bluuebunny/crossref_metadata_2025_split huggingface dataset:
RECENT DEVELOPMENTS IN COMPUTERISED ANALYSIS OF THERMOLUMINESCENCE GLOW CURVES: SOFTWARE CODES, MECHANISMS AND DOSIMETRIC APPLICATIONS
Authors: Horowitz Y S , Oster L , Reshes G , Nemirovsky D , Ginzburg D , Biderman S , Bokobza Y , Sterenberg M , Eliyahu I 
Published: June 2022

Abstract
The computerised deconvolution of thermoluminescence glow curves into component glow peaks is discussed in detail with special emphasis on advances of the subject post 2013. A plethora of computer codes have been developed using models based on first-order kinetics, second-orders kinetics, interactive traps and continuous distributions of activation energies. The glow curves of several materials are displayed and discussed along with new and improved dosimetric applications:precision effects of heating rate, heavy charged particles, mixed field α/ϒ dosimetry, fading and dose–response linearity. Finally recommendations are made for future efforts.
LncRNA SNHG11 promotes the malignant transformation of human bronchial epithelial cells induced by beryllium sulfate
Authors: Deng Weihua , Sun Zhanbing , Chen Shaoxiong , Li Guilan , Liu Xiuli , Huang Lian , Zhang Zhaohui 
Published: June 2022

Abstract

Background
Beryllium and its compounds are carcinogenicity, but the mechanisms through which this occurs have yet to be clarified. Accumulating evidence exists that long noncoding RNAs (lncRNAs) play an important role in occurrence and development of cancer.

Aims and Methods
To explore the carcinogenic mechanism of beryllium, human bronchial epithelial cells (16HBE) were treated with 50 μM beryllium sulfate (BeSO4) for 45 passages (~23 weeks). The expression levels of lncRNA SNHG7, SNHG11, SNHG15, MIR22HG, GMPS, and SIK1 were detected at passage 0 (P0), 15 (P15), 25 (P25), 35 (P35), and 45 (P45).

Results
The results indicated that enhanced cell proliferation, extensive clones in soft agar, protein expressions of up-regulated matrix metalloproteinase 9 (MMP9), matrix metalloproteinase 2 (MMP2), proliferating cell nuclear antigen (PCNA), cyclin D1, and down-regulated p53 were all observed at the 45th passage in 16HBE cells. Thus, BeSO4-transformed 16HBE cells (T-16HBE) were established. Meanwhile, the study found that the expression of lncRNA SNHG11 was elevated during malignant transformation. Knockdown of SNHG11 in T-16HBE cells blocked cell proliferation, invasion, and migration, and decreased the protein levels of MMP9, MMP2, PCNA, cyclin D1, but increased p53.

Conclusions
The studies revealed that SNHG11 acts as an oncogene in the malignant transformation of 16HBE cells induced by BeSO4, which signifies progress in the study of the carcinogenic mechanism of beryllium.
SARS-CoV-2 RT-PCR positivity in relation to clinical and demographic characteristics in residents of border quarantine centres, Khyber Pakhtunkhwa, Pakistan: a prospective cohort study
Authors: Imran Muhammad , Uddin Azhar , Ambade Preshit , Khan Sajjad , Wahab Abdul , Akbar Hussain , Iqbal Zafar , Ernst Kacey 
Published: June 2022

AbstractBackgroundAs international travellers were the primary source of sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, border checkpoints became an important tool to isolate cases. We determined the period prevalence and SARS-CoV-2 reverse transcription polymerase chain reaction positivity in relation to clinical and demographic characteristics in healthy travellers quarantined at the Pakistan–Afghanistan border.MethodsThe study was conducted from 15 to 25 April 2020. Period prevalence was calculated and the association between positivity and individuals’ age, sex and occupation were assessed using χ2 and Mantel–Haenszel tests. Logistic regression was used to calculate adjusted odds ratios (ORs) for each age group. Time-to-event (TTE) analysis was conducted to check the difference in positivity among various groups.ResultsIn a total of 708 individuals, 71 tested positive (10%). Compared with those ≤20 y of age, the sex- and occupation-adjusted odds of testing positive were less among the older age group (41–60 y; OR 0.26, p=0.008). Taxi drivers had higher odds of testing positive (OR 4.08, p&lt;0.001). Kaplan–Meier curves and hazard ratios (0.32, p&lt;0.01) showed that the positivity period differed significantly across the pre-symptomatic vs asymptomatic group (26 vs 14 d).ConclusionsThe cases who were likely to acquire infection through occupational exposure largely remained asymptomatic. For effective control of transmission and the emergence of new variants, testing capacities should be revamped with effective isolation measures.
Inhibition of PECAM‐1 Significantly Delays Leukocyte Extravasation into the Subcortex Post‐Stroke
Authors: Arias Erika , Nadkarni Neil , Fang Raymond , Haynes Maureen , Batra Ayush , Muller William , Sullivan David 
Published: June 2022

Background and PurposeCurrent therapies for ischemic stroke focus on reperfusion but do not address the acute inflammatory response that results in significant reperfusion injury. To advance future therapies, a thorough understanding of the precise spatiotemporal underpinnings of leukocyte extravasation and infiltration is necessary. We describe the evolution of the inflammatory response in a mouse transient middle cerebral artery occlusion (tMCAO) stroke model at several time points after reperfusion and the modulation of this response with PECAM blockade.MethodsThe transient Middle Cerebral Artery Occlusion model (90 minutes of ischemia followed by reperfusion) was used to simulate large vessel occlusion stroke and recanalization. We used wide field and confocal immunofluorescence microscopy to examine the exact distribution of neutrophils with close examination of the leukocyte position with regard to the brain vasculature and the perivascular space. Flow cytometry of single cell suspensions was used to confirm cell identity at different time points post‐stroke.ResultsLarge ischemic strokes involving both the subcortex and cortex (over 20% of the ischemic hemisphere) were induced in mice. At 12 and 24 hours, leukocyte recruitment and extravasation was primarily localized to the cortical surface. This contrasts with other organs where there is considerable migration of neutrophils deep into the inflamed tissue by 24 hours. Flow cytometry showed at 24 hours a majority of leukocytes were neutrophils. Over 48 to 72 hours, leukocytes were increasingly found deeper into the subcortex. Throughout the infarct (determined with triphenyl tetrazolium chloride staining), leukocyte recruitment was not uniform but rather organized in clusters. Disrupting leukocyte diapedesis with PECAM function‐blocking monoclonal antibody restricted leukocytes to within 500 microns of the surface when compared to control; and this was still evident at 72 hours (n=3 mice per group, p<0.01, Control 46% ± 4.0 %; PECAM‐1 Ab 62% ± 5.0%). High‐resolution wide‐field microscopy confirmed inhibition of TEM by PECAM‐1 blockade at 24 hours. Flow cytometry showed approximately equal numbers of monocytes and neutrophils at 72 hours.ConclusionsOur findings demonstrate that leukocyte infiltration into a stroke evolves over several days following reperfusion. The use of PECAM blockade modulates the natural progression of leukocytes into the infarcted stroke bed. A better understanding of leukocyte spatiotemporal infiltration and its regulators could help inform the next generation of therapeutic interventions.
The Psychological and Somatic Consequences of Digital Amputation
Authors: Skoff Hillel , Skoff Hannah 
Published: June 2022

Background:
Major limb amputation is a devastating potential outcome of trauma, tumor, or disease. Much has been written about the physical, functional, economic, and psychological consequences of major limb loss. In contradistinction, considerably less has been written concerning the consequences of “minor” limb loss, specifically single partial digit amputations. Are minor limb (partial single digit) amputations associated with symptoms of psychological disorder similar to those reported for major limb amputations?

Methods:
We conducted a clinical research study through interview and examination of 25 adult patients (average age: 45 years) who had suffered a single partial digit amputation to determine if symptoms of depression, anxiety, anger, or posttraumatic stress disorder newly occurred, and if such symptoms correlated with the surgical outcome. Questionnaires for Quick-DASH, Michigan Hand Score, and Diagnostic and Statistical Manual of Mental Disorders-5 Psychological Profile testing were completed.

Results:
All but one of the patients suffered from psychological symptoms for a minimum of 3 months. Symptom resolution time averaged 6 months for seven of the 25 patients. For 18 of the 25 patients, both psychological disturbance and neuroma pain were ongoing. The Psychological Profile scores suggesting pathology were inversely related to the scores on the Quick-Dash and Michigan Hand (somatic) questionnaires indicating wellness (P < 0.03).

Conclusions:
(1) Even minor partial amputations of single digits can trigger significant psychological disturbance; the study hypothesis is validated. (2) Psychological and somatic outcomes are directly correlative. (3) Mitigating neuroma pain and verbally offering psychological support services early in the postamputation period should improve the clinical outcome of digital amputations.
Whole-Blood and Peripheral Mononuclear Cell Transcriptional Response to Prolonged Altitude Exposure in Well-Trained Runners
Authors: Sutehall Shaun , Malinsky Fernanda , Shurlock Jonathan , Wang Guan , Bosch Andrew , Pitsiladis Yannis P. 
Published: June 2022

Background:
Recombinant human erythropoietin (rHuEpo) abuse by athletes threatens the integrity of sport. Due to the overlap in physiological response to rHuEpo and altitude exposure, it remains difficult to differentiate changes in hematological variables caused by rHuEpo or altitude, and therefore, other molecular methods to enhance anti-doping should be explored.

Objective:
To identify the hematological and transcriptomic response to prolonged altitude exposure typical of practices used by elite athletes.

Design:
Longitudinal study.

Setting:
University of Cape Town and Altitude Training Centre in Ethiopia.

Participants and Intervention:
Fourteen well-trained athletes sojourned to an altitude training camp in Sululta, Ethiopia (∼2400-2500 m above sea level) for 27 days. Blood samples were taken before arrival, 24 hours, and 9, 16, and 24 days after arrival at altitude in addition to 24 hours and 6, 13, and 27 days upon return to sea level.

Main Outcome Measures:
Blood samples were analyzed for hemoglobin concentration, hematocrit, and reticulocyte percentage. The transcriptomic response in whole blood and peripheral blood mononuclear cells (PBMC) were analyzed using gene expression microarrays.

Results:
A unique set of 29 and 10 genes were identified to be commonly expressed at every altitude time point in whole blood and PBMC, respectively. There were no genes identified upon return to sea level in whole blood, and only one gene within PBMC.

Conclusions:
The current study has identified a series of unique genes that can now be integrated with genes previously validated for rHuEpo abuse, thereby enabling the differentiation of rHuEpo from altitude exposure.
Sexually Transmitted Infection Testing, Prevalence, and Treatment Among Individuals Receiving HIV Preexposure Prophylaxis Within an Integrated Healthcare Delivery System
Authors: Schmidt Mark A. , Dickerson John F. , O'Keeffe-Rosetti Maureen C. , Salas Suzanne B. , Donald Judy L. , Tao Guoyu 
Published: June 2022

Background
Initial and follow-up sexually transmitted infection (STI) and human immunodeficiency virus (HIV) testing are recommended when taking HIV preexposure prophylaxis (PrEP). We assessed STI services before and after PrEP initiation among persons 18 years or older.

Methods
We conducted this retrospective cohort study at a US integrated healthcare delivery system. We measured HIV/STI testing rates, STI prevalence and treatment at 3 time points: (1) at PrEP initiation, (2) at 120 days, and (3) at 210 days.

Results
Of 685 PrEP initiators, 67.2% continued PrEP use at 120 days and 49.5% at 210 days. Of PrEP users, HIV and STI testing were greater than 85% and greater than 80%, respectively, at all 3 time points. Prevalence for any chlamydia, rectal chlamydia, and any gonorrhea, rectal gonorrhea, or pharyngeal gonorrhea was always high at the 120 days and 210 days (eg, 6.9%, 10.5%, 6.7%, 5.0%, and 5.2%, respectively, at the 120 days for continuous PrEP users). Over 90% of all individuals who tested positive for chlamydia and gonorrhea received antibiotic pharmacy fills within 7 days at 120 and 210 days. Monthly PrEP-related pharmacy cost was about $2259 to $2659. The proportion of the total medical cost that was PrEP-related pharmacy was about 82% for PrEP continuous users.

Conclusions
Although HIV/STI testing rates were high, they can still be improved during HIV PrEP management. High STI prevalence after PrEP initiation in this study suggests that patients taking PrEP are at risk of acquiring an STI. Interventions to improve STI services during PrEP management are continuously needed.
Unravelled multilevel transformation networks for predicting sparsely observed spatio-temporal dynamics
Authors: Saha Priyabrata , Mukhopadhyay Saibal 
Published: June 2022

In this paper, we address the problem of predicting complex, nonlinear spatio-temporal dynamics when available data are recorded at irregularly spaced sparse spatial locations. Most of the existing deep learning models for modelling spatio-temporal dynamics are either designed for data in a regular grid or struggle to uncover the spatial relations from sparse and irregularly spaced data sites. We propose a deep learning model that learns to predict unknown spatio-temporal dynamics using data from sparsely-distributed data sites. We base our approach on the radial basis function (RBF) collocation method which is often used for meshfree solution of partial differential equations. The RBF framework allows us to unravel the observed spatio-temporal function and learn the spatial interactions among data sites on the RBF-space. The learned spatial features are then used to compose multilevel transformations of the raw observations and predict its evolution in future time steps. We demonstrate the advantage of our approach using both synthetic and real-world climate data.
This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Gaussian processes meet NeuralODEs: a Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data
Authors: Bhouri Mohamed Aziz , Perdikaris Paris 
Published: June 2022

We present a machine learning framework (GP-NODE) for Bayesian model discovery from partial, noisy and irregular observations of nonlinear dynamical systems. The proposed method takes advantage of differentiable programming to propagate gradient information through ordinary differential equation solvers and perform Bayesian inference with respect to unknown model parameters using Hamiltonian Monte Carlo sampling and Gaussian Process priors over the observed system states. This allows us to exploit temporal correlations in the observed data, and efficiently infer posterior distributions over plausible models with quantified uncertainty. The use of the Finnish Horseshoe as a sparsity-promoting prior for free model parameters also enables the discovery of parsimonious representations for the latent dynamics. A series of numerical studies is presented to demonstrate the effectiveness of the proposed GP-NODE method including predator–prey systems, systems biology and a 50-dimensional human motion dynamical system.
This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
A physics-based digital twin for model predictive control of autonomous unmanned aerial vehicle landing
Authors: McClellan Andrew , Lorenzetti Joseph , Pavone Marco , Farhat Charbel 
Published: June 2022

This paper proposes a two-level, data-driven, digital twin concept for the autonomous landing of aircraft, under some assumptions. It features a digital twin instance (DTI) for model predictive control (MPC); and an innovative, real-time, digital twin prototype for fluid–structure interaction and flight dynamics to inform it. The latter digital twin is based on the linearization about a pre-designed glideslope trajectory of a high-fidelity, viscous, nonlinear computational model for flight dynamics; and its projection onto a low-dimensional approximation subspace to achieve real-time performance, while maintaining accuracy. Its main purpose is to predict in real time, during flight, the state of an aircraft and the aerodynamic forces and moments acting on it. Unlike static lookup tables or regression-based surrogate models based on steady-state wind tunnel data, the aforementioned real-time digital twin prototype allows the DTI for MPC to be informed by a truly dynamic flight model, rather than a less accurate set of steady-state aerodynamic force and moment data points. The paper describes in detail the construction of the proposed two-level digital twin concept and its verification by numerical simulation. It also reports on its preliminary flight validation in autonomous mode for an off-the-shelf unmanned aerial vehicle instrumented at Stanford University.
This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes applied to bubble dynamics
Authors: Charalampopoulos A. , Bryngelson S. H. , Colonius T. , Sapsis T. P. 
Published: June 2022

Solving the population balance equation (PBE) for the dynamics of a dispersed phase coupled to a continuous fluid is expensive. Still, one can reduce the cost by representing the evolving particle density function in terms of its moments. In particular, quadrature-based moment methods (QBMMs) invert these moments with a quadrature rule, approximating the required statistics. QBMMs have been shown to accurately model sprays and soot with a relatively compact set of moments. However, significantly non-Gaussian processes such as bubble dynamics lead to numerical instabilities when extending their moment sets accordingly. We solve this problem by training a recurrent neural network (RNN) that adjusts the QBMM quadrature to evaluate unclosed moments with higher accuracy. The proposed method is tested on a simple model of bubbles oscillating in response to a temporally fluctuating pressure field. The approach decreases model-form error by a factor of 10 when compared with traditional QBMMs. It is both numerically stable and computationally efficient since it does not expand the baseline moment set. Additional quadrature points are also assessed, optimally placed and weighted according to an additional RNN. These points further decrease the error at low cost since the moment set is again unchanged.This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
Deep learning for centre manifold reduction and stability analysis in nonlinear systems
Authors: Ghadami Amin , Epureanu Bogdan I. 
Published: June 2022

Bifurcations cause large qualitative and quantitative changes in the dynamics of nonlinear systems with slowly varying parameters. These changes most often are due to modifications that occur in a low-dimensional subspace of the overall system dynamics. The key challenge is to determine what that low-dimensional subspace is, and construct a low-order model that governs the dynamics in that subspace. Centre manifold theory can provide a theoretical means to construct such low-order models for strongly nonlinear systems that undergo bifurcations. Performing a centre manifold analysis, however, is particularly challenging when the system dimensionality is high or impossible when an accurate model of the system is not available. This paper introduces a data-driven approach for identifying a reduced order model of the system based on centre manifold theory. The approach does not require a model of the full order system. Instead, a deep learning approach capable of identifying the centre manifold and the transformation to the centre space is created using measurements of the system dynamics from random perturbations. This approach unravels the characteristics of the system dynamics in the vicinity of bifurcations, providing critical information regarding the behaviour of the system.
This article is part of the theme issue ‘Data-driven prediction in dynamical systems’.
The native cell differentiation program aberrantly recapitulated in yki3S/A-induced intestinal hyperplasia drives invasiveness and cachexia-like wasting phenotypes
Authors: Pranoto Inez K.A. , Lee Jiae , Kwon Young V. 
Published: June 2022

SummaryMany tumors recapitulate the developmental and differentiation program of their tissue of origin, a basis for tumor cell heterogeneity. Although stem-cell-like tumor cells are well-studied, the roles of tumor cells undergoing differentiation in inducing the phenotypes associated with advanced cancers remains to be elucidated. Here, we employ Drosophila genetics to demonstrate that the native differentiation program of intestinal stem cells plays a key role in determining an intestinal tumor’s capacity to invade and induce various non-tumor-autonomous phenotypes. The differentiation program that generates absorptive cells enterocytes is aberrantly recapitulated in the intestinal tumors generated through activation of the Yap1 ortholog Yorkie. Elimination of tumor cells in the enterocyte lineage allows stem cell-like tumor cells to grow but suppresses invasiveness and reshapes various phenotypes associated with cachexia-like wasting by altering the expression of tumor-derived factors. Our study provides insight into how a native differentiation program determines a tumor’s capacity to induce the phenotypes associated with advanced cancers and suggests that manipulating the differentiation programs co-opted in tumors might be a way to treat some complications of cancer, including cachexia.
Adaptation to climate change through dense planting for sustainable agriculture
Authors: Huang Zhixiong , He Xue , Zhao Xueqiang , Teng Wan , Hu Mengyun , Li Hui , Zhang Yijing , Tong Yiping 
Published: June 2022

AbstractOveruse of fertilizers increased greenhouse gases emissions, induced global climate changes and extreme weather and made future agriculture unsustainable. Engineering crops to adapt to stressed conditions is crucial. Here, we cloned a transcription factor TabZIP45 (basic region zipper), controlled by a microRNA binding site polymorphism, conferring adaptation to both nitrogen deficiency and dense planting. TabZIP45 interacted with TaFTL43 (Flowering locus T like43) to change gene expression regulation. TabZIP45 coordinated phosphatidylinositol diphosphate (PIP2) metabolism and calcium (Ca2+) signaling to adapt to environmental stresses. Knockout of TabZIP45-4B by genome editing rescued grain yield loss caused by nitrogen deficiency by modulation of TaDwarf4 under dense planting through Ca2+ signaling disruption. Thus, TabZIP45-4B edited wheat warranted a sustainable and environmentally friendly way to enhance grain yield under adverse conditions.One-Sentence SummaryCalcium and lipids integrated adverse environmental signaling to modulate plant growth