bluuebunny/crossref_metadata_2025 huggingface dataset:
Global Quaternary Carbonate Burial: Proxy- and Model-Based Reconstructions and Persisting Uncertainties
Authors: Wood Madison , Hayes Christopher T. , Paytan Adina
Published: July 2022

Constraining rates of marine carbonate burial through geologic time is critical for interpreting reconstructed changes in ocean chemistry and understanding feedbacks and interactions between Earth's carbon cycle and climate. The Quaternary Period (the past 2.6 million years) is of particular interest due to dramatic variations in sea level that periodically exposed and flooded areas of carbonate accumulation on the continental shelf, likely impacting the global carbonate budget and atmospheric carbon dioxide. These important effects remain poorly quantified. Here, we summarize the importance of carbonate burial in the ocean–climate system, review methods for quantifying carbonate burial across depositional environments, discuss advances in reconstructing Quaternary carbonate burial over the past three decades, and identify gaps and challenges in reconciling the existing records. Emerging paleoceanographic proxies such as the stable strontium and calcium isotope systems, as well as innovative modeling approaches, are highlighted as new opportunities to produce continuous records of global carbonate burial.
Hybrid Improper Ferroelectricity: A Theoretical, Computational, and Synthetic Perspective
Authors: Benedek Nicole A. , Hayward Michael A.
Published: July 2022

We review the theoretical, computational, and synthetic literature on hybrid improper ferroelectricity in layered perovskite oxides. Different ferroelectric mechanisms are described and compared, and their elucidation using theory and first-principles calculations is discussed. We also highlight the connections between crystal chemistry and the physical mechanisms of ferroelectricity. The experimental literature on hybrid improper ferroelectrics is surveyed, with a particular emphasis on cation-ordered double perovskites, Ruddlesden–Popper and Dion–Jacobson phases. We discuss preparative routes for synthesizing hybrid improper ferroelectrics in all three families and the conditions under which different phases can be stabilized. Finally, we survey some synthetic opportunities for expanding the family of hybrid improper ferroelectrics.
An Improved BP Neural Network Algorithm for the Evaluation System of Innovation and Entrepreneurship Education in Colleges and Universities
Authors: Sun Xuying , Zhang Yu
Published: July 2022

The ability of college students has important index to evaluate the training quality of universities. Domestic scholars begin to cultivate spirit and ability of students. With the rapid development of tourism industry and the continuous emergence of “tourism +” new business forms, there is an urgent demand for professionals with outstanding innovation and entrepreneurship ability. China’s education field urgently needs a system that can scientifically evaluate the teaching quality. The purpose of this topic is to enrich the theoretical methods of universities. Taking S University as the research sample, the relevant evaluation index system is set up, and, on this basis, the evaluation model of network is established, providing relevant basis for evaluation and cultivation of universities. According to certain evaluation indicators, this paper constructs the main framework of teaching quality evaluation in colleges and universities. 7 representative universities in China are randomly selected, 6 of which are samples and 1 university is the research target, MATLAB is used to calculate the scores of each index, the current situation of quality in a university is analyzed, and corresponding improvements opinion is proposed. Based on the analysis of the current education in a university, it is found that, in the current education, innovation and entrepreneurship knowledge and professional knowledge are taken into account, and the academic achievements are remarkable, forming a preliminary education system, but it is also found that there are some problems of low educational practicality, and corresponding suggestions for this problem are put forward. If the evaluation system is put into practical application, it will improve the education level of cultivating innovative entrepreneurial talents in tourism major in universities.
Research on Permeability Enhancement Model of Pressure Relief Roadway for Deep Coal Roadway Strip
Authors: Wang Zhonghua , Cao Jianjun , Liu Jun , Li Chengcheng
Published: July 2022

Aiming at the problem of permeability enhancement in deep coal roadway strip, it proposed a pressure relief roadway permeability enhancement model, and the model was verified through experiments, theoretical calculations, and field tests. The experiment reveals that the unloading of gas-containing coal can achieve the effect of permeability enhancement. Theoretical calculation shows that with the increase of the distance from the coal seam, the overlying coal seam’s permeability enhancement multiple and the width of the significant permeability enhancement zone gradually decrease, and the width of the general permeability enhancement zone gradually increases and then stabilizes. Field tests show that the pressure relief roadway is arranged 9 m directly below the coal seam; the overlying coal strata has a significant pressure relief and permeability enhancement effect. This research can provide reference value for the high-efficiency permeability enhancement in the deep coal roadway strip.
Using Blockchain Technology and Sharing Culture to Promote Sustainable Forest Management in Tribal Communities
Authors: Peng Yixiao , Huang Wenyi
Published: July 2022

Forest protection is crucial to ensuring the balance between human beings and ecology. This study explores the key role played by communities that originally lived in forest‐protected areas in implementing the traditional management of forests. The unified management mode previously used by the state power can no longer meet the demands of modern times; hence, multiple types of management systems should be implemented to enable adaption to the original ecology of forest areas. A multimodal management mode should be adopted to restore the original ecology of forest areas. The adoption of this management system can restore a forest to its original state (i.e., the state that existed prior to the entry of state power). The forest has been in a state of ecological balance involving numerous species since ancient times. However, in the modern field of science, the passive restoration of a community’s self‐governance ability could be unsustainable and unstable. To improve this situation, blockchain technology can first be used to improve the community management of a forest, such that the capabilities of the original local community can be improved; second, tourism promotion benefits both the community and the forest. When a community in a forest develops the tourism industry with the support of blockchain technology, the information and resources of all parties can be widely connected with the larger world, and this considerably increases success rates; finally, the traditional spiritual culture of a community, such as the culture of sharing, should be promoted. In addition to the skillful utilization of technology, culture can improve the traditional forest management ability of tribal communities who live in native forest areas in terms of their personality traits. Overall, we conclude that: against the evolution history of the over one hundred years, the adoption of new technology for forest management is inherently a creative innovation for the tribal community’s entrepreneurial development.
The Catalytic Influence of Polymers and Surfactants on the Rate Constants of Reaction of Maltose with Cerium (IV) in Acidic Aqueous Medium
Authors: Dahadha Adnan A. , Hassan Mohammed , Mfarej Tamara , Bani Issa Razan , Saadh Mohamed J. , Al-Dhoun Mohammad , Abunuwar Mohammad , Talat Nesrin T.
Published: July 2022

Kinetics of the reaction of maltose with cerium ammonium sulfate were analyzed spectrophotometrically by observing the decrease of the absorbance of cerium (IV) at 385 nm in the presence and absence of polyethylene glycols (600, 1500, and 4000) and polyvinylpyrrolidone (PVP), in addition to anionic micelles of sodium dodecyl sulfate (SDS), cationic micelles of cetyltrimethylammonium bromide (CTAB) and non-ionic micelles of Tween 20 surfactants. Generally, there is little literature about using the polymers (PEGs and PVP) as catalysts in the oxidation-reduction reactions. Therefore, the major target of this work was to investigate the influence of the nature of polymers and surfactants on the oxidation rates of maltose by cerium (IV) in acidic aqueous media, as well as employing the Piszkiewicz model to explain the catalytic effect. The kinetic runs were derived by adaptation of the pseudo first-order reaction conditions with respect to the cerium (IV). The reaction was found to be first-order with respect to the oxidant and fractional-order to maltose and H2SO4. The reaction rates were enhanced in the presence of polymer and micellar catalysis. Indeed, the surfactants were found to work perfectly close to their critical micelle concentrations (CMC). Electrostatic interaction and H-bonding appear to play an influential role in binding maltose molecules to polymer/surfactant micelles, while oxidant ions remain at the periphery of the Stern layer within the micelle.
Dynamical System in Chaotic Neurons with Time Delay Self‐Feedback and Its Application in Color Image Encryption
Authors: Xu Yao-Qun , Zhen Xin-Xin , Tang Meng
Published: July 2022

The time delay caused by transmission in neurons is often ignored, but it is demonstrated by theories and practices that time delay is unavoidable. A new chaotic neuron model with time delay self‐feedback is proposed based on Chen’s chaotic neuron. The bifurcation diagram and Lyapunov exponential diagram are used to analyze the chaotic characteristics of neurons in the model when they receive the output signals at different times. The experimental results exhibit that it has a rich dynamic behavior. In addition, the randomness of chaotic series generated by chaotic neurons with time delay self‐feedback under different conditions is verified. In order to investigate the application of this model in image encryption, an image encryption scheme is proposed. The security analysis of the simulation results shows that the encryption algorithm has an excellent anti‐attack ability. Therefore, it is necessary and practical to study chaotic neurons with time delay self‐feedback.
Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach
Authors: Shelatkar Tejas , Urvashi Dr. , Shorfuzzaman Mohammad , Alsufyani Abdulmajeed , Lakshmanna Kuruva
Published: July 2022

Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can diagnose brain tumors by employing magnetic resonance imaging (MRI) as a supporting technology. We propose transfer learning approaches for a deep learning model to detect malignant tumors, such as glioblastoma, using MRI scans in this study. This paper presents a deep learning-based approach for brain tumor identification and classification using the state-of-the-art object detection framework YOLO (You Only Look Once). The YOLOv5 is a novel object detection deep learning technique that requires limited computational architecture than its competing models. The study used the Brats 2021 dataset from the RSNA-MICCAI brain tumor radio genomic classification. The dataset has images annotated from RSNA-MICCAI brain tumor radio genomic competition dataset using the make sense an AI online tool for labeling dataset. The preprocessed data is then divided into testing and training for the model. The YOLOv5 model provides a precision of 88 percent. Finally, our model is tested across the whole dataset, and it is concluded that it is able to detect brain tumors successfully.
A Hybrid Matching Network for Fault Diagnosis under Different Working Conditions with Limited Data
Authors: He Qiuchen , Li Shaobo , Li Chuanjiang , Zhang Junxing , Zhang Ansi , Zhou Peng
Published: July 2022

Intelligent fault diagnosis methods based on deep learning have achieved much progress in recent years. However, there are two major factors causing serious degradation of the performance of these algorithms in real industrial applications, i.e., limited labeled training data and complex working conditions. To solve these problems, this study proposed a domain generalization-based hybrid matching network utilizing a matching network to diagnose the faults using features encoded by an autoencoder. The main idea was to regularize the feature extractor of the network with an autoencoder in order to reduce the risk of overfitting with limited training samples. In addition, a training strategy using dropout with random changing rates on inputs was implemented to enhance the model’s generalization on unseen domains. The proposed method was validated on two different datasets containing artificial and real faults. The results showed that considerable performance was achieved by the proposed method under cross-domain tasks with limited training samples.
Task-Oriented Network Abnormal Behavior Detection Method
Authors: Li Tao , Dong Wenzhe , Hu Aiqun , Han Jinguang
Published: July 2022

Since network systems have become increasingly large and complex, the limitations of traditional abnormal packet detection have gradually emerged. The existing detection methods mainly rely on the recognition of packet features, which lack the association of specific applications and result in hysteresis and inaccurate judgement. In this paper, a task-oriented abnormal packet behavior detection method is proposed, which creatively collects action identifications during the execution of network tasks and inserts security labels into communication packets. Specifically, this paper defines the network tasks as a collection of state and action sequences to achieve the fine-grained division of the execution of network tasks, performs Hash value matching based on random communication string and action identification sequence for packet authentication, and proposes a mechanism of action identification sequence matching and abnormal behavior decision-making based on a finite state machine, according to the fine-grained monitoring of task execution action sequence. Furthermore, to verify the validity of the anomaly detection method proposed in this paper, a prototype based on the FTP communication platform is constructed, on which the simulation experiments, including the DDOS attack and backdoor attack, are conducted. The experimental results show that the proposed task-oriented abnormal behavior detection method can effectively intercept network malicious data packets and realize the active security defense for network systems.
Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator
Authors: Zeng Minling , Liu Runmin , Gao Ming , Jiang Yizhang
Published: July 2022

With the advancement of Internet technology and the widespread use of mobile smartphones, urban e-commerce is becoming increasingly saturated. Rural e-commerce ushered in a new era of development. How to improve rural logistics carrying capacity to keep up with the development of rural e-commerce and better serve the development of rural e-commerce has become a hot topic. The purpose of this study is to predict logistics demand in the context of the development of rural e-commerce. We develop an indicator system for forecasting rural logistics demand in Guangdong Province. The GM (1,1) gray forecasting model with a weakening buffer operator was used to forecast rural logistics demand in Guangdong Province. According to the results, the prediction model has good matching and precision. It was also found that demand for rural logistics in Guangdong Province will generally rise in the short to medium term. Based on the findings of this study, the government should stimulate demand for rural consumer goods, encourage technological innovation, develop an Internet-rural logistics mode, and meet the supply requirements of rural logistics based on the situation of each region.
Design and Implementation of ALU Using Graphene Nanoribbon Field‐Effect Transistor and Fin Field‐Effect Transistor
Authors: Rebecca Florance D. , Prabhakar B. , Mishra Manoj Kumar
Published: July 2022

Arithmetic and logical unit (ALU) are the core operational programmable logic block in microprocessors, microcontrollers, and real‐time‐integrated circuits. The conventional ALUs were developed using complementary metal oxide semiconductor (CMOS) technology, which resulted in excessive power consumptions, path delays, and number of transistors. Therefore, this article focuses on the design and development of hybrid delay‐controlled reconfigurable ALU (DCR‐ALU) using field‐effect transistor (FinFET) and graphene nanoribbon field‐effect transistor (GnrFET) technologies. Initially, a novel carry output predictable full adder (COPFA) and carry input selectable full adders (CISFA) are developed using multiplexer selection logic; then, delay‐controlled hybrid adder (DCHA) and delay‐controlled hybrid subtractor (DCHS) are developed using these full adders. In addition, a unified delay‐controlled hybrid adder and subtractor (DCHAS) is developed by combining these DCHA and DCHS. Further, a delay controller array multiplier (DCAM) also developed using DCHA modules. Finally, DCR‐ALU is developed by adopting the DCHAS, DCAM, and logical operations. The obtained simulation results shows that the proposed nanotechnology‐based models outperformed the conventional adders and subtractors in terms of area, power, and delay reduction.
Effects of Baffle Height and Baffle Location on Heat Transfer and Flow Profiles in a Baffled Duct: A CFD Analysis
Authors: Boonloi Amnart , Jedsadaratanachai Withada
Published: July 2022

CFD analysis of flow and heat transfer characteristics in a baffled duct is reported. The baffle locations (

s
=
0.05
H
–
0.40
H

), flow paths (V-apex directing Downstream or VD and V-apex directing Upstream or VU), and baffle heights (

b
=
0.05
H
–
0.30
H

) are investigated in the laminar flow regime with the Reynolds number based on the entry conditions between 100 and 2,000. Solutions of the present work are obtained by the finite volume method (a commercial code). Key mechanisms such as fluid streams, impinging streams, and disturbed thermal boundary layer in the baffled duct are observed. The baffle locations have high impact on flow and heat transfer behavior. The best heat transfer rate of the baffled duct is 15.55 times higher than that of the general duct with no baffle, while the optimum TEF is 4.06.
Research on the Design and Analysis Method of the Bird Collision-Resistant Structure of Electric Aircraft Composite Cap-Type-Reinforced Wall Panel-Filled Battery Integration
Authors: Zhang Yongjie , Zhang Nuo , Cui Bo , Shi Lei
Published: July 2022

Compared with traditional energy aircraft, electric/hybrid aircraft show the advantages of environmental protection and low carbon and have been considered one of the most promising directions for the future development of the aviation industry. However, the battery (battery box) structure employed in electric/hybrid aircraft generally faces several problems (e.g., insufficient rigidity/strength and low structural load-bearing efficiency). In this study, the composite cap-type-reinforced wall plate structure commonly applied in electric aircraft is developed to fill the battery structure using the internal cavity of the cap type, which leads to the formation of an integrated structure type of a composite cap-type-reinforced wall plate filled battery. The basic static strength analysis of the integrated structure was conducted to measure its basic load-bearing capacity. To investigate the impact resistance of the integrated structure, a series of bird collision simulations were conducted to analyze the impact position, impact angle, impact speed, and other factors on the integrated structure and the design direction of the composite cap-type-reinforced wall plate-filled battery-integrated structure against bird collision was summarized.
A Lightweight Human Action Classification Method for Green IoT Sport Applications
Authors: Xiao Da , Huang Tianyu , Li Yihao , Liu Chang , Zhang Fuquan
Published: July 2022

This paper proposes a lightweight human action classification method for Green Internet of Things (IoT) sport applications. This method classifies the human motion data collected by wearables or other IoT devices with energy-efficient techniques, by enabling a small number of sample training and incremental classification to achieve the purpose of energy-efficient. To lessen the complexity of the model and reduce the number of samples required for parameter estimation, we propose a shared Hidden Conditional Random Field (sHCRF) model. The sHCRF model adds a shared-classification layer structure to reduce the parameter computation. In the experiments, the classification accuracy of the sHCRF model is above 95%. This paper introduces an incremental learning method based on knowledge distillation. The new model suppresses the forgetting of existing classification knowledge while fitting new data to learn new classification knowledge. In the incremental scenarios, the classification accuracy of the sHCRF model is above 70%. The experimental results show that this method can lightly implement convenient and fast automatic classification of action acquisition.
Investigation on Mechanical and Durability Performance of Reinforced Concrete Containing Red Soil as Alternate for M‐Sand
Authors: Sebastin S. , David M. Franchis , Karthick Alagar , Singh Ashita , Vanjinathan J. , Kumar Sanjeev , Meem Mahseena Akter
Published: July 2022

The river sand is a primary parameter in the concrete structure. This work replaces accessible locally accessible substitution materials like red soil and manufactured sand (M‐Sand). In this paper, the mechanical properties and durability of concrete containing red soil and M‐Sand have been studied. In this investigation, M30 grade concrete was used, and tests were conducted for two sets of combinations; i.e., red soil as a partial replacement for river sand seems to be 20%, 30%, 40%, 50%, and 60%, and red soil as a partial replacement for manufactured sand (M‐Sand) seems to be 60%, 50%, 40%, 30%, and 20%. The compressive strength (7 days, 28 days, 90 days), split tensile strength (28 days), and flexural strength (28 days) have been determined. The combination S4‐50% river sand + 50% red soil and S9‐70% M‐Sand + 30% red soil gives more compressive strength than other combinations. Similarly, the combination S3‐60% river sand + 40% red soil and S6‐40% M‐Sand + 60% red soil gives more flexural and split tensile strength than other combinations. The scanning electron microscope (SEM) analysis, EDAX analysis, and durability tests like alkalinity, sulfate attack, and chloride attack have also been studied.
IoT-Based Technological Framework for Inhibiting the Spread of COVID-19: A Pandemic Using Machine Learning and Fuzzy-Based Processes
Authors: Kaur Amandeep , Elarabawy Mahmoud M. , Abd-Elnaby Mohammed , Varadarajan Vijayakumar , Sharma Subhash
Published: July 2022

The COVID-19 infestation has resulted in the loss of the lives of millions of people and the destruction of commercial, communal, and healthcare systems around the world. To control these kinds of pandemics, complete knowledge of the traits and responses to the disease is required, and this knowledge can be gathered using various computational methods. These computational techniques can be very helpful in information building required for taking appropriate action timely and applying preventive mechanisms. Although there are numerous computational approaches that the researchers are applying over the past few months, there is a need to re-evaluate and compare these available techniques for finding out the best technique that can help reduce the extent of COVID-19. Hence, in this paper, we carried out a literature review to emphasize the assistance of various computational approaches around COVID-19. The paper presents a categorization of approaches such as multicriteria decision-making, fuzzy AHP, machine learning, neural network, and data science that have been used to deal with the epidemic. Furthermore, this study discusses various challenges experienced when accessing the COVID-19 data. The conclusions of the paper propose the best computational approach among all to be appraised for future investigations and implementations.
Innovative Mode of Human Resource Management of University Teachers Based on Intelligent Big Data Analysis
Authors: Bai Yuhong
Published: July 2022

In the era of knowledge economy, the competition between countries and enterprises is increasingly manifested in the competition of talents and education system. In this article, aiming at the drawbacks of the traditional HRM model of university teachers, we design and construct a management innovation model and decision-making model based on intelligent big data analysis. This article introduces DM technology. It also introduces the related knowledge of DM and the analysis and design process of HRM decision system. In this system, DM technology is used to analyze and process the existing data, predict the future situation, and provide auxiliary support for decision-making. Through simulation, the decision-making accuracy of this model can reach 95.68%, which is about 10.02% higher than other systems. It has certain practicability and reliability. This article makes a useful attempt for the application of DM technology in HRM. The research in this article is expected to play an important decision-making reference and service support for HRM of university teachers and further promote the development of HRM innovation of university teachers.
Stress Intensity Factors for Corner Cracks under Arbitrary Stress Fields in the Finite Plates Based on the Point Weight Function Method
Authors: Li Guo , Zhou Huimin , Liu Junbo , Xu Tongge , Ding Shuiting
Published: July 2022

Probabilistic damage tolerance assessment is an essential method to evaluate the safety of aeroengine rotors. The stress intensity factors (SIFs) are the core parameters. The weight function method can calculate SIF efficiently. The available weight functions for corner cracks are suitable for cracks with universal stresses. However, when cracks are under bivariant stress distributions, the lack of the weight function database makes the damage tolerance assessment impractical. Therefore, this paper derives the point weight functions for corner cracks, which are suited for cracks in real-world components with two-directional stress distributions. The response surface method is used to build the surrogate model of the point weight functions. By integrating the weight functions with the stress distributions, SIFs can be calculated with high accuracy. In sum, 81% of the differences between the point weight function method and finite element results are less than 10%.
Cancer among Immigrants: Diverse Histories, Diverse Disparities, Diverse Opportunities to Promote Equity
Authors: Dee Edward Christopher , Gomez Scarlett Lin
Published: July 2022

Immigrants–people who live in a country different from their country of birth–constitute approximately 250 million people globally. Migrants are diverse in their reasons for immigration, ranging from those who are forced to flee their home country for survival, to those seeking a better life. Migrants face diverse barriers in access to care. Therefore, it is critical in the context of cancer health to improve our understanding of the epidemiology of cancer amongst migrants to inform policy, screening, and management.

In this issue of Cancer Epidemiology, Biomarkers & Prevention, Yu and colleagues evaluate patterns in the incidence of infection-associated cancers–cancers of the stomach, liver, and cervix–amongst migrants in Australia. They demonstrate that the incidence of infection-related cancers is heterogeneous amongst immigrant populations, underscoring the value of studies that disaggregate groups in ways that reflect the diversity amongst these groups.

In this editorial, we contextualize the work of Yu and colleagues in the setting of studies exploring cancer health amongst migrants in various parts of the world. We call attention to disparities in risk factors, prevention, screening, and access to care. Finally, we call on the research and medical communities to work to elucidate their diverse stories, understand their diverse disparities, and act upon diverse opportunities to promote equity.

See related article by Yu et al., p. 1394
IMPACT: A Randomized Controlled Trial of an mHealth Physical Activity Intervention for Young Adult Cancer Survivors
Authors: Valle CG , Diamond M , Pinto BM , LaRose JG , Nezami BT , Hales DP , Deal AM , Heiling H , Rini CM , Rosenstein DL , Tate DF
Published: July 2022

Purpose: The IMPACT trial evaluated a theory-based mobile physical activity (PA) intervention on total PA (primary) and moderate-to-vigorous (MVPA) at 6 months in a nationwide sample of young adult cancer survivors (YACS). Methods: YACS (N=280) were randomized to either an intervention group or a self-help (control) group. All participants received digital tools (activity tracker, smart scale, Facebook group) and an individual videochat session. Intervention participants also received a 6-month mHealth program with components to promote increased PA (behavioral lessons, adaptive goal-setting, tailored feedback, tailored text messages, Facebook group prompts). PA was assessed via accelerometry and online questionnaire (Godin Leisure Time Exercise Questionnaire) at baseline and 6 months. Using linear mixed models and an intention-to-treat approach, we tested for group differences in changes from baseline to 6 months, adjusting for education, time since diagnosis, age, and accelerometer wear time. Results: Of 280 YACS (M=33.4 (SD 4.8) yrs, 81.8% women, 23.2% racial/ethnic minority individuals), 92.9% completed 6-month measures. Device-measured total PA min/wk (i.e., sum of light, moderate, and vigorous PA) increased from a mean of 1974.3 (SD=673.9) to 2024.3 (686.7) at 6 months in the intervention group (p=.26) and from 1814.9 (704.5) to 1877.7 (758.2) in the control group (p=.43), with no difference between groups (p=.84). Both groups increased MVPA min/wk over 6 months; increases were 24.7 min/wk (95% CI: 14.8, 34.6; p<.0001) in the intervention versus 11.4 min/wk (95% CI: 1.4, 21.4; p=.02) in the control (p=.07 between groups). Increases in MVPA were 99.7% and 41.6% over baseline in the intervention and control groups, respectively. Increases in self-reported total PA were significant; 123.3 min/wk (95 CI%: 94.5, 152.1; p<.0001) in the intervention versus 83.40 (95% CI: 49.30, 117.50; p<.0001) in the control (p=.08 between groups). Conclusions: While both groups increased total PA over 6 months, the intervention doubled the increase in MVPA min/wk relative to the control group, which is associated with important health benefits. Future research should examine moderators of effects to identify for whom, and under what conditions, the effectiveness varied.
Proton Pump Inhibitor Use and Obesity-Associated Cancers in the Women's Health Initiative
Authors: Ballinger TJ , Djuric Z , Sardesai S , Hovey K , Andrews C , Braskey TM , Rohan TE , Saquib N , Shadyab AH , Simon M , Wactawski-Wende J , Wallace R , Kato I
Published: July 2022

Purpose: Proton pump inhibitors (PPIs) inhibit fatty acid synthase (FAS), a critical enzyme in lipogenesis, energy balance, and cancer cell survival. We aimed to evaluate the association of PPI use with incidence of common obesity- related cancers in women: postmenopausal breast, colorectal, and endometrial cancers. Methods: Our study included 124,931 postmenopausal who were enrolled in the Women's Health Initiative (WHI) observational study and clinical trials, and had responded to a year 3 follow-up assessment. We examined prescription and over the counter use of PPI and/or histamine 2 receptor antagonists (H2RA) at baseline and year 3, to isolate potential effects of FAS inhibition by PPI rather than simply acid suppression. Incident cancer cases were physician-adjudicated. Cox proportional hazard regression models were used to estimate multivariable hazard ratios (HR) and 95% confidence intervals (CI) for associations between PPI and/or H2RA use and cancer incidence after year 3. Results: There were 7956 PPI ever users (with or without H2RA use) and 9398 H2RA only users. PPI or H2RA use was not associated with risk of breast cancer (n=9186 cases), compared to women who did not use either agent (HR 1.01, 95% CI 0.93-1.10 and HR 0.95 95% CI 0.87-1.03, respectively). The incidence of colorectal cancer (n=2280) was significantly lower in PPI users (HR 0.75, 95% CI 0.61-0.92), but not in H2RA users (HR 1.13, 95% CI 0.97-1.31). This association was strengthened with increasing duration (p=0.006) and potency (p=0.005) of PPI use and held regardless of BMI or NSAID use. PPI or H2RA use was not associated with endometrial cancer (n=1231) (HR 0.81, 95% CI 0.61-1.07 and HR 1.13, 95% CI 0.91-1.40, respectively), but showed a trend in decreased risk with increasing PPI potency (P=0.048). Conclusions: Among postmenopausal women, PPI use, but not H2RA use, demonstrated an inverse, dose-responsive association with colorectal cancer incidence. This was consistent with preclinical data that FAS inhibition prevents colon cancer progression and supports further investigation of this commonly used medication as a cancer preventive agent. PPI use was not associated with incidence of breast or endometrial cancer.
“Should I Give it to My Kids?”: Factors that Influence HPV Vaccine Hesitancy Among African American Parents
Authors: Washington A , Chabaan J , Fakih A , Ford S , Rutledge L , Lilly J , Clemons P , Thompson H
Published: July 2022

Purpose: The purpose of our study was to describe the influences that impact vaccine hesitancy in African American parents who have previously delayed or denied vaccinating their children against HPV. Methods: We conducted three focus groups, approx. 90 minutes each. Participants were recruited from various community clinics and organizations in Michigan. Using thematic analysis and the Vaccine Hesitancy Determinants framework, we described the experiences of parents who have delayed or denied vaccinating their children against HPV. Results: Twenty parents participated in the focus groups; the majority of the parents had Medicaid (75%), were employed full-time (55%), and had some college education but no degree (50%). Several contextual factors influenced decision-making: historical events, perceptions of both pharmaceutical and governmental figures, and perceived discrimination based on race and socioeconomic status. Whether it was the result of mistrust due to the ongoing Flint water crisis or concern over the profit-driven industry of pharmaceutical companies, these parents were deeply mistrustful of the motivations behind vaccination programs. Parental beliefs and attitudes focused on ensuring the health and safety of their children, which involved being hesitant to vaccinate. Some parents were swayed by vaccination experiences of personal acquaintances, while others maintained their hesitancy status. Knowledge and awareness in this group were mixed regarding the HPV vaccine. Most struggled to articulate the purpose of the vaccine thoroughly and often refused to vaccinate their children. Meanwhile, only a few vaccine-specific issues were relevant in group discussions, such as vaccination schedule and provider recommendation. Some parents viewed weak recommendations as a subtle signal to not vaccinate their children, while others viewed too strong of a recommendation as a cause for concern. Conclusion: Findings highlight parents' willingness to stick with their strong beliefs, despite recommendations from healthcare providers and personal acquaintances. Effective communications strategies are essential for health education and establishing a trustworthy patient-provider relationship.
Understanding Cancer Genetic Risk Assessment Intentions in a Tailored Risk Communication Intervention Randomized Controlled Trial
Authors: LeCompte CG , McDougall J , Walters ST , Toppmeyer D , Boyce TW , Lu S , Stroup A , Paddock L , Grumet S , Lin Y , Ani J , Heidt E , Kinney AY
Published: July 2022

Background: Pathogenic variants in cancer predisposition genes increase second, hereditary cancer risk among women with breast and/or ovarian cancer, and primary cancers in their relatives. National guidelines recommend cancer genetic risk assessment (CGRA) (genetic counseling and/or genetic testing) for women at increased hereditary breast and ovarian cancer (HBOC) risk. Yet, less than half of high risk women, including rural dwellers and racial minorities have accessed CGRA. Purpose: The Genetic Risk Assessment for Cancer Education and Empowerment Project (GRACE), a superiority trial, addressed this translational gap, testing the efficacy of a targeted print brochure (TP) vs tailored counseling and navigation (TCN) vs usual care (UC) on CGRA intentions. TCN targeted behavioral variables theorized to mediate CGRA intentions. We believe GRACE is the first study of its kind promoting guideline-based CGRA to women at increased HBOC risk. Methods: CGRA-eligible women were recruited from three state cancer registries (N=641), completed a baseline survey, and randomized to TCN, TP or UC. TP and TCN received the mailed educational brochure. TCN also engaged in a telephone-based decision coaching and navigation session using motivational interviewing and tailored materials based on the Extended Parallel Process Model and Health Action Process Approach. Participants completed a follow-up survey at one month. Results: TCN improved CGRA intentions compared to TP (0.64, p<0.001, CI 0.32, 0.97) and UC (0.69, p<0.001, CI 0.37, 1.02). Theoretical targets, perceived risk (0.77, p=0.02, CI 0.11, 1.44) and self-efficacy (0.67, p=0.04, CI 0.05, 1.28) mediated CGRA intentions in TCN. Stratification showed increases in CGRA intentions for TCN vs TP among non-Hispanic Whites, Hispanics, urban dwellers, and women with low health literacy and no family history of breast and/or ovarian cancer (FBOC). In TCN, perceived self-efficacy improved in women with no FBOC. Conclusions: Improvements in CGRA intentions and theorized mediators support use of tailored risk communication interventions in Hispanics and women with low health literacy and no FBOC. Further tailoring may improve CGRA intentions in Blacks, other minorities, rural dwellers, and women with high health literacy and FBOC.
Multiomic Characterization of High-Grade Serous Ovarian Carcinoma Enables High-Resolution Patient Stratification
Authors: Hollis Robert L. , Meynert Alison M. , Michie Caroline O. , Rye Tzyvia , Churchman Michael , Hallas-Potts Amelia , Croy Ian , McCluggage W. Glenn , Williams Alistair R.W. , Bartos Clare , Iida Yasushi , Okamoto Aikou , Dougherty Brian , Barrett J. Carl , March Ruth , Matakidou Athena , Roxburgh Patricia , Semple Colin A. , Harkin D. Paul , Kennedy Richard , Herrington C. Simon , Gourley Charlie
Published: July 2022

Purpose:

High-grade serous ovarian carcinoma (HGSOC) is the most common ovarian cancer type; most patients experience disease recurrence that accumulates chemoresistance, leading to treatment failure. Genomic and transcriptomic features have been associated with differential outcome and treatment response. However, the relationship between events at the gene sequence, copy number, and gene-expression levels remains poorly defined.

Experimental Design:

We perform multiomic characterization of a large HGSOC cohort (n = 362) with detailed clinical annotation to interrogate the relationship between patient subgroups defined by specific molecular events.

Results:

BRCA2-mutant (BRCA2m) and EMSY-overexpressing cases demonstrated prolonged survival [multivariable hazard ratios (HR) 0.40 and 0.51] and significantly higher first- and second-line chemotherapy response rate. CCNE1-gained (CCNE1g) cases demonstrated underrepresentation of FIGO stage IV cases, with shorter survival but no significant difference in treatment response. We demonstrate marked overlap between the TCGA- and Tothill-derived subtypes. IMR/C2 cases displayed higher BRCA1/2m frequency (25.5%, 32.5%) and significantly greater immune cell infiltration, whereas PRO/C5 cases had the highest CCNE1g rate (23.9%, 22.2%) and were uniformly low in immune cell infiltration. The survival benefit for cases with aberrations in homologous recombination repair (HRR) genes was apparent across all transcriptomic subtypes (HR range, 0.48–0.68). There was significant co-occurrence of RB loss and HRR gene aberrations; RB loss was further associated with favorable survival within HRR-aberrant cases (multivariable HR, 0.50).

Conclusions:

These data paint a high-resolution picture of the molecular landscape in HGSOC, better defining patients who may benefit most from specific molecular therapeutics and highlighting those for whom novel treatment strategies are needed to improve outcomes.
FDA Approval Summary: Belzutifan for von Hippel-Lindau Disease–Associated Tumors
Authors: Fallah Jaleh , Brave Michael H. , Weinstock Chana , Mehta Gautam U. , Bradford Diana , Gittleman Haley , Bloomquist Erik W. , Charlab Rosane , Hamed Salaheldin S. , Miller Claudia P. , Dorff Sarah E. , Chambers Wiley A. , Mixter Bronwyn D. , Dinin Jeannette , Pierce William F. , Ricks Tiffany K. , Tang Shenghui , Donoghue Martha , Pazdur Richard , Amiri-Kordestani Laleh , Ibrahim Amna , Beaver Julia A.
Published: July 2022

On August 13, 2021, the FDA approved belzutifan (WELIREG, Merck), a first-in-class hypoxia-inducible factor (HIF) inhibitor for adult patients with von Hippel-Lindau (VHL) disease who require therapy for associated renal cell carcinoma (RCC), central nervous system (CNS) hemangioblastomas, or pancreatic neuroendocrine tumors (pNET), not requiring immediate surgery. The FDA granted approval based on the clinically meaningful effects on overall response rate (ORR) observed in patients enrolled in Study MK-6482-004. All 61 patients had VHL-associated RCC; some also had CNS hemangioblastomas and/or pNET. For VHL disease–associated RCC, ORR was 49% [95% confidence interval (CI), 36–62], median duration of response (DoR) was not reached, 56% of responders had DoR ≥12 months, and median time to response was 8 months. Twenty-four patients had measurable CNS hemangioblastomas with an ORR of 63% (95% CI, 41–81), and 12 patients had measurable pNET with an ORR of 83% (95% CI, 52–98). For these tumors, median DoR was not reached, with 73% and 50% of patients having response durations ≥12 months for CNS hemangioblastomas and pNET, respectively. The most common adverse reactions, including laboratory abnormalities, reported in ≥20% were anemia, fatigue, increased creatinine, headache, dizziness, increased glucose, and nausea. Belzutifan can render some hormonal contraceptives ineffective and can cause embryo-fetal harm during pregnancy. This article summarizes the data and the FDA thought process supporting traditional approval of belzutifan for this indication.
Combination Therapies for Advanced Hepatocellular Carcinoma: Biomarkers and Unmet Needs
Authors: Cappuyns Sarah , Llovet Josep M.
Published: July 2022

The novel combination of checkpoint inhibitors targeting the PD(L)1 pathway and anti-VEGFA therapy has revolutionized the treatment landscape of advanced hepatocellular carcinoma (HCC). However, biomarkers predictive of response to these therapies are still lacking, representing a major clinical challenge.

See related articles by Zhang et al., p. 3499, and Zhu et al., p. 3537
Predictive Value of Liver Stiffness Measurement by Magnetic Resonance Elastography for Complications after Liver Resection: A Systematic Review and Meta-Analysis
Authors: Liang Jiaxu , Qiu Bo , Yin Suo , Chen Yong , Zhang Sijia
Published: July 2022

Background and Aims: Liver fibrosis has been recognized as a significant risk factor for short-term outcomes after hepatectomy. Magnetic resonance elastography (MRE) showed higher diagnostic performance in staging liver fibrosis than other elastography modalities. This study aimed to assess the accuracy of predicting postoperative complications in patients with malignant liver tumors using liver stiffness measurement (LSM) by MRE. Methods: After a systematic review of the relevant studies, the sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the curve (AUC) for the diagnosis of postoperative complications were pooled using bivariate meta-analysis. Meanwhile, the pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the effect. Heterogeneity was explored by sensitivity analysis, univariate meta-regression, and subgroup analysis. The potential publication bias was evaluated by the Deek’s funnel plot test. Results: Eight studies comprising a total of 1,154 patients that predicted postoperative outcomes as their purpose were ultimately included in the quantitative analysis. The pooled results of the meta-analysis revealed that the pooled sensitivity, specificity, and AUC were 78% (95% CI: 69–85%, Higgins’s inconsistency index [I2] = 43.00), 75% (95% CI: 70–80%, Higgins’s inconsistency index [I2] = 72.53), and 0.83 (95% CI: 0.80–0.86), respectively. Preoperative LSM by MRE was significantly associated with the development of overall postoperative outcomes (OR 1.78, 95% CI: 1.49–2.08). Univariate meta-regression showed that advanced fibrosis stage (≥F3), HCC patient proportion and cut-off value significantly influenced the heterogeneity of the included studies. The AUC of several novel prediction models based on LSM by MRE ranged from 0.818 to 0.911. Conclusions: In conclusion, liver stiffness measured by MRE was a significant predictor of postoperative outcomes in patients undergoing liver resection. Future studies could focus on setting a prognostic model integrated with LSM by MRE in distinguishing patients at high risk of posthepatectomy complications.