bluuebunny/crossref_metadata_2025 huggingface dataset:
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

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

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
Synchronization of Belousov–Zhabotinsky oscillators with electrochemical coupling in a spontaneous process
Authors: Liu Yifan , Pérez-Mercader Juan , Kiss István Z.
Published: September 2022

A passive electrochemical coupling approach is proposed to induce spontaneous synchronization between chemical oscillators. The coupling exploits the potential difference between a catalyst redox couple in the Belousov–Zhabotinsky (BZ) reaction, without external feedback, to induce surface reactions that impact the kinetics of the bulk system. The effect of coupling in BZ oscillators under batch condition is characterized using phase synchronization measures. Although the frequency of the oscillators decreases nonlinearly over time, by a factor of 2 or more within 100 cycles, the coupling is strong enough to maintain synchronization. In such a highly drifting system, the Gibbs–Shannon entropy of the cyclic phase difference distribution can be used to quantify the coupling effect. We extend the Oregonator BZ model to account for the drifting natural frequencies in batch condition and for electrochemical coupling, and numerical simulations of the effect of acid concentration on synchronization patterns are in agreement with the experiments. Because of the passive nature of coupling, the proposed coupling scheme can open avenues for designing pattern recognition and neuromorphic computation systems using chemical reactions in a spontaneous process.
Formation of Si nanoparticles by pulsed discharge of Si strips in distilled water
Authors: Zhong Longhai , Gao Xin , Qiao Jinchao , Zhang Xueying , Xiao Zeqi , Chen Pengwan
Published: September 2022

Si nanoparticle features multiple excellent properties, such as high theoretical capacity of 4200 mAh/g and low volume expansion effect, and it is regarded as an outstanding anode electrode material for Li-ion batteries. In this study, we obtained Si nanoparticles through pulsed discharge of Si strips and analyzed the pulsed discharge process based on recorded current data. The recovered samples were characterized by various techniques, such as XRD, Raman spectroscopy, SEM, and TEM. The characterization results confirm that the recovered samples are smooth spherical Si nanoparticles smaller than 200 nm. Our investigation reveals that the charging voltage is a key factor to adjust the size distribution of recovered Si nanoparticles. In the charging voltage range of 4–7 kV, the increase of charging voltage value decreases D90 (the particle size at the 90% undersize point in the size distribution) of recovered Si nanoparticles from 48.7 to 24.9 nm. In the charging voltage range of 7–12 kV, the increase of charging voltage value increases D90 of recovered Si nanoparticles from 24.9 to 66.5 nm. Thus, the critical charging voltage value is 7 kV, at which condition D90 of formed Si nanoparticles is the minimum (24.9 nm). In addition, the analysis of discharge current curves indicates three discharge stages, including semiconductor joule heating, conductor joule heating, and plasma discharge, which possess correlation to the size distribution of formed Si nanoparticles.
A setup for grazing incidence fast atom diffraction
Authors: Pan Peng , Rad Jaafar Najafi , Roncin Philippe
Published: September 2022

We describe a UHV setup for grazing incidence fast atom diffraction (GIFAD) experiments. The overall geometry is simply a source of keV atoms facing an imaging detector. Therefore, it is very similar to the geometry of reflection high energy electron diffraction experiments used to monitor growth at surfaces. Several custom instrumental developments are described making GIFAD operation efficient and straightforward. The difficulties associated with accurately measuring the small scattering angle and the related calibration are carefully analyzed.
Bound modes in the continuum based phononic waveguides
Authors: Rahman Adib , Pal Raj Kumar
Published: September 2022

We analytically predict and numerically demonstrate the existence of a family of bound modes in the continuum (BICs) in bi-layered spring-mass chains. A coupled array of such chains is then used to illustrate transversely bound waves propagating along a channel in a lattice. We start by considering the compact region formed by coupling two spring-mass chains with defects and predict bound modes arising due to reflection symmetries in this region. Dispersion analysis of a waveguide consisting of an array of appropriately coupled bi-layered chains reveals the presence of a branch having bound modes in the passband. Finally, detailed numerical analyses verify the existence of a BIC and its propagation through the waveguide at passband frequencies without energy leakage. The framework allows us to achieve BICs and their propagation for any arbitrary size and location of the compact region. Such BICs open avenues for novel classes of resonators with extremely high Q factors due to zero energy leakage and allow for guiding confined waves in structures without requiring bandgaps.
Transport and nonequilibrium phase transitions in polygonal urn models
Authors: Cirillo Emilio N. M. , Colangeli Matteo , Di Francesco Antonio , Kröger Martin , Rondoni Lamberto
Published: September 2022

We study the deterministic dynamics of N point particles moving at a constant speed in a 2D table made of two polygonal urns connected by an active rectangular channel, which applies a feedback control on the particles, inverting the horizontal component of their velocities when their number in the channel exceeds a fixed threshold. Such a bounce-back mechanism is non-dissipative: it preserves volumes in phase space. An additional passive channel closes the billiard table forming a circuit in which a stationary current may flow. Under specific constraints on the geometry and on the initial conditions, the large N limit allows nonequilibrium phase transitions between homogeneous and inhomogeneous phases. The role of ergodicity in making a probabilistic theory applicable is discussed for both rational and irrational urns. The theoretical predictions are compared with the numerical simulation results. Connections with the dynamics of feedback-controlled biological systems are highlighted.
Enhanced piezoelectric properties and domain morphology under alternating current electric field poled in [001]-oriented PIN-PMN-PT single crystal
Authors: Song Kexin , Ma Ming , Hu Qingyuan , Qiao Liao , Zhao Jinyan , Qiu Chaorui , Liu Jinfeng , Luan Peng , Guo Haisheng , Li Fei , Li Zhenrong , Fan Shiji , Xu Zhuo
Published: September 2022

The piezoelectric and dielectric properties of PMN-PT single crystals were significantly enhanced by alternating current electric field poling (ACP). In this work, to investigate the mechanisms of piezoelectric performance enhancement in relaxor ferroelectric single crystals by ACP, a [001]-oriented PIN-PMN-PT single crystal with a diameter of 3 in was grown by the modified Bridgman method, and a series of single crystal samples within 100 mm of the height of the crystal boule were prepared. Compared with their direct current electric field poling (DCP) counterparts, the electrical properties of single crystal samples at different heights by ACP were regularly enhanced. The piezoelectric coefficient d33 and the dielectric constant ɛ33 of the rhombohedral samples both increased by nearly 20%. Based on the results of polarized light microscopy, the domain wall in [001]-poled ACP samples could not be observed along the [001] direction. The brightness of polarized light propagating along the [010] orientation was enhanced after ACP. The domain images of {100} in the DCP and ACP samples were observed by piezoelectric force microscopy. The results showed that the domain size of ACP samples increased. The existence of layered domains can be clearly found in the scanning electron microscopy results of the stress fracture surface of the ACP sample. According to the analysis, the improvement of the piezoelectric performance in ACP samples comes from the elimination of the 71° domain walls. This work demonstrates that certain ACPs can regulate the domain structure and steadily improve the piezoelectric properties of R-phase PIN-PMN-PT single crystals.
Electron temperature gradient driven transport model for tokamak plasmas
Authors: Rafiq T. , Wilson C. , Luo L. , Weiland J. , Schuster E. , Pankin A. Y. , Guttenfelder W. , Kaye S.
Published: September 2022

A new model for electron temperature gradient (ETG) modes is developed as a component of the multi-mode anomalous transport module [Rafiq et al., Phys Plasmas 20, 032506 (2013)] to predict a time-dependent electron temperature profile in conventional and low aspect ratio tokamaks. This model is based on two-fluid equations that govern the dynamics of low-frequency short- and long-wavelength electromagnetic toroidal ETG driven drift modes. A low collisionality NSTX discharge is used to scan the plasma parameter dependence on the ETG real frequency, growth rate, and electron thermal diffusivity. Electron thermal transport is discovered in the deep core region where modes are more electromagnetic in nature. Several previously reported gyrokinetic trends are reproduced, including the dependencies of density gradients, magnetic shear, β and gradient of β (β′), collisionality, safety factor, and toroidicity, where β is the ratio of the plasma pressure to the magnetic pressure. The electron heat diffusivity associated with the ETG mode is discovered to be on a scale consistent with the experimental diffusivity determined by power balance analysis.
The influence of illumination conditions in the measurement of built-in electric field at p–n junctions by 4D-STEM
Authors: da Silva Bruno C. , Momtaz Zahra S. , Bruas Lucas , Rouviére Jean-Luc , Okuno Hanako , Cooper David , den-Hertog Martien I.
Published: September 2022

Momentum resolved 4D-STEM, also called center of mass (CoM) analysis, has been used to measure the long range built-in electric field of a silicon p–n junction. The effect of different STEM modes and the trade-off between spatial resolution and electric field sensitivity are studied. Two acquisition modes are compared: nanobeam and low magnification (LM) modes. A thermal noise free Medipix3 direct electron detector with high speed acquisition has been used to study the influence of low electron beam current and millisecond dwell times on the measured electric field and standard deviation. It is shown that LM conditions can underestimate the electric field values due to a bigger probe size used but provide an improvement of almost one order of magnitude on the signal-to-noise ratio, leading to a detection limit of 0.011 MV cm−1. It is observed that the CoM results do not vary with acquisition time or electron dose as low as 24 e−/A2, showing that the electron beam does not influence the built-in electric field and that this method can be robust for studying beam sensitive materials, where a low dose is needed.
Drag reduction and the Vogel exponent of a flexible beam in transient shear flows
Authors: Rahimi Ali Mehdizadeh , Lustig Steven R. , Bardhan Jaydeep P. , Jamali Safa
Published: September 2022

Interactions between a flexible beam and a fluid in a channel are of great relevance to biological hairy surfaces, aquatic vegetation, marine life (e.g., fish gills), and many industrial systems alike. While steady state response of a beam to such flows is fairly well-explored, their behavior in the transient regime is not fully understood. A series of numerical simulations are performed to study the laminar Couette flow of an incompressible viscous fluid past an elastic beam in a two-dimensional channel. The flexible beam is perpendicular to the direction of flow, and its base is fixed to the stationary bottom of the channel. We measure the evolution of the Vogel exponent, drag reduction, and reconfiguration number during the transient and steady-state response of the fluid–structure system for different geometrical and physical properties. Our benchmark shows a good agreement between numerical and experimental observations. Our results show that the system's steady-state response at different bulk-fluid velocities can be reproduced by investigating the shear flow response during the transient regime. We define a new variable that characterizes the evolution of the local velocity profile in the proximity of the free end of the beam and use that to characterize the transient-regime response. The analysis yields insight into the competing effects of elasticity of the beam and non-linear flow response.
Relative permeability as a stationary process: Energy fluctuations in immiscible displacement
Authors: McClure James E , Fan Ming , Berg Steffen , Armstrong Ryan T. , Berg Carl Fredrik , Li Zhe , Ramstad Thomas
Published: September 2022

Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work, we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large length scales and relying on averaging in both space and time to homogenize the behavior. Explicit criteria are obtained to define stationary conditions: (1) there can be no net change for extensive measures of the system state over the time averaging interval; (2) the net energy inputs into the system are zero, meaning that the net rate of work done on the system must balance with the heat removed; and (3) there is no net work performed due to the contribution of internal energy fluctuations. Results are then evaluated based on direct numerical simulation. Dynamic connectivity is observed during steady-state flow, which is quantitatively assessed based the Euler characteristic. We show that even during steady-state flow at low capillary number (Ca∼1×10−5), typical flow processes will explore multiple connectivity states. The residence time for each connectivity state is captured based on the time-and-space average. The distribution for energy fluctuations is shown to be multi-modal and non-Gaussian when terms are considered independently. However, we demonstrate that their sum is zero. Given an appropriate choice of the thermodynamic driving force, we show that the conventional relative permeability relationship is sufficient to model the energy dissipation in systems with complex pore-scale dynamics that routinely alter the structure of fluid connected pathways.
Revisit of the oblique-breakdown regime in supersonic boundary layers and mechanism of the extra amplification of streak modes
Authors: Song Runjie , Dong Ming , Zhao Lei
Published: September 2022

In the low-Mach-number supersonic boundary layers, the oblique-breakdown regime may be the most efficient route to trigger the laminar–turbulent transition, because the most unstable Mack first mode always appears as an oblique wave. In this paper, we revisit this issue by use of the nonlinear parabolized stability equation (NPSE) approach and particularly focus on the extra amplification of the streak mode generated by the direct interaction of the introduced oblique modes. This mechanism is then well explained based on the weakly nonlinear analysis, and its predictions on the evolution of the streak mode and the two-dimensional traveling-wave mode are quantitatively confirmed by the NPSE calculations. Additionally, the important role of the streak mode, leading to the secondary instability, on triggering the transition onset is identified.
Semiflexible polymer solutions. II. Fluctuations and Frank elastic constants
Authors: Ghosh Ashesh , MacPherson Quinn , Wang Zhen-Gang , Spakowitz Andrew J.
Published: September 2022

We study the collective elastic behavior of semiflexible polymer solutions in a nematic liquid-crystalline state using polymer field theory. Our polymer field-theoretic model of semiflexible polymer solutions is extended to include second-order fluctuation corrections to the free energy, permitting the evaluation of the Frank elastic constants based on orientational order fluctuations in the nematic state. Our exact treatment of wormlike chain statistics permits the evaluation of behavior from the nematic state, thus accurately capturing the impact of single-chain behavior on collective elastic response. Results for the Frank elastic constants are presented as a function of aligning field strength and chain length, and we explore the impact of conformation fluctuations and hairpin defects on the twist, splay, and bend moduli. Our results indicate that the twist elastic constant Ktwist is smaller than both bend and splay constants (Kbend and Ksplay, respectively) for the entire range of polymer rigidity. Splay and bend elastic constants exhibit regimes of dominance over the range of chain stiffness, where Ksplay > Kbend for flexible polymers (large-N limit) while the opposite is true for rigid polymers. Theoretical analysis also suggests the splay modulus tracks exactly to that of the end-to-end distance in the transverse direction for semiflexible polymers at intermediate to large-N. These results provide insight into the role of conformation fluctuations and hairpin defects on the collective response of polymer solutions.
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

This 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

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.
Conformable fractional heat equation with fractional translation symmetry in both time and space
Authors: Chung W S , Gungor A , Kříž J , Lütfüoğlu B C , Hassanabadi H
Published: September 2022

We investigate the fractional heat equation with fractional translation in both time and position with different fractional orders. As examples, we consider a rod and an α-disk with an initial constant temperature and discuss their cooling processes in the examined formalism.
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

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

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

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

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 < .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

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

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

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

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

Motivation

Genome-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.

Results

We 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 implementation

permGWAS is open-source and publicly available on GitHub for download: https://github.com/grimmlab/permGWAS.

Supplementary information

Supplementary data are available at Bioinformatics online.
DrDimont: explainable drug response prediction from differential analysis of multi-omics networks
Authors: Hiort Pauline , Hugo Julian , Zeinert Justus , Müller Nataniel , Kashyap Spoorthi , Rajapakse Jagath C , Azuaje Francisco , Renard Bernhard Y , Baum Katharina
Published: September 2022

Motivation

While it has been well established that drugs affect and help patients differently, personalized drug response predictions remain challenging. Solutions based on single omics measurements have been proposed, and networks provide means to incorporate molecular interactions into reasoning. However, how to integrate the wealth of information contained in multiple omics layers still poses a complex problem.

Results

We present DrDimont, Drug response prediction from Differential analysis of multi-omics networks. It allows for comparative conclusions between two conditions and translates them into differential drug response predictions. DrDimont focuses on molecular interactions. It establishes condition-specific networks from correlation within an omics layer that are then reduced and combined into heterogeneous, multi-omics molecular networks. A novel semi-local, path-based integration step ensures integrative conclusions. Differential predictions are derived from comparing the condition-specific integrated networks. DrDimont’s predictions are explainable, i.e. molecular differences that are the source of high differential drug scores can be retrieved. We predict differential drug response in breast cancer using transcriptomics, proteomics, phosphosite and metabolomics measurements and contrast estrogen receptor positive and receptor negative patients. DrDimont performs better than drug prediction based on differential protein expression or PageRank when evaluating it on ground truth data from cancer cell lines. We find proteomic and phosphosite layers to carry most information for distinguishing drug response.

Availability and implementation

DrDimont is available on CRAN: https://cran.r-project.org/package=DrDimont.

Supplementary information

Supplementary data are available at Bioinformatics online.
SimBu: bias-aware simulation of bulk RNA-seq data with variable cell-type composition
Authors: Dietrich Alexander , Sturm Gregor , Merotto Lorenzo , Marini Federico , Finotello Francesca , List Markus
Published: September 2022

Motivation

As complex tissues are typically composed of various cell types, deconvolution tools have been developed to computationally infer their cellular composition from bulk RNA sequencing (RNA-seq) data. To comprehensively assess deconvolution performance, gold-standard datasets are indispensable. Gold-standard, experimental techniques like flow cytometry or immunohistochemistry are resource-intensive and cannot be systematically applied to the numerous cell types and tissues profiled with high-throughput transcriptomics. The simulation of ‘pseudo-bulk’ data, generated by aggregating single-cell RNA-seq expression profiles in pre-defined proportions, offers a scalable and cost-effective alternative. This makes it feasible to create in silico gold standards that allow fine-grained control of cell-type fractions not conceivable in an experimental setup. However, at present, no simulation software for generating pseudo-bulk RNA-seq data exists.

Results

We developed SimBu, an R package capable of simulating pseudo-bulk samples based on various simulation scenarios, designed to test specific features of deconvolution methods. A unique feature of SimBu is the modeling of cell-type-specific mRNA bias using experimentally derived or data-driven scaling factors. Here, we show that SimBu can generate realistic pseudo-bulk data, recapitulating the biological and statistical features of real RNA-seq data. Finally, we illustrate the impact of mRNA bias on the evaluation of deconvolution tools and provide recommendations for the selection of suitable methods for estimating mRNA content. SimBu is a user-friendly and flexible tool for simulating realistic pseudo-bulk RNA-seq datasets serving as in silico gold-standard for assessing cell-type deconvolution methods.

Availability and implementation

SimBu is freely available at https://github.com/omnideconv/SimBu as an R package under the GPL-3 license.

Supplementary information

Supplementary data are available at Bioinformatics online.
Increasing confidence in proteomic spectral deconvolution through mass defect
Authors: Clasen Milan A , Kurt Louise U , Santos Marlon D M , Lima Diogo B , Liu Fan , Gozzo Fabio C , Barbosa Valmir C , Carvalho Paulo C
Published: September 2022

Motivation

Confident deconvolution of proteomic spectra is critical for several applications such as de novo sequencing, cross-linking mass spectrometry and handling chimeric mass spectra.

Results

In general, all deconvolution algorithms may eventually report mass peaks that are not compatible with the chemical formula of any peptide. We show how to remove these artifacts by considering their mass defects. We introduce Y.A.D.A. 3.0, a fast deconvolution algorithm that can remove peaks with unacceptable mass defects. Our approach is effective for polypeptides with less than 10 kDa, and its essence can be easily incorporated into any deconvolution algorithm.

Availability and implementation

Y.A.D.A. 3.0 is freely available for academic use at http://patternlabforproteomics.org/yada3.

Supplementary information

Supplementary information is available at Bioinformatics online.