitis at diagnosis, the latter was prevailing in concomitant and later IBD onset. These patients more frequently used steroids, but there were no differences in relapse rates. Concomitant onset of IBD was associated with the development of diabetes mellitus. There were no cases of colon or pancreatic malignancy during follow‐up. In our systematic analysis, a total of 693 AIP type 2 patients were included from 24 single‐center retrospective studies and 8 multicenter retrospective studies. A diagnosis of IBD was reported in 330 (47.8%) patients. Relapse rate was 20.0%.ConclusionsClinical and radiological remission of AIP type 2 was high, while the cumulative incidence of relapse is around 20%. Our results show that concomitance of IBD imposes no obvious risk of a different disease course for AIP type 2.
Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution
Authors: Hustad Kristian Gregorius , Ivanovic Ena , Recha Adrian Llop , Sakthivel Abinaya Abbi 
Published: May 2022

AbstractIon channels on the membrane of cardiomyocytes regulate the propagation of action potentials from cell to cell and hence are essential for the proper function of the heart. Through computer simulations with the classical monodomain model for cardiac tissue and the more recent extracellular-membrane-intracellular (EMI) model where individual cells are explicitly represented, we investigated how conduction velocity (CV) in cardiac tissue depends on the strength of various ion currents as well as on the spatial distribution of the ion channels. Our simulations show a sharp decrease in CV when reducing the strength of the sodium (Na+) currents, whereas independent reductions in the potassium (K1 and Kr) and L-type calcium currents have negligible effect on the CV. Furthermore, we find that an increase in number density of Na+ channels towards the cell ends increases the CV, whereas a higher number density of K1 channels slightly reduces the CV. These findings contribute to the understanding of ion channels (e.g. Na+ and K+ channels) in the propagation velocity of action potentials in the heart.
A Computational Study of Flow Instabilities in Aneurysms
Authors: Berre Nanna , Castro Gabriela , Kjeldsberg Henrik , Masri Rami , Gjerde Ingeborg 
Published: May 2022

AbstractThe majority of hemorrhagic strokes are caused by cerebral aneurysms, harboured in a large portion of the human population. Currently, it is unclear what constitutes a dangerous aneurysm, and the risk of rupture of such aneurysms is challenging to quantify. Previous studies have shown that flow dynamics play an important role in the development of aneurysms. However, there is varying consensus on blood flow patterns and stability. In this work, we formulate a Reynolds–Orr method to quantify the stability of blood flow in arteries. Applying this method to blood flow in four different arterial models, we find that the blood flow therein is unstable under physiological conditions. We show the most unstable eigenmodes for each of these models and discuss how they potentially could help explain the initiation and growth of aneurysms.
A year in pharmacology: new drugs approved by the US Food and Drug Administration in 2021
Authors: Kayki-Mutlu Gizem , Aksoyalp Zinnet Sevval , Wojnowski Leszek , Michel Martin C. 
Published: May 2022

AbstractThe second year of the COVID-19 pandemic had no adverse effect on the number of new drug approvals by the US Food and Drug Administration (FDA). Quite the contrary, with a total of 50 new drugs, 2021 belongs to the most successful FDA years. We assign these new drugs to one of three levels of innovation: (1) first drug against a condition (“first-in-indication”), (2) first drug using a novel molecular mechanism (“first-in-class”), and (3) “next-in-class”, i.e., a drug using an already exploited molecular mechanism. We identify 21 first-in-class, 28 next-in-class, and only one first-in-indication drugs. By treatment area, the largest group is once again cancer drugs, many of which target specific genetic alterations. Every second drug approved in 2021 targets an orphan disease, half of them being cancers. Small molecules continue to dominate new drug approvals, followed by antibodies and non-antibody biopharmaceuticals. In 2021, the FDA continued to approve drugs without strong evidence of clinical effects, best exemplified by the aducanumab controversy.
A framework for randomized time-splitting in linear-quadratic optimal control
Authors: Veldman D. W. M. , Zuazua E. 
Published: May 2022

AbstractInspired by the successes of stochastic algorithms in the training of deep neural networks and the simulation of interacting particle systems, we propose and analyze a framework for randomized time-splitting in linear-quadratic optimal control. In our proposed framework, the linear dynamics of the original problem is replaced by a randomized dynamics. To obtain the randomized dynamics, the system matrix is split into simpler submatrices and the time interval of interest is split into subintervals. The randomized dynamics is then found by selecting randomly one or more submatrices in each subinterval. We show that the dynamics, the minimal values of the cost functional, and the optimal control obtained with the proposed randomized time-splitting method converge in expectation to their analogues in the original problem when the time grid is refined. The derived convergence rates are validated in several numerical experiments. Our numerical results also indicate that the proposed method can lead to a reduction in computational cost for the simulation and optimal control of large-scale linear dynamical systems.
Predicting complicated appendicitis based on clinical findings: the role of Alvarado and Appendicitis Inflammatory Response scores
Authors: Haak F. , Kollmar O. , Ioannidis A. , Slotta J. E. , Ghadimi M. B. , Glass T. , von Strauss und Torney M. 
Published: May 2022

Abstract
Purpose
The pre-interventional differentiation between complicated and uncomplicated appendicitis is decisive for treatment. In the context of conservative therapy, the definitive diagnosis of uncomplicated appendicitis is mandatory. This study investigates the ability of clinical scoring systems and imaging to differentiate between the two entities.

Methods
This is a retrospective analysis of two cohorts from two tertiary referral centers in Switzerland and Germany. All consecutive patients underwent appendectomy between January 2008 and April 2013 (in the first cohort) or between January 2017 and June 2019 (the second cohort). Exclusion criteria did not apply as all patients found by the database search and received an appendectomy were included. Diagnostic testing and calculation of a receiver operating curve were performed to identify a cutoff for clinical scores that resulted in a minimum sensitivity of 90% to detect complicated appendicitis. The cutoff was combined with additional diagnostic imaging criteria to see if diagnostic properties could be improved.

Results
Nine hundred fifty-six patients were included in the analysis. Two hundred twenty patients (23%) had complicated appendicitis, and 736 patients (77%) had uncomplicated appendicitis or no inflammation. The complicated appendicitis cohort had a mean Alvarado score of 7.03 and a mean AIR of 5.21. This compared to a mean Alvarado of 6.53 and a mean AIR of 4.07 for the uncomplicated appendicitis cohort. The highest Alvarado score with a sensitivity of > 90% to detect complicated appendicitis was ≧ 5 (sensitivity = 95%, specificity 8.99%). The highest AIR score with a sensitivity of > 90% to detect complicated appendicitis was ≧ 3 (sensitivity 91.82%, specificity 18.53). The analysis showed that additional CT information did not improve the sensitivity of the proposed cut-offs.

Conclusion
AIR and Alvarado scores showed limited capability to distinguish between complicated and uncomplicated appendicitis even with additional imaging in this retrospective cohort. As conservative management of appendicitis needs to exclude patients with complicated disease reliably, appendectomy seems until now to remain the safest option to prevent undertreatment of this mostly benign disease.
Energy balance-related factors and risk of colorectal cancer based on KRAS, PIK3CA, and BRAF mutations and MMR status
Authors: Jenniskens Josien C. A. , Offermans Kelly , Simons Colinda C. J. M. , Samarska Iryna , Fazzi Gregorio E. , van der Meer Jaleesa R. M. , Smits Kim M. , Schouten Leo J. , Weijenberg Matty P. , Grabsch Heike I. , van den Brandt Piet A. 
Published: May 2022

Abstract
Introduction
KRAS mutations (KRASmut), PIK3CAmut, BRAFmut, and mismatch repair deficiency (dMMR) have been associated with the Warburg-effect. We previously observed differential associations between energy balance-related factors (BMI, clothing-size, physical activity) and colorectal cancer (CRC) subtypes based on the Warburg-effect. We now investigated whether associations between energy balance-related factors and risk of CRC differ between subgroups based on mutation and MMR status.

Methods
Information on molecular features was available for 2349 incident CRC cases within the Netherlands Cohort Study (NLCS), with complete covariate data available for 1934 cases and 3911 subcohort members. Multivariable-adjusted Cox-regression was used to estimate associations of energy balance-related factors with risk of CRC based on individual molecular features (KRASmut; PIK3CAmut; BRAFmut; dMMR) and combinations thereof (all-wild-type + MMR-proficient (pMMR); any-mutation/dMMR).

Results
In men, BMI and clothing-size were positively associated with risk of colon, but not rectal cancer, regardless of molecular features subgroups; the strongest associations were observed for PIK3CAmut colon cancer. In women, however, BMI and clothing-size were only associated with risk of KRASmut colon cancer (p-heterogeneityKRASmut versus all-wild-type+pMMR = 0.008). Inverse associations of non-occupational physical activity with risk of colon cancer were strongest for any-mutation/dMMR tumors in men and women, and specifically for PIK3CAmut tumors in women. Occupational physical activity was inversely associated with both combination subgroups of colon cancer in men.

Conclusion
In men, associations did not vary according to molecular features. In women, a role of KRAS mutations in the etiological pathway between adiposity and colon cancer is suggested, and of PIK3CA mutations between physical activity and colon cancer.
A Faster Reduction of the Dynamic Time Warping Distance to the Longest Increasing Subsequence Length
Authors: Sakai Yoshifumi , Inenaga Shunsuke 
Published: May 2022

AbstractThe similarity between a pair of time series, i.e., sequences of indexed values in time order, is often estimated by the dynamic time warping (DTW) distance, instead of any in the well-studied family of measures including the longest common subsequence (LCS) length and the edit distance. Although it may seem as if the DTW and the LCS(-like) measures are essentially different, we reveal that the DTW distance can be represented by the longest increasing subsequence (LIS) length of a sequence of integers, which is the LCS length between the integer sequence and itself sorted. For a given pair of time series of lengthnsuch that the dissimilarity between any elements is an integer between zero andc, we propose an integer sequence that represents any substring-substring DTW distance as its band-substring LIS length. The length of the produced integer sequence is$$O(c n^2)$$O(cn2), which can be translated to$$O(n^2)$$O(n2)for constant dissimilarity functions. To demonstrate that techniques developed under the LCS(-like) measures are directly applicable to analysis of time series via our reduction of DTW to LIS, we present time-efficient algorithms for DTW-related problems utilizing the semi-local sequence comparison technique developed for LCS-related problems.
A prognostic scoring system for conversion surgery after trastuzumab-based chemotherapy for human epidermal growth factor receptor 2-positive advanced gastric cancer
Authors: Arigami Takaaki , Matsushita Daisuke , Okubo Keishi , Shimonosono Masataka , Sasaki Ken , Tsuruda Yusuke , Kita Yoshiaki , Tanabe Kan , Mori Shinichiro , Yanagita Shigehiro , Uenosono Yoshikazu , Nakajo Akihiro , Kurahara Hiroshi , Ohtsuka Takao 
Published: May 2022

Abstract
Purpose
To investigate the clinical indications and prognostic significance of surgical interventions after chemotherapy using trastuzumab-containing regimens for patients with human epidermal growth factor receptor 2 (HER2)-positive advanced gastric cancer (AGC).

Methods
A total of 146 patients with AGC who underwent chemotherapy were enrolled in this retrospective study. Tumors with an immunohistochemistry (IHC) score of 3 + or an IHC score of 2 + plus fluorescence in situ hybridization positivity were defined as HER2-positive AGC. We devised a scoring system for predicting prognosis associated with conversion surgery.

Results
Thirty-three patients received trastuzumab-based chemotherapy for HER2-positive tumors. Multivariate analyses identified advanced age, peritoneal dissemination, histologically undifferentiated tumors, and tumor response of progressive disease as independent prognostic factors for a worse prognosis. Twelve patients with HER2-positive AGC underwent conversion surgery. The conversion surgery group of patients with HER2-positive AGC had a better prognosis than the chemotherapy-alone group. A prognostic scoring system based on age, peritoneal dissemination, and histological type was significantly correlated with the presence or absence of conversion surgery and the prognosis of patients with HER2-positive AGC.

Conclusions
Our scoring system has the clinical potential to predict prognosis associated with conversion surgery after trastuzumab-containing chemotherapy for patients with HER2-positive AGC.
Interpolating between volume and lattice point enumerator with successive minima
Authors: Freyer Ansgar , Lucas Eduardo 
Published: May 2022

AbstractWe study inequalities that simultaneously relate the number of lattice points, the volume and the successive minima of a convex body to one another. One main ingredient in order to establish these relations is Blaschke’s shaking procedure, by which the problem can be reduced from arbitrary convex bodies to anti-blocking bodies. As a consequence of our results, we obtain an upper bound on the lattice point enumerator in terms of the successive minima, which is equivalent to Minkowski’s upper bound on the volume in terms of the successive minima.
Are the statistical tests the best way to deal with the biomarker selection problem?
Authors: Urkullu Ari , Pérez Aritz , Calvo Borja 
Published: May 2022

AbstractStatistical tests are a powerful set of tools when applied correctly, but unfortunately the extended misuse of them has caused great concern. Among many other applications, they are used in the detection of biomarkers so as to use the resulting p-values as a reference with which the candidate biomarkers are ranked. Although statistical tests can be used to rank, they have not been designed for that use. Moreover, there is no need to compute any p-value to build a ranking of candidate biomarkers. Those two facts raise the question of whether or not alternative methods which are not based on the computation of statistical tests that match or improve their performances can be proposed. In this paper, we propose two alternative methods to statistical tests. In addition, we propose an evaluation framework to assess both statistical tests and alternative methods in terms of both the performance and the reproducibility. The results indicate that there are alternative methods that can match or surpass methods based on statistical tests in terms of the reproducibility when processing real data, while maintaining a similar performance when dealing with synthetic data. The main conclusion is that there is room for the proposal of such alternative methods.
Hecke correspondences for smooth moduli spaces of sheaves
Authors: Neguţ Andrei 
Published: May 2022

AbstractWe define functors on the derived category of the moduli space ℳ of stable sheaves on a smooth projective surface (under Assumptions A and S below), and prove that these functors satisfy certain commutation relations. These relations allow us to prove that the given functors induce an action of the elliptic Hall algebra on the$K$K-theory of the moduli space ℳ, thus generalizing the action studied by Nakajima, Grojnowski and Baranovsky in cohomology.
A deep ensemble learning method for colorectal polyp classification with optimized network parameters
Authors: Younas Farah , Usman Muhammad , Yan Wei Qi 
Published: May 2022

AbstractColorectal Cancer (CRC), a leading cause of cancer-related deaths, can be abated by timely polypectomy. Computer-aided classification of polyps helps endoscopists to resect timely without submitting the sample for histology. Deep learning-based algorithms are promoted for computer-aided colorectal polyp classification. However, the existing methods do not accommodate any information on hyperparametric settings essential for model optimisation. Furthermore, unlike the polyp types, i.e., hyperplastic and adenomatous, the third type, serrated adenoma, is difficult to classify due to its hybrid nature. Moreover, automated assessment of polyps is a challenging task due to the similarities in their patterns; therefore, the strength of individual weak learners is combined to form a weighted ensemble model for an accurate classification model by establishing the optimised hyperparameters. In contrast to existing studies on binary classification, multiclass classification require evaluation through advanced measures. This study compared six existing Convolutional Neural Networks in addition to transfer learning and opted for optimum performing architecture only for ensemble models. The performance evaluation on UCI and PICCOLO dataset of the proposed method in terms of accuracy (96.3%, 81.2%), precision (95.5%, 82.4%), recall (97.2%, 81.1%), F1-score (96.3%, 81.3%) and model reliability using Cohen’s Kappa Coefficient (0.94, 0.62) shows the superiority over existing models. The outcomes of experiments by other studies on the same dataset yielded 82.5% accuracy with 72.7% recall by SVM and 85.9% accuracy with 87.6% recall by other deep learning methods. The proposed method demonstrates that a weighted ensemble of optimised networks along with data augmentation significantly boosts the performance of deep learning-based CAD.
Using machine learning to create a repository of judgments concerning a new practice area: a case study in animal protection law
Authors: Watson Joe , Aglionby Guy , March Samuel 
Published: May 2022

AbstractJudgments concerning animals have arisen across a variety of established practice areas. There is, however, no publicly available repository of judgments concerning the emerging practice area of animal protection law. This has hindered the identification of individual animal protection law judgments and comprehension of the scale of animal protection law made by courts. Thus, we detail the creation of an initial animal protection law repository using natural language processing and machine learning techniques. This involved domain expert classification of 500 judgments according to whether or not they were concerned with animal protection law. 400 of these judgments were used to train various models, each of which was used to predict the classification of the remaining 100 judgments. The predictions of each model were superior to a baseline measure intended to mimic current searching practice, with the best performing model being a support vector machine (SVM) approach that classified judgments according to term frequency—inverse document frequency (TF-IDF) values. Investigation of this model consisted of considering its most influential features and conducting an error analysis of all incorrectly predicted judgments. This showed the features indicative of animal protection law judgments to include terms such as ‘welfare’, ‘hunt’ and ‘cull’, and that incorrectly predicted judgments were often deemed marginal decisions by the domain expert. The TF-IDF SVM was then used to classify non-labelled judgments, resulting in an initial animal protection law repository. Inspection of this repository suggested that there were 175 animal protection judgments between January 2000 and December 2020 from the Privy Council, House of Lords, Supreme Court and upper England and Wales courts.
Model order reduction of layered waveguides via rational Krylov fitting
Authors: Druskin Vladimir , Güttel Stefan , Knizhnerman Leonid 
Published: May 2022

AbstractRational approximation recently emerged as an efficient numerical tool for the solution of exterior wave propagation problems. Currently, this technique is limited to wave media which are invariant along the main propagation direction. We propose a new model order reduction-based approach for compressing unbounded waveguides with layered inclusions. It is based on the solution of a nonlinear rational least squares problem using the RKFIT method. We show that approximants can be converted into an accurate finite difference representation within a rational Krylov framework. Numerical experiments indicate that RKFIT computes more accurate grids than previous analytic approaches and even works in the presence of pronounced scattering resonances. Spectral adaptation effects allow for finite difference grids with dimensions near or even below the Nyquist limit.