bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tube removal, tailored antibiotic treatment and endoscopic suturing effectively treats peristomal infection and consecutive persisting gastrostomy fistula – a case series
Authors: Brechmann Thorsten , Jägers Lisa Linnea , Schyroki Yvonne , Naveed Parweiz 
Published: September 2022

Abstract
Objectives Peristomal leakage, infection, and persisting fistula after tube removal are rare, but well-known complications in long-term percutaneous endoscopic gastrostomies (PEG). A standard treatment procedure is missing. This case series describes a procedure of tube removal, tailored antibiotic therapy and endoscopic closure with a gastropexy device after mechanical de-epithelialization of the fistulous tract.
Case presentation Three patients with infected long-standing PEG (4 to 21 years) were included. The tubes were removed endoscopically and tailored antimicrobial therapy was administered over 10 to 14 days. The persisting fistula was de-epithelialized mechanically and sutured under endoscopic control with a dedicated gastropexy device 11 to 25 days thereafter. A new PEG tube was placed in the same session on a different site. After 30 days the fistula had healed completely, and the PEG worked well in all subjects.
Conclusions Endoscopic sealing of a persisting fistula with a dedicated gastropexy device after thorough de-epithelialization is a promising technique that needs confirmation by larger studies.
Clinical Value of Echo-Tracking in Gestational Diabetes
Mellitus
Authors: Zhou Youxia , Lan Qianyu , Li Yuan , Qi Lin , Dong Yiming , Zhou Haixia , Zhang Jiefang 
Published: September 2022

Abstract
Background Vascular endothelial function plays an essential role in
gestational diabetes mellitus (GDM) pathogenesis. Vascular elasticity is
evaluated by the echo-tracking (ET) technique. In this study, we aimed to assess
the clinical value of the ET technique in women with GDM and provide a basis for
early evaluation and prevention of gestational diabetes.
Methods Sixty-five patients with GDM and 65 gestational week-matched
normal glucose tolerance pregnant women were enrolled in this study. The
endothelial function parameters of pressure-strain elasticity coefficient (EP),
the common carotid stiffness index (β), arterial compliance (AC),
single-point pulsed-wave velocity (PWVβ), and augment index (AI) of
bilateral common carotid arteries, were compared between the GDM and control
groups by using ET technique. The correlations between plasma glucose levels and
ET parameters were also analyzed.
Results Our results indicated that EP, β, PWVβ, and AI
were significantly higher in the GDM group (p<0.05), whereas AC was
significantly lower in patients with GDM than in the control group
(p<0.001). In addition, fasting plasma glucose and plasma glucose level
after 2 h oral glucose tolerance test was correlated with ET parameters
of EP, β, PWVβ, AI, and AC.
Conclusions The application of ET technology to gestational diabetes women
could provide a basis for early evaluation and prevention of gestational
diabetes. It would detect early and accurate signs of diabetes in pregnant women
and provide a timely and reasonable clinical treatment plan to reduce and delay
the occurrence of complications.
Evaluation of Treatment with Omega-3 Fatty Acid Supplements on Salivary Levels of Resolvin E1 in Chronic Periodontitis Patients
Authors: Murali Aparna C , Bhandary Rahul , Ramesh Amitha , Venugopalan Geethu 
Published: September 2022

Abstract
Context Under healthy conditions, inflammation proceeds through natural healing processes by an organized cycle. Similar to any other systemic infection, periodontal disease is also a manifestation of dysregulated inflammatory pathway.Endogenous lipid mediators called resolvins and docosatrienes, produced from omega-3 fatty acid precursors, possess various immunoregulatory properties. These polyunsaturated fatty acids cannot be synthesized in body, instead these have to be taken through diet. This study aims to evaluate the effect of adjunctive treatment with daily dietary supplementation of omega-3 fatty acids in chronic periodontitis.
Aims The aim of this study was to assess periodontal parameters and salivary levels of Resolvin E1 with and without dietary supplementation of omega-3 fatty acid capsules in chronic periodontitis patients.
Methods and Materials Three-month comparative clinical study was performed on 52 patients allotted to two groups, each with 26 subjects. Both groups received an initial phase 1 therapy followed by additional dietary supplementation of 500 mg of omega-3 fatty acid capsules for 3 months for the test group. Salivary levels of Resolvin E1, periodontal parameters, including pocket probing depth (PPD), clinical attachment loss (CAL), bleeding on probing (BOP), and periodontal inflamed surface area (PISA), were assessed at baseline, 1 and 3 months after the study.
Statistical Analysis Used Data was analyzed with an unpaired t-test between the group and paired t-test for within the group comparison. p-Value less than 0.05 was considered significant.
Results PPD and CAL showed statistically significant differences between the two groups and within the groups
Strategies in tracing linguistic variation in a corpus of Old Irish texts (CorPH)
Authors: Stifter David , Qiu Fangzhe , Aquino-López Marco A. , Bauer Bernhard , Lash Elliott , White Nora 
Published: September 2022

AbstractThis article introduces Corpus PalaeoHibernicum (CorPH), a corpus currently consisting of 78 texts in Early Irish (c. 7th–10th cent.) created by the ERC-fundedChronologicon Hibernicum(ChronHib) project by bringing together pre-existing lexical and syntactic databases and adding further crucial texts from the period. In addition to being annotated for POS, morphological and syntactic information, another layer of annotation has been developed for CorPH – ‘Variation Tagging’, i.e. a tagset that numerically encodes synchronic language variation during the Early Irish period, thus allowing for much improved research on the chronological variation among the material. Another new pillar of studying linguistic variation is Bayesian Language Variation Analysis (BLaVA), in order to address the challenge that “not-so-big data” poses to statistical corpus methods. Instead of reflecting feature frequencies, BLaVA models language variation as probabilities of variation.
DH-Mammo PET: a dual-head positron emission mammography system for breast imaging
Authors: Shi Yu , Wang Yirong , Zhou Jianwei , Zhu Yuzhen , Lyu Xudong , Hui Hui , Wen Bo , Liu Yanyun , Li Lei , Li Juntao , Meng Fanzhen , Kang Fei , Zhu Shouping 
Published: September 2022

Abstract

Objective. To develop a simultaneous positron emission tomography-Optical (OPET) breast imaging dual-head PET subsystem, called DH-Mammo PET, for accurate, early diagnosis and efficacy assessment of breast cancer with high resolution and sensitivity. Approach. We developed a breast-dedicated PET based on LYSO crystal, silicon photomultiplier array and multi-voltage threshold sampling technique. It consists of two detector heads, each with a detection area of 216 mm × 145.5 mm. The distance between the detector heads is fixed at 120 mm. In order to extract coincidences and correct data, GPU-based software coincidence processing, random, scatter, normalization, gap-filling and attenuation corrections were applied in turn. The images were reconstructed using maximum likelihood expectation maximization with depth of interaction (DOI) modeling. The performance of DH-Mammo PET was evaluated referring to NEMA NU 4–2008, NU 2–2007 and Chinese industry recommended standard YY/T 1835–2022. Besides, several clinical patient images of DH-Mammo PET were compared with those of a whole-body PET/CT. Main results. The energy resolution was 14.5%, and time resolution was < 1.31 ns. Indicated by the 22Na point source imaging, its spatial resolution was 2.60 mm (5.40 mm), 1.00 mm (1.04 mm), and 0.96 mm (0.93 mm) in the X, Y and Z directions, respectively, using the system response matrix with (without) DOI modeling. Indicated by the Derenzo phantom imaging, the spatial resolution was ∼3.0 mm, <1.2 mm, and <1.2 mm in the X, Y and Z directions. The system sensitivity was 6.87%, 4.89% and 3.37% with an energy window of 100–800, 250–750 and 350–650 keV, respectively. The scatter fraction was 26.43%, and the peak NECR was 162.6 kcps at 24.1 MBq for the modified rat-like phantom. As for the recovery coefficients, they ranged from 0.15 to 1.04 for rods between 1 and 5 mm obtained with a NEMA image quality phantom. The spill-over ratio for the air-filled and water-filled chamber was 0.05 and 0.11, respectively. DH-Mammo PET can provide more image details in clinical experiments and fulfil a fast scan with 60–120 s acquisition time. Significance. Good spatial resolution and high sensitivity of DH-Mammo PET would enable fast and accurate PET imaging of the breast. Besides, combining the DH-Mammo PET with the diffuse optical tomography would make full use of tumor metabolic imaging and tissue endogenous optical imaging, which would improve the accuracy of early clinical diagnosis of small lesions of breast cancers.
Amphibian collapses increased malaria incidence in Central America
*
Authors: Springborn Michael R , Weill Joakim A , Lips Karen R , Ibáñez Roberto , Ghosh Aniruddha 
Published: September 2022

Abstract
Biodiversity in ecosystems plays an important role in supporting human welfare, including regulating the transmission of infectious diseases. Many of these services are not fully-appreciated due to complex environmental dynamics and lack of baseline data. Multicontinental amphibian decline due to the fungal pathogen Batrachochytrium dendrobatidis (Bd) provides a stark example. Even though amphibians are known to affect natural food webs—including mosquitoes that transmit human diseases—the human health impacts connected to their massive decline have received little attention. Here we leverage a unique ensemble of ecological surveys, satellite data, and newly digitized public health records to show an empirical link between a wave of Bd-driven collapse of amphibians in Costa Rica and Panama and increased human malaria incidence. Subsequent to the estimated date of Bd-driven amphibian decline in each ‘county’ (canton or distrito), we find that malaria cases are significantly elevated for several years. For the six year peak of the estimated effect, the annual expected county-level increase in malaria ranges from 0.76 to 1.1 additional cases per 1000 population. This is a substantial increase given that cases country-wide per 1000 population peaked during the timeframe of our study at approximately 1.5 for Costa Rica and 1.1 for Panama. This previously unidentified impact of biodiversity loss illustrates the often hidden human welfare costs of conservation failures. These findings also show the importance of mitigating international trade-driven spread of similar emergent pathogens like Batrachochytrium salamandrivorans.
Lax operator and superspin chains from 4D CS gauge theory
Authors: Boujakhrout Y , Saidi E H , Laamara R Ahl , Drissi L B 
Published: September 2022

Abstract
We study the properties of interacting line defects in the four-dimensional Chern Simons (CS) gauge theory with invariance given by the

S
L

m
|
n

super-group family. From this theory, we derive the oscillator realisation of the Lax operator for superspin chains with SL(m|n) symmetry. To this end, we investigate the holomorphic property of the bosonic Lax operator

L

and build a differential equation

D
L
=
0

solved by the Costello–Gaioto–Yagi realisation of

L

in the framework of the CS theory. We generalize this construction to the case of gauge super-groups, and develop a Dynkin super-diagram algorithm to deal with the decomposition of the Lie superalgebras. We obtain the generalisation of the Lax operator describing the interaction between the electric Wilson super-lines and the magnetic ’t Hooft super-defects. This coupling is given in terms of a mixture of bosonic and fermionic oscillator degrees of freedom in the phase space of magnetically charged ’t Hooft super-lines. The purely fermionic realisation of the superspin chain Lax operator is also investigated and it is found to coincide exactly with the

Z

2

-gradation of Lie superalgebras.
Valley-dependent topological edge states in plasma photonic crystals
Authors: LI Jianfei , ZHOU Chen , YAO Jingfeng , YUAN Chengxun , WANG Ying , ZHOU Zhongxiang , ZHANG Jingwen , KUDRYAVTSEV Anatoly A 
Published: September 2022

Abstract
Plasma photonic crystals designed in this paper are composed of gas discharge tubes to control the flow of electromagnetic waves. The band structures calculated by the finite element method are consistent with the experimental results which have two distinct attenuation peaks in the ranges of 1‒2.5 GHz and 5‒6 GHz. Electromagnetic parameters of the plasma are extracted by the Nicolson–Ross–Weir method and effective medium theory. The measured electron density is between

1
×

10

11

cm

−
3

and

1
×

10

12

cm

−
3

,

which verifies the correctness of the parameter used in the simulation, and the collision frequency is near

1.5
×

10

10

Hz
.

As the band structures are corroborated by the measured scattering parameters, we introduce the concept of photonic topological insulator based on the quantum Valley Hall effect into the plasma photonic crystal. A valley-dependent plasma photonic crystal with hexagonal lattice is constructed, and the phase transition of the valley

K

(

K
′

) occurs by breaking the spatial inversion symmetry. Valley-spin locked topological edge states are generated and excited by chiral sources. The frequency of the non-bulk state can be dynamically regulated by the electron density. This concept paves the way for novel, tunable topological edge states. More interestingly, the Dirac cone is broken when the electron density increases to

3.1
×

10

12

cm

−
3

,

which distinguishes from the methods of applying a magnetic field and changing the symmetry of the point group.
Role of High-Risk HPV Testing in Papanicolaou Tests With Atypical Glandular Cells With and Without Concurrent Squamous Cell Abnormalities
Authors: Lin Lawrence H , Koloori Maryam N , Brandler Tamar C , Simsir Aylin 
Published: September 2022

Abstract

Objectives
Data on Papanicolaou (Pap) tests with atypical glandular cells (AGCs) with concurrent squamous cell abnormalities (AGC + Sq) are limited. We evaluated histologic outcomes and the role of high-risk human papillomavirus (HR-HPV) testing in this setting compared with AGCs without concurrent squamous cell abnormalities (AGC-alone).

Methods
This study used a retrospective cohort of patients with Pap test diagnoses of AGC + Sq and AGC-alone between October 2013 and August 2021.

Results
We included 287 Pap tests from 278 patients. The HR-HPV test was positive in 55% of AGC + Sq cases and 14% of AGC-alone cases (P &lt; .0001). Most AGC + Sq cases displayed squamous lesions (41.5%) or were benign (41.5%) on histology, whereas AGC-alone cases were predominantly benign (72%) or extracervical neoplasms (18%). AGC + Sq cases showed higher rates of significant histologic lesions (P = .0001), which were associated with positive HR-HPV status (P = .0012). In AGC-alone cases, HR-HPV status was associated with significant histology only in patients 50 years of age or younger. In both groups, 20% or more of HR-HPV–negative patients harbored significant lesions.

Conclusions
AGC + Sq represents a distinct group of patients. HR-HPV testing and patient age provide useful information in the evaluation of AGC, but triage based on HR-HPV testing is not recommended because of the potential for missing significant lesions.
Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories
Authors: Cifuentes-Bernal Andres M , Pham Vu V H , Li Xiaomei , Liu Lin , Li Jiuyong , Duy Le Thuc 
Published: September 2022

Abstract
The traditional way for discovering genes which drive cancer (namely cancer drivers) neglects the dynamic information of cancer development, even though it is well known that cancer progresses dynamically. To enhance cancer driver discovery, we expand cancer driver concept to dynamic cancer driver as a gene driving one or more bio-pathological transitions during cancer progression. Our method refers to the fact that cancer should not be considered as a single process but a compendium of altered biological processes causing the disease to develop over time. Reciprocally, different drivers of cancer can potentially be discovered by analysing different bio-pathological pathways. We propose a novel approach for causal inference of genes driving one or more core processes during cancer development (i.e. dynamic cancer driver). We use the concept of pseudotime for inferring the latent progression of samples along a biological transition during cancer and identifying a critical event when such a process is significantly deviated from normal to carcinogenic. We infer driver genes by assessing the causal effect they have on the process after such a critical event. We have applied our method to single-cell and bulk sequencing datasets of breast cancer. The evaluation results show that our method outperforms well-recognized cancer driver inference methods. These results suggest that including information of the underlying dynamics of cancer improves the inference process (in comparison with using static data), and allows us to discover different sets of driver genes from different processes in cancer. R scripts and datasets can be found at https://github.com/AndresMCB/DynamicCancerDriver
Multi-modality artificial intelligence in digital pathology
Authors: Qiao Yixuan , Zhao Lianhe , Luo Chunlong , Luo Yufan , Wu Yang , Li Shengtong , Bu Dechao , Zhao Yi 
Published: September 2022

Abstract
In common medical procedures, the time-consuming and expensive nature of obtaining test results plagues doctors and patients. Digital pathology research allows using computational technologies to manage data, presenting an opportunity to improve the efficiency of diagnosis and treatment. Artificial intelligence (AI) has a great advantage in the data analytics phase. Extensive research has shown that AI algorithms can produce more up-to-date and standardized conclusions for whole slide images. In conjunction with the development of high-throughput sequencing technologies, algorithms can integrate and analyze data from multiple modalities to explore the correspondence between morphological features and gene expression. This review investigates using the most popular image data, hematoxylin–eosin stained tissue slide images, to find a strategic solution for the imbalance of healthcare resources. The article focuses on the role that the development of deep learning technology has in assisting doctors’ work and discusses the opportunities and challenges of AI.
Clustered tree regression to learn protein energy change with mutated amino acid
Authors: Tu Hongwei , Han Yanqiang , Wang Zhilong , Li Jinjin 
Published: September 2022

Abstract
Accurate and effective prediction of mutation-induced protein energy change remains a great challenge and of great interest in computational biology. However, high resource consumption and insufficient structural information of proteins severely limit the experimental techniques and structure-based prediction methods. Here, we design a structure-independent protocol to accurately and effectively predict the mutation-induced protein folding free energy change with only sequence, physicochemical and evolutionary features. The proposed clustered tree regression protocol is capable of effectively exploiting the inherent data patterns by integrating unsupervised feature clustering by K-means and supervised tree regression using XGBoost, and thus enabling fast and accurate protein predictions with different mutations, with an average Pearson correlation coefficient of 0.83 and an average root-mean-square error of 0.94kcal/mol. The proposed sequence-based method not only eliminates the dependence on protein structures, but also has potential applications in protein predictions with rare structural information.
CORN—Condition Orientated Regulatory Networks: bridging conditions to gene networks
Authors: Leung Ricky Wai Tak , Jiang Xiaosen , Zong Xueqing , Zhang Yanhong , Hu Xinlin , Hu Yaohua , Qin Jing 
Published: September 2022

Abstract
A transcriptional regulatory network (TRN) is a collection of transcription regulators with their associated downstream genes, which is highly condition-specific. Understanding how cell states can be programmed through small molecules/drugs or conditions by modulating the whole gene expression system granted us the potential to amend abnormal cells and cure diseases. Condition Orientated Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/home) is a library of condition (small molecule/drug treatments and gene knockdowns)-based transcriptional regulatory sub-networks (TRSNs) that come with an online TRSN matching tool. It allows users to browse condition-associated TRSNs or match those TRSNs by inputting transcriptomic changes of interest. CORN utilizes transcriptomic changes data after specific conditional treatment in cells, and in vivo transcription factor (TF) binding data in cells, by combining TF binding information and calculations of significant expression alterations of TFs and genes after the conditional treatments, TRNs under the effect of different conditions were constructed. In short, CORN associated 1805 different types of specific conditions (small molecule/drug treatments and gene knockdowns) to 9553 TRSNs in 25 human cell lines, involving 204TFs. By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This study demonstrated with examples that CORN can aid the understanding of molecular pathology, pharmacology and drug repositioning, and screened drugs with high potential for cancer and coronavirus disease 2019 (COVID-19) treatments.
Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions
Authors: John Maura , Ankenbrand Markus J , Artmann Carolin , Freudenthal Jan A , Korte Arthur , Grimm Dominik G 
Published: September 2022

AbstractMotivationGenome-wide association studies (GWAS) are an integral tool for studying the architecture of complex genotype and phenotype relationships. Linear mixed models (LMMs) are commonly used to detect associations between genetic markers and a trait of interest, while at the same time allowing to account for population structure and cryptic relatedness. Assumptions of LMMs include a normal distribution of the residuals and that the genetic markers are independent and identically distributed—both assumptions are often violated in real data. Permutation-based methods can help to overcome some of these limitations and provide more realistic thresholds for the discovery of true associations. Still, in practice, they are rarely implemented due to the high computational complexity.ResultsWe propose permGWAS, an efficient LMM reformulation based on 4D tensors that can provide permutation-based significance thresholds. We show that our method outperforms current state-of-the-art LMMs with respect to runtime and that permutation-based thresholds have lower false discovery rates for skewed phenotypes compared to the commonly used Bonferroni threshold. Furthermore, using permGWAS we re-analyzed more than 500 Arabidopsis thaliana phenotypes with 100 permutations each in less than 8 days on a single GPU. Our re-analyses suggest that applying a permutation-based threshold can improve and refine the interpretation of GWAS results.Availability and implementationpermGWAS is open-source and publicly available on GitHub for download: https://github.com/grimmlab/permGWAS.Supplementary informationSupplementary data are available at Bioinformatics online.