bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three molecular subtypes and a five‐gene signature for hepatocellular carcinoma based on m7G‐related classification
Authors: Yue Yuan , Tao Jie , An Dan , Shi Lei 
Published: October 2023

AbstractBackgroundThe current research investigated the heterogeneity of hepatocellular carcinoma (HCC) based on the expression of N7‐methylguanosine (m7G)‐related genes as a classification model and developed a risk model predictive of HCC prognosis, key pathological behaviors and molecular events of HCC.MethodsThe RNA sequencing data of HCC were extracted from The Cancer Genome Atlas (TCGA)‐live cancer (LIHC) database, hepatocellular carcinoman database (HCCDB) and Gene Expression Omnibus database, respectively. According to the expression level of 29 m7G‐related genes, a consensus clustering analysis was conducted. The least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression algorithm were applied to create a risk prediction model based on normalized expression of five characteristic genes weighted by coefficients. Tumor microenvironment (TME) analysis was performed using the MCP‐Counter, TIMER, CIBERSORT and ESTIMATE algorithms. The Tumor Immune Dysfunction and Exclusion algorithm was applied to assess the responses to immunotherapy in different clusters and risk groups. In addition, patient sensitivity to common chemotherapeutic drugs was determined by the biochemical half‐maximal inhibitory concentration using the R package pRRophetic.ResultsThree molecular subtypes of HCC were defined based on the expression level of m7G‐associated genes, each of which had its specific survival rate, genomic variation status, TME status and immunotherapy response. In addition, drug sensitivity analysis showed that the C1 subtype was more sensitive to a number of conventional oncolytic drugs (including paclitaxel, imatinib, CGP‐082996, pyrimethamine, salubrinal and vinorelbine). The current five‐gene risk prediction model accurately predicted HCC prognosis and revealed the degree of somatic mutations, immune microenvironment status and specific biological events.ConclusionIn this study, three heterogeneous molecular subtypes of HCC were defined based on m7G‐related genes as a classification model, and a five‐gene risk prediction model was created for predicting HCC prognosis, providing a potential assessment tool for understanding the genomic variation, immune microenvironment status and key pathological mechanisms during HCC development.
Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter‐Observer Variability
Authors: Jing Xueping , Wielema Mirjam , Monroy‐Gonzalez Andrea G. , Stams Thom R.G. , Mahesh Shekar V.K. , Oudkerk Matthijs , Sijens Paul E. , Dorrius Monique D. , van Ooijen Peter M.A. 
Published: October 2023

BackgroundAccurate breast density evaluation allows for more precise risk estimation but suffers from high inter‐observer variability.PurposeTo evaluate the feasibility of reducing inter‐observer variability of breast density assessment through artificial intelligence (AI) assisted interpretation.Study TypeRetrospective.PopulationSix hundred and twenty‐one patients without breast prosthesis or reconstructions were randomly divided into training (N = 377), validation (N = 98), and independent test (N = 146) datasets.Field Strength/Sequence1.5 T and 3.0 T; T1‐weighted spectral attenuated inversion recovery.AssessmentFive radiologists independently assessed each scan in the independent test set to establish the inter‐observer variability baseline and to reach a reference standard. Deep learning and three radiomics models were developed for three classification tasks: (i) four Breast Imaging‐Reporting and Data System (BI‐RADS) breast composition categories (A–D), (ii) dense (categories C, D) vs. non‐dense (categories A, B), and (iii) extremely dense (category D) vs. moderately dense (categories A–C). The models were tested against the reference standard on the independent test set. AI‐assisted interpretation was performed by majority voting between the models and each radiologist's assessment.Statistical TestsInter‐observer variability was assessed using linear‐weighted kappa (κ) statistics. Kappa statistics, accuracy, and area under the receiver operating characteristic curve (AUC) were used to assess models against reference standard.ResultsIn the independent test set, five readers showed an overall substantial agreement on tasks (i) and (ii), but moderate agreement for task (iii). The best‐performing model showed substantial agreement with reference standard for tasks (i) and (ii), but moderate agreement for task (iii). With the assistance of the AI models, almost perfect inter‐observer variability was obtained for tasks (i) (mean κ = 0.86), (ii) (mean κ = 0.94), and (iii) (mean κ = 0.94).Data ConclusionDeep learning and radiomics models have the potential to help reduce inter‐observer variability of breast density assessment.Level of Evidence3Technical EfficacyStage 1
Exponential stability and numerical analysis of Timoshenko system with dual‐phase‐lag thermoelasticity
Authors: Bouraoui Hamed Abderrahmane , Djebabla Abdelhak , Sahari Mohamed Lamine , Boulaaras Salah 
Published: October 2023

AbstractThis study aims to investigate the well‐posedness and stability of a thermoelastic Timoshenko system with non‐Fourier heat conduction. Specifically, we analyze the system using the dual‐phase‐lag (DPL) model, which incorporates two thermal relaxation times, and , to model non‐instantaneous heat propagation. Applying the semigroup approach, we demonstrate the existence and uniqueness of the solutions. Subsequently, we introduce a novel stability parameter using the multiplier method. Exponential decay is proven for the case of with . Using Gearhart–Prüss theorem, we show the lack of exponential stability when and . Numerically, we present a fully discrete approximation using the finite element method and the backward Euler scheme, and we provide some numerical simulations to show the discrete energy decay and the behavior of solutions.
Study of mercury resistance and Fourier transform infrared spectroscopy‐based metabolic profiling of a potent Bacillus tropicus strain from forest soil
Authors: Saha Barnan K. , Roy Vivek , Saha Jayanti , Chatterjee Abhik , Pal Ayon 
Published: October 2023

AbstractMercury (Hg) is a highly toxic heavy metal and Hg‐resistant indigenous bacterial isolates may offer a green and cost‐effective bioremediation strategy to counter Hg contamination. In this study, a potent Hg‐resistant bacterium was isolated from the forest soil of a bird sanctuary. Identification using matrix‐assisted laser desorption ionization‐time of flight mass spectrometry depicted the isolate as a strain of Bacillus tropicus, validated by morphological, biochemical, and molecular studies. The isolate demonstrated biological Hg removal efficiency and capacity of 50.67% and 19.76 mg g−1, respectively. The plasmid borne resistance determinant, merA, encoding mercuric reductase, was detected in the bacterium endowing it with effective Hg volatilization and resistance capability. A Fourier‐transform infrared spectroscopic comparative metabolic profiling revealed the involvement of various functional groups like –COOH, ‐CH2, ‐OH, PO4− and so on, resulting in differential spectral patterns of the bacterium both in control and Hg‐exposed situations. A temporal variance in metabolic signature was also observed during the early and mid‐log phase of growth in the presence of Hg. The bacterium described in this study is the first indigenous Hg‐resistant strain isolated from the Uttar Dinajpur region, which could be further explored and exploited as a potent bioresource for Hg remediation.
Potentially traumatic pandemic stressors and anxiety‐related sleep disturbance among Latinx persons
Authors: Buitron Victor , Mayorga Nubia Angelina , Vujanovic Anka A. , Schmidt Norman B. , Zvolensky Michael J. 
Published: October 2023

AbstractLatinx persons have endured elevated rates of traumatic stress related to the COVID‐19 pandemic. The effect of potentially traumatic pandemic stressors on anxiety‐related sleep disturbances, a factor implicated in trauma‐related psychopathology, is largely unexamined in this population. The present study evaluated the additive effect of potentially traumatic pandemic stressors (e.g., hospitalization) on anxiety‐related sleep disturbances. Further, given within‐group disparities across Latinx communities with intersectional identities and COVID‐19–related risk factors, comparisons of the likelihood of pandemic stressors, by subgroup (i.e., older persons, individuals with chronic illness, and Black Latinx persons), were evaluated. Participants were 292 (29.8% female, Mage = 35.03 years, SD = 8.72) Latinx adults who completed a questionnaire battery during a period of high contagion (June 2020–July 2021). There were statistically significant differences across groups such that participants who experienced any potentially traumatic pandemic stressors reported elevated scores on indices of anxiety, depressive symptoms, and anxiety‐related sleep disturbances compared to those who had not experienced these stressors, ds = 0.54–93. Hierarchical regression analysis revealed that hospitalization was associated with anxiety‐related sleep disturbances after controlling for age, sex, chronic illness history, other stressors, anxiety, depressive symptoms, and somatic symptom burden, ΔR2 = .01. Black Latinx identity and chronic illness were significantly associated with potentially traumatic pandemic‐related stressors. This is the first empirical work to evaluate the role of potentially traumatic pandemic stressors on sleep disturbances among Latinx persons and indicates that hospitalization in a pandemic context has an incremental effect on sleep disturbances in this minoritized group.
A detailed reaction mechanism for hexamethyldisiloxane combustion via experiments and ReaxFF molecular dynamics simulations
Authors: Huang Yaosong , Chen Hao 
Published: October 2023

AbstractHexamethyldisiloxane (HMDSO) is one of the main impurities in the syngas produced from sewage and landfill plants. In order to utilize this syngas or control the characteristics of the generated silica particles, it is crucial to understand the chemical kinetics of HMDSO combustion. This study investigated the process of HMDSO combustion using synchrotron radiation mass spectrometry (SRMS), gas chromatography (GC), and ReaxFF molecular dynamics simulations. First, the force field used for ReaxFF simulation was validated by comparing the energies of different bond lengths, bond angles, and dihedral angles with the ones from DFT calculations. Good agreements were found. Then, ReaxFF simulations of HMDSO combustion with this force field were conducted under various conditions, which include different equivalence ratios (0.67, 1.0, and 1.5) and temperatures ranging from 2000 to 3500 K. The oxidation characteristics of HMDSO were analyzed, including the evolution of gas products and particle formation. Finally, based on the results from experiments and ReaxFF simulations, the reaction pathways, reaction lists, and reaction kinetics data during HMDSO combustion were obtained. A detailed reaction mechanism was proposed and validated by applying it in modeling the H2/HMDSO/O2 combustion systems. The temperature and part of the gas products such as CO and CO2 as well as SiO could be well predicted.
Ultra‐Low‐Crosstalk Silicon Arrayed‐Waveguide Grating (De)multiplexer with 1.6‐nm Channel Spacing
Authors: Shen Xiaowan , Li Chenlei , Zhao Weike , Li Huan , Shi Yaocheng , Dai Daoxin 
Published: October 2023

AbstractA silicon arrayed‐waveguide grating (AWG) with 1.6‐nm channel spacing is proposed and realized with high performances for dense wavelength‐division (de)multiplexing systems. For the present AWG, the arrayed waveguides are broadened uniformly to be far beyond the singlemode regime, so that random phase errors and propagation loss are minimized even without any additional requirement for the fabrication process. Particularly, Euler‐bends are introduced for the arrayed waveguides to shrink the device footprint and suppress any excitation of higher‐order modes. As an example, a 16 × 16 AWG (de)multiplexer is realized with a compact footprint of 600 × 800 µm2 by using single‐etched 220‐nm‐thick silicon photonic waveguides. When using the fabricated AWG to demultiplex the channels launched from the central input port, the excess loss and the adjacent‐channel crosstalk of the central output port are ≈2.2 and ≈−31.7 dB, respectively. Such an AWG is one of the best among silicon implementations.
A branch‐and‐price algorithm for identical parallel machine scheduling with multiple milestones
Authors: Zhong Weiya , Cui Jia , Jiang Yiwei 
Published: October 2023

AbstractThis article considers an identical parallel‐machine task scheduling problem motivated by operations management of online services. A task with an integer processing time can be split into sub‐tasks with integer processing times. Each task has multiple integer milestones and at each milestone a nonnegative penalty will occur. The penalty value of a task at a milestone is a convex nonincreasing function of the completed amount by this milestone. Our objective is to determine a feasible schedule for all the tasks on given identical parallel machines, such that the sum of all tasks' total penalty at all milestones is minimized. We prove the NP‐hardness of this problem in the ordinary sense and develop a branch‐and‐price algorithm. Computational experiments utilizing data from an online service operations survey show that this algorithm is singularly efficient and promising.
Robust optimization for the integrated berth allocation and quay crane assignment problem
Authors: Wang Chong , Miao Lixin , Zhang Canrong , Wu Tao , Liang Zhe 
Published: October 2023

AbstractThis paper studies the berth allocation and quay crane assignment problem (denoted by BACAP) under uncertainty. We assume that the ships' arrival and operation time is uncertain in this problem. We merge the proactive and reactive strategies to address the two‐stage robust optimization (denoted by RO) model for the BACAP to obtain a complete schedule with robustness. We obtain the berth allocation and quay crane assignment with a proactive strategy in the first stage. In the second stage, we formulate a rescheduling model with a reactive strategy considering the sensitivity towards the change in the complete schedule. The second stage model is based on the prospect theory, a quantitative way to describe the stakeholders' perception, including the port managers and shipowners, of the deviation from the baseline plan. The two stages are iterated until a favorable schedule with high robustness is found. To illustrate the superiority of the two‐stage robust optimization model with the prospect theory for the complete schedule, we give an intuitive example to compare the performance among the related models. The two‐stage RO model with the prospect theory for the complete schedule can generate a lower cost and higher robustness schedule. As for the solution methods, the column and constraint generation (denoted by C&CG) algorithm is applied to obtain the exact solution for the two‐stage RO model. Moreover, we propose the scenario‐constrained C&CG (denoted by SC) algorithm, which can reduce constraints and variables for the master problem to accelerate the solving process of the two‐stage RO model. In addition, the optimality of the SC algorithm is verified by analyzing the pattern of the occurrence of the worst‐case scenarios. Besides, to tackle the large‐scale instances, we propose the schedule‐fixed (denoted by SF) algorithm, in which the results of the previous iterations are treated as fixed. The SF algorithm can increase computing efficiency with a small gap compared to the optimal solution value. Furthermore, extensive numerical experiments are conducted on both real‐life instances and randomly generated instances to verify the superiority and generality of our model and algorithms.
Crack phase‐field enhanced finite cover method for dynamic fracture at finite strain
Authors: Han Jike , Hirayama Daigo , Shintaku Yuichi , Moriguchi Shuji , Terada Kenjiro 
Published: October 2023

SummaryThis study presents an enhancement of the diffusive‐discrete crack transition scheme (10.1002/nme.7169) to describe dynamic fracture at finite strain. In the enhanced scheme, the crack initiation, propagation, and bifurcation processes are determined from an energy minimization problem based on crack phase‐field theory, and the predicted diffusive crack is replaced by the discrete representation using the finite cover method. In the meantime, numerical damping is introduced to maintain computational stability and avoid distortion of the physical mesh in the finite cover context. By taking advantage of the features of the diffusive‐discrete crack transition scheme, the proposed approach enables us to stably simulate a series of dynamic fracture events involving crack initiation at an arbitrary location, propagation, and bifurcation in arbitrary directions, arbitrary divisions of an original object into multiple portions, and independent motions of divided portions. After spatial and temporal discretizations by the finite cover method and the Newmark method are described, as well as the simulation algorithm of the enhanced finite cover‐based staggered iterative procedure for dynamic fracture, several representative numerical examples are presented to demonstrate the performance and capabilities of the developed approach.
Assessment of menstrual health in adolescent and young adults with sickle cell disease
Authors: Notice Brittany , Soffer Elizabeth , Tickle Kelly , Xiang Yijin , Gee Beatrice E. , Sidonio, Jr Robert F. , Sokkary Nancy , Batsuli Glaivy 
Published: October 2023

AbstractBackgroundSickle cell disease (SCD) is associated with hypercoagulability, but adults with SCD also have an increased incidence of bleeding including heavy menstrual bleeding (HMB). HMB is common among adolescent females, but the impact of HMB in pediatric SCD is unclear. The objectives of this study were to examine menstrual health status, knowledge, and quality of life (QOL).MethodsWe performed a single‐institutional multi‐clinic cross‐sectional study comprised of a five‐part survey in pediatric participants with SCD. The survey included the validated Menstrual Bleeding Questionnaire (MBQ) and Self‐administered Bleeding Assessment Tool (Self‐BAT).ResultsForty‐eight participants with a median age of 16 years (range: 12–21 years) completed the study. The mean age at onset of menarche was 13 ± 1.3 years. On the MBQ, 29% reported heavy/very heavy menstrual flow, 61% reported moderate or severe dysmenorrhea, and 96% had menses lasting less than 1 week. The Self‐BAT revealed that 42% of participants reported a history of HMB. Participants with severe dysmenorrhea or HMB had higher MBQ scores, corresponding to worse QOL. Despite this, less than 20% of participants had attempted any hormonal therapy for menstrual regulation. The odds of hormonal therapy utilization were comparable among participants on hydroxyurea versus not on hydroxyurea (odds ratio 1.58, 95% confidence interval [CI]: 0.33–7.56).ConclusionsThe prevalence of HMB and dysmenorrhea is high among adolescents and young women with SCD. Strategies that incorporate menstrual health assessment into routine medical care in this population would help address this important area of pediatric health.
Experimental investigation on failure mechanisms of hybrid steel/GFRP hat‐shaped beams under bending loading
Authors: Duan Libin , Lu Debiao , Liu Xing , Zhang Yu , Xu Wei , Du Zhanpeng , Jiang Haobing 
Published: October 2023

AbstractThe bending failure mechanism and energy absorption characteristics of hybrid metal/composite structures are the keys to the side collision safety of automobiles. The purpose of this paper is to investigate the bending behavior and failure mechanism of hybrid Steel/GFRP hat‐shaped beams under three‐point bending. Firstly, both quasi‐static and dynamic three‐point bending tests were conducted on Steel, GFRP and hybrid Steel/GFRP hat‐shaped beams. Then, the effect of layups and loading speeds on the bending failure behaviors of GFRP hat‐shaped beams were investigated, and the five stages of the bending process of GFRP hat‐shaped beams were exposed. Finally, the failure mechanism of hybrid Steel/GFRP hat‐shaped beams under both quasi‐static and dynamic three‐point bending were investigated. It is found that the failure mechanism is related to the interaction effect between the Steel and GFRP parts in the hybrid Steel/GFRP hat‐shaped beam. In the bending failure process, the crack propagation in GFRP parts is delayed by the plastic deformation of the connected Steel parts, which improves the energy absorption and load carrying capacities of the hybrid Steel/GFRP hat‐shaped beam, and this improvement in the whole bending process is quantitatively exposed in this work. Besides, it is found that with the same impact energy, the load carrying capacity of the hybrid Steel/GFRP hat‐shaped beam can be increased by the loading roll diameter increasing.Highlights
A bending process with five stages of GFRP hat‐shaped beams is exposed.
The loading speed increases impact loads due to the strain rate strengthening.
The interaction between Steel and GFRP improves the load carrying capacity.
The load carrying improvement is due to crack propagation delay in GFRP parts.
The greater loading roll diameter increases the load carrying capacity.
Physician knowledge, practice patterns, and barriers encountered regarding guideline‐concordant use of bone modifying agents for prostate cancer
Authors: Mitchell Aaron P. , Persaud Sonia , Palyca Paul , Salner Andrew , Farooki Azeez , Ostroff Jamie S. , Morris Michael J. , Chimonas Susan 
Published: October 2023

AbstractBackgroundGuidelines recommend bone‐modifying agents (BMAs) for patients with castrate‐resistant prostate cancer (CRPC) and bone metastasis, but not for castrate‐sensitive prostate cancer (CSPC). Physicians beliefs and practices regarding BMA therapy are poorly understood.MethodsThis was a qualitative interview study with embedded Likert‐scale elements. Study participants were physicians who treat prostate cancer, located within an academic cancer center or an affiliated community‐based network. Participants were asked about their experiences and practice patterns regarding BMA therapy. Participants used Likert‐scale items to identify the most common barriers to guideline‐concordant BMA use and the most effective potential interventions. Participants were subsequently asked to rank the three most common barriers and the three most effective interventions to reduce underuse (for CRPC) and overuse (for CSPC).ResultsNineteen physicians were invited and 15 participated; one physician did not answer some questions as outside of their practice scope. All were aware of the recommendation for BMAs in CRPC. 14% (2/14) were unaware of the recommendation against BMA use for CSPC; an additional 29% (4/14) believed that BMA use could be appropriate for CSPC depending on the metastatic disease burden. 36% (5/14) were unaware of recommendations for screening and treatment of low bone mineral density. The most common barriers (occurring “often” or “sometimes”) were obtaining dental clearance (11/15) and insufficient clinic time (6/15). The interventions identified as most effective to reduce underuse were dental navigation (11/15) and electronic medical record (EMR)‐based guidance (9/15). The interventions identified as most effective to reduce overuse were peer‐to‐peer education (14/15) and EMR‐based guidance (13/15).ConclusionsAwareness of guideline recommendations for screening and treatment of low bone mineral density and against BMA use for CSPC was good, but not complete. Dental navigation, peer‐to‐peer education, and EMR‐based guidance were preferred intervention strategies to improve guideline‐concordant use.