bluuebunny/crossref_metadata_2025 huggingface dataset:
Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course Recommendation
Authors: Sun Jianshan , Mei Suyuan , Yuan Kun , Jiang Yuanchun , Cao Jie
Published: January 2024

The rapid development of Massive Open Online Courses (MOOCs) platforms has created an urgent need for an efficient personalized course recommender system that can assist learners of all backgrounds and levels of knowledge in selecting appropriate courses. Currently, most existing methods utilize a sequential recommendation paradigm that captures the user’s learning interests from their learning history, typically through recurrent or graph neural networks. However, fewer studies have explored how to incorporate principles of human learning at both the course and category levels to enhance course recommendations. In this article, we aim at addressing this gap by introducing a novel model, named Prerequisite-Enhanced Catory-Aware Graph Neural Network (PCGNN), for course recommendation. Specifically, we first construct a course prerequisite graph that reflects the human learning principles and further pre-train the course prerequisite relationships as the base embeddings for courses and categories. Then, to capture the user’s complex learning patterns, we build an item graph and a category graph from the user’s historical learning records, respectively: (1) the item graph reflects the course-level local learning transition patterns and (2) the category graph provides insight into the user’s long-term learning interest. Correspondingly, we propose a user interest encoder that employs a gated graph neural network to learn the course-level user interest embedding and design a category transition pattern encoder that utilizes GRU to yield the category-level user interest embedding. Finally, the two fine-grained user interest embeddings are fused to achieve precise course prediction. Extensive experiments on two real-world datasets demonstrate the effectiveness of PCGNN compared with other state-of-the-art methods.
MCN4Rec: Multi-level Collaborative Neural Network for Next Location Recommendation
Authors: Li Shuzhe , Chen Wei , Wang Bin , Huang Chao , Yu Yanwei , Dong Junyu
Published: January 2024

Next location recommendation plays an important role in various location-based services, yielding great value for both users and service providers. Existing methods usually model temporal dependencies with explicit time intervals or learn representation from customized point of interest (POI) graphs with rich context information to capture the sequential patterns among POIs. However, this problem is perceptibly complex, because various factors, e.g., users’ preferences, spatial locations, time contexts, activity category semantics, and temporal relations, need to be considered together, while most studies lack sufficient consideration of the collaborative signals. Toward this goal, we propose a novel
M
ulti-Level
C
ollaborative Neural
N
etwork for next location
Rec
ommendation (MCN4Rec). Specifically, we design a multi-level view representation learning with level-wise contrastive learning to collaboratively learn representation from local and global perspectives to capture complex heterogeneous relationships among user, POI, time, and activity categories. Then, a causal encoder-decoder is applied to the learned representations of check-in sequences to recommend the next location. Extensive experiments on four real-world check-in mobility datasets demonstrate that our model significantly outperforms the existing state-of-the-art baselines for the next location recommendation. Ablation study further validates the benefits of the collaboration of the designed sub-modules. The source code is available at
https://github.com/quai-mengxiang/MCN4Rec
.
KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation
Authors: Tao Wei , Zhou Yucheng , Wang Yanlin , Zhang Hongyu , Wang Haofen , Zhang Wenqiang
Published: January 2024

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods.
Analyzing and Detecting Information Types of Developer Live Chat Threads
Authors: Shang Xiuwei , Zhang Shuai , Zhang Yitong , Guo Shikai , Li Yulong , Chen Rong , Li Hui , Li Xiaochen , Jiang He
Published: January 2024

Online chatrooms serve as vital platforms for information exchange among software developers. With multiple developers engaged in rapid communication and diverse conversation topics, the resulting chat messages often manifest complexity and lack structure. To enhance the efficiency of extracting information from chat
threads
, automatic mining techniques are introduced for thread classification. However, previous approaches still grapple with unsatisfactory classification accuracy due to two primary challenges that they struggle to adequately capture long-distance dependencies within chat threads and address the issue of category imbalance in labeled datasets. To surmount these challenges, we present a topic classification approach for chat information types named EAEChat. Specifically, EAEChat comprises three core components: the text feature encoding component captures contextual text features using a multi-head self-attention mechanism-based text feature encoder, and a siamese network is employed to mitigate overfitting caused by limited data; the data augmentation component expands a small number of categories in the training dataset using a technique tailored to developer chat messages, effectively tackling the challenge of imbalanced category distribution; the non-text feature encoding component employs a feature fusion model to integrate deep text features with manually extracted non-text features. Evaluation across three real-world projects demonstrates that EAEChat, respectively, achieves an average precision, recall, and F1-score of 0.653, 0.651, and 0.644, and it marks a significant 7.60% improvement over the state-of-the-art approaches. These findings confirm the effectiveness of our method in proficiently classifying developer chat messages in online chatrooms.
Spectrum of Diabetic Neuropathy: New Insights in Diagnosis and Treatment
Authors: Dillon Brendan R. , Ang Lynn , Pop-Busui Rodica
Published: January 2024

Diabetic neuropathy is a highly prevalent complication of diabetes. It consists of a broad range of neuropathic conditions, such as distal symmetric polyneuropathy and various forms of autonomic neuropathies involving the cardiovascular, gastrointestinal, and urogenital systems. Prevention or diagnosis in early stages of disease is crucial to prevent symptomatic onset and progression, particularly in the absence of current disease-modifying therapies. In this review, we describe the four main types of diabetic neuropathy. We review current understanding with respect to diagnosis and treatment while highlighting knowledge gaps and future directions.
Lessons Learned from Approval of Aducanumab for Alzheimer's Disease
Authors: Heidebrink Judith L. , Paulson Henry L.
Published: January 2024

When the US Food and Drug Administration used the accelerated approval process to authorize the use of the antiamyloid drug aducanumab to treat Alzheimer's disease (AD), many people hoped this signaled a new era of disease-modifying treatment. But 2 years later, aducanumab's failure to launch provides a cautionary tale about the complexities of dementia and the need for a thorough and transparent review of the role that regulatory agencies and various stakeholders play in approving AD drugs. We highlight the events leading to aducanumab's controversial approval and discuss some of the key lessons learned from the drug's failure to deliver the hoped-for benefits. These lessons include the inherent limitations of antiamyloid strategies for a complex disease in which amyloid is only one of several pathological processes, the need for clinical trials that better reflect the diversity of communities affected by AD, the potential pitfalls of futility analyses in clinical trials, the need for greater transparency and other modifications to the approval process, and the dementia field's unreadiness to move from the highly controlled environment of clinical trials to the widespread and chronic use of resource-intensive, disease-modifying drugs in real-world treatment scenarios. People with dementia desperately need effective therapies. We hope that the aducanumab story will inspire changes to the approval process—changes that restore public trust and improve future efforts to deliver disease-modifying therapies to the clinic.
Prostate-Specific Membrane Antigen: Gateway to Management of Advanced Prostate Cancer
Authors: Unterrainer Lena M. , Calais Jeremie , Bander Neil H.
Published: January 2024

Prostate-specific membrane antigen (PSMA) as a transmembrane protein is overexpressed by prostate cancer (PC) cells and is accessible for binding antibodies or low-molecular-weight radioligands due to its extracellular portion. Successful targeting of PSMA began with the development of humanized J591 antibody. Due to their faster clearance compared to antibodies, small-molecule radioligands for targeted imaging and therapy of PC have been favored in recent development efforts. PSMA positron emission tomography (PET) imaging has higher diagnostic performance than conventional imaging for initial staging of high-risk PC and biochemical recurrence detection/localization. However, it remains to be demonstrated how to integrate PSMA PET imaging for therapy response assessment and as an outcome endpoint measure in clinical trials. With the recent approval of 177Lu-PSMA-617 by the US Food and Drug Administration for metastatic castration-resistant PC progressing after chemotherapy, the high value of PSMA-targeted therapy was confirmed. Compared to standard of care, PSMA-based radioligand therapy led to a better outcome and a higher quality of life. This review, focusing on the advanced PC setting, provides an overview of different approved and nonapproved PSMA-targeted imaging and therapeutic modalities and discusses the future of PSMA-targeted theranostics, also with an outlook on non-radiopharmaceutical-based PSMA-targeted therapies.
Electrodeposition of Nickel-Tungsten Alloy with Functional Concentration Periodically Graded Material Structure for Low Stress and High Hardness
Authors: Park Soobin , Han Haneul , Seo Jinmyeong , Park Jungjoon , Yoon Sanghwa , Yoo Bongyoung
Published: January 2024

A nickel-tungsten alloy film was deposited using an electrodeposition process. The tungsten concentration in the nickel-tungsten alloy was controlled by the applied current density. The surface morphology, micro-structure, internal stress, and hardness were characterized as a single-layer structure. Hardness increased as the tungsten content increased, but micro-cracks occurred on the surface. A multi-layered structure was selected to increase the hardness without micro-cracks. The multi-layered nickel-tungsten alloy film was deposited to form two types: functional periodic materials and functional graded materials. These multi-layered structures were deposited by changing the applied current density periodically and gradually, respectively, during the deposition process. The mechanical properties, such as internal stress and hardness of the nickel-tungsten alloy, were characterized as a function of the tungsten concentration of the nickel-tungsten alloy film. As the number of periods increased, the internal stress decreased, and micro-cracks were removed from the surface. However, the gradually varied nickel-tungsten alloy had higher internal stress than the periodically varied alloy. Similar hardness was observed because the concentration of nickel-tungsten film at the top of the multi-layered structure was the same. Overall, we demonstrated enhanced mechanical properties, including low internal stress and high hardness, of concentration periodically graded nickel-tungsten alloy.
The Impact of Formate-Based Electrolytes on The Electrochemical Performance of Asymmetric Supercapacitors Containing Activated Carbon and MnO2 as Electrode Materials
Authors: Liu Siqi , Douard Camille , Brousse Thierry , Balducci Andrea
Published: January 2024

In this work we report on the properties of three novel aqueous electrolytes containing 1 m (mol kg−1) of lithium formate, sodium formate and potassium formate in H2O. We show that these cheap and environmentally friendly electrolytes display high conductivity and low viscosity from 0 °C to 80 °C. When used in asymmetric supercapacitors (SCs) containing Manganese dioxide (MnO2) as active material in the positive electrode and activated carbon (AC) as active material in the negative electrode, these electrolytes allow the design of devices with operating voltage up to 1.7 V. Asymmetric SC containing these novel electrolytes display good capacity (19 mAh g−1, 18 mAh g−1 and 13 mAh g−1 in 1 m HCOOK in H2O, 1 m HCOOLi in H2O and 1 m HCOONa in H2O, respectively). The capacity retention after 10,000 cycles of the devices containing 1 m HCOOLi in H2O, 1 m HCOONa in H2O and 1 m HCOOK in H2O are all higher than 85%.
Secreted ADAMTS-like proteins as regulators of connective tissue function
Authors: Taye Nandaraj , Redhead Charlene , Hubmacher Dirk
Published: January 2024

The extracellular matrix (ECM) determines functional properties of connective tissues through structural components, such as collagens, elastic fibers, or proteoglycans. The ECM also instructs cell behavior through regulatory proteins, including proteases, growth factors, and matricellular proteins, which can be soluble or tethered to ECM scaffolds. The secreted a disintegrin and metalloproteinase with thrombospondin type 1 repeats/motifs-like (ADAMTSL) proteins constitute a family of regulatory ECM proteins that are related to ADAMTS proteases but lack their protease domains. In mammals, the ADAMTSL protein family comprises seven members, ADAMTSL1-6 and papilin. ADAMTSL orthologs are also present in the worm, Caenorhabditis elegans, and the fruit fly, Drosophila melanogaster. Like other matricellular proteins, ADAMTSL expression is characterized by tight spatiotemporal regulation during embryonic development and early postnatal growth and by cell type- and tissue-specific functional pleiotropy. Although largely quiescent during adult tissue homeostasis, reexpression of ADAMTSL proteins is frequently observed in the context of physiological and pathological tissue remodeling and during regeneration and repair after injury. The diverse functions of ADAMTSL proteins are further evident from disorders caused by mutations in individual ADAMTSL proteins, which can affect multiple organ systems. In addition, genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) in ADAMTSL genes to complex traits, such as lung function, asthma, height, body mass, fibrosis, or schizophrenia. In this review, we summarize the current knowledge about individual members of the ADAMTSL protein family and highlight recent mechanistic studies that began to elucidate their diverse functions.
Modulatory effects of estrous cycle on ingestive behaviors and energy balance in young adult C57BL/6J mice maintained on a phytoestrogen-free diet
Authors: Reho John J. , Muskus Patricia C. , Bennett Darby M. , Grobe Connie C. , Burnett Colin M.L , Nakagawa Pablo , Segar Jeffrey L. , Sigmund Curt D. , Grobe Justin L.
Published: January 2024

When provided a phytoestrogen-free diet, the estrous cycle had very little effect on food and water intake, physical activity, or energy expenditure in C57BL/6J mice. In contrast, when provided an NaCl drink in addition to food and water, the estrous cycle was associated with changes in intake behaviors and energy expenditure. These findings highlight the complex interactions among estrous cycling, dietary formulation, and nutrient presentation upon ingestive behaviors and energy homeostasis in mice.
The Inhibitory Properties of the Ambroxol Derivative on the Corrosion of Mild Steel in Hydrochloric Acid Medium
Authors: Nikolaychuk Pavel Anatolyevich , Biryukov Aleksandr Igorevich , Sharov Artem Vladimirovich , Burmistrov Leon Olegovich , Amelina Natalya Sergeevna , Tereshkina Anastasia Andreevna
Published: January 2024

A compound 2-(6,8-dibromo-3-(4-hydroxycyclohexyl)-1,2,3,4-tetrahydroquinazolin-2-yl)phenol was synthetised from ambroxol hydrochloride and salicylaldehyde. The structure of the compound was studied with UV, IR, Raman, and 1H NMR spectroscopy. The inhibitory ability of the synthetised compound on the corrosion of mild stainless steel EN Fe37-3FN in 0.5 M hydrochloric acid solution was studied using gravimetric and electrochemical methods, including potentiodynamic polarisation and EIS. It was shown that the inhibitory activity of the compound increases with the increase of its concentration in a solution. An addition of 3 mg/l of the compound reduces the corrosion rate by 20% and that of 400 mg/l by 85%. The data of gravimetric and electrochemical measurements coincide well. The sorption of the compound on the metal surface obeys the Langmuir adsorption isotherm, and the nature of adsorption is physical. The compound exhibits the chelating activity with both ferrous and ferric ions in the acidic solution. The synthetised compound may be a good choice for the inhibition of steel corrosion in acidic environments.
Chaotic Wind-Driven Optimization with Hyperbolic Tangent Model and T-Distributed Mutation Strategy
Authors: Fang Da , Yan Jun , Zhou Quan
Published: January 2024

Meta-heuristic algorithms have the advantages of resilience, global optimization capacity, and coding flexibility, making them helpful in tackling difficult optimization issues. The enhanced wind-driven optimization (CHTWDO) that was proposed in this paper coupled the chaotic map approach and the hyperbolic tangent with the T-distribution mutation method. The initial air particles are evenly distributed in the system space through a tent mapping strategy. Meanwhile, the variation probability of the hyperbolic tangent model and the T-distribution variation method are used to improve the comprehensive performance of the algorithm. In this way, the global search accuracy and the ability of avoiding the extreme value of the algorithm can be taken into account. Combining the three strategies, CHTWDO had higher global search accuracy and a stronger ability to jump out of local extremum. Comparing with the eight meta-heuristic algorithms (including WDO) and the single strategy improved WDO on 24 test functions, the experimental results show that CHTWDO with two improved strategies has better convergence precision and faster convergence speed. Statistical tests such as Friedman’s and Wilcoxon’s rank-sum tests are used to determine significant differences between these comparison algorithms. Finally, CHTWDO also obtains the best results on four classical optimization problems in engineering applications, which verifies its practicality and effectiveness.
Differential Game Model for a Dual-Channel Supply Chain’s Optimal Strategy under the Reference Carbon Emission Effect
Authors: Yu Di
Published: January 2024

Taking into account the impact of time factors on emission reductions and brand reputation, the reference carbon emission effect and dual-channel supply chain are incorporated into a unified analysis framework. We applied differential game theory to build models under centralized decision-making and decentralized decision-making. The aim of the research is to explore the strategies of a single manufacturer and a single retailer on product pricing, low-carbon production, and advertising. The research analyses the impact of reference carbon emission effects, cost coefficients, and interchannel substitutable coefficients on profits. In order to alleviate the double marginal effect brought about by decentralized decision-making, a cost-compensation coordination mechanism is proposed. The conclusions are as follows. First, centralized decision-making is the optimal decision-making mode, but further consultation is required to implement it voluntarily by both parties. Second, a cost-recovery contract occurs when the fixed fee that the retailer gives the manufacturer meets certain conditions. The contract can make the retailer’s advertising investment reach the level of centralized decision-making and improve the member’s profit under the decentralized decision-making. The coordination mechanism is effective. Third, the reference carbon emission effect can bring about an increase in the manufacturer’s low-carbon production input and profits. The retailer’s advertising investment is not affected by the reference carbon emission effect. Fourth, wholesale prices and online or offline retail prices are all positively correlated with the market share of the channel. The price-substitution coefficient between channels is positively correlated with both low-carbon inputs and profits.
Developing a Hybrid Irrigation System for Smart Agriculture Using IoT Sensors and Machine Learning in Sri Ganganagar, Rajasthan
Authors: Kaur Amritpal , Bhatt Devershi Pallavi , Raja Linesh
Published: January 2024

The agriculture sector is one of the largest consumers of fresh water. Different types of irrigation systems are available, including center pivot, drip and sprinkler systems, and linear motion systems. However, the complex structure of existing irrigation systems and their high maintenance costs encourage Indian farmers to continue using these methods. Due to its ease of use and low energy consumption, surface irrigation is one of the most popular irrigation techniques. Although the main reasons for poor irrigation application efficiency are uneven irrigation water distribution and deep absorption, using a variety of technologies, countries are trying to increase the sustainability of agriculture. Automated irrigation systems contribute significantly to water conservation. The combination of automation and Internet of Things (IoT) improves agricultural practices. These technologies help farmers understand their crops, minimize their impact on the environment, and preserve resources. They also enable efficient monitoring of the weather, water resources, and soil. This research proposes an intelligent, low-cost field irrigation system. The proposed prototype can measure soil moisture, rain status, wind speed, water level, temperature, and humidity using a hardware sensor and unit. To decide whether to turn on or off the motor, a variety of sensors are used to get a range of readings and conclusions. They enable automatic watering when soil moisture levels are below a certain threshold, and if soil moisture is equal to the required moisture, then the irrigation process stops. Every few minutes, the sensors measure the environmental factors. Data are collected and stored on a ThingSpeak cloud server for analysis. To evaluate the data we collected, we used a variety of models, such as K-nearest neighbors (KNN), Naïve Bayes, random forest, and logistic regression. Compared to other Naïve Bayes and random forest models, the accuracy rate was 98.8%, the mean square error was 0.16, and the results of logistic regression, KNN, and SVM were in order: (98.3%/1.66), (99.3%/0.66), and (99.5%/0.5), respectively. In the end, an automated irrigation system run on IoT applications gives farmers access to remote monitoring and control, as well as information about the specifics of the irrigation field.
Oscillation of Fourth‐Order Nonlinear Semi‐Canonical Neutral Difference Equations via Canonical Transformations
Authors: Ganesan P. , Palani G. , Graef John R. , Thandapani E.
Published: January 2024

The authors present a new technique for transforming fourth‐order semi‐canonical nonlinear neutral difference equations into canonical form. This greatly simplifies the examination of the oscillation of solutions. Some new oscillation criteria are established by comparison with first‐order delay difference equations. Examples are provided to illustrate the significance and novelty of the main results. The results are new even for the case of nonneutral difference equations.
Sensorineural Hearing Loss in Seropositive Neuromyelitis Optica Spectrum Disorder and Myelin Oligodendrocyte Glycoprotein Antibody‐Associated Disorder
Authors: Kwon Soonwook , Choi Soyoun , Chung Yeon Hak , Min Ju-Hong
Published: January 2024

Background. Acute sensorineural hearing loss (SNHL) is a rare development in the central nervous system (CNS) demyelinating diseases such as aquaporin‐4‐IgG‐positive neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD). Methods. We retrospectively reviewed consecutive patients with seropositive NMOSD or MOGAD in the CNS Inflammatory and Demyelinating Disease Registry at Samsung Medical Center from January 2015 to December 2020. After the medical chart review, the demographic data and the results of brain magnetic resonance imaging (MRI) and audiometry of patients with hearing loss were collected. Results. Five patients (NMOSD, n = 3; MOGAD, n = 2) were diagnosed with SNHL, two developed SNHL before the first core clinical symptom, and another two patients who underwent brain MRI at the timing of hearing loss showed lesions. Only three patients received high‐dose steroids; however, hearing loss did not improve in any patients. Conclusion. SNHL was observed in a small number of patients with seropositive NMOSD and MOGAD; however, it could be underrecognized. Further large cohort prospective studies are helpful to elucidate the clinical implication of SNHL in NMOSD and MOGAD.
Biofilm-Inhibitory Activity of Wild Mushroom Extracts against Pathogenic Bacteria
Authors: Gebreyohannes Gebreselema , Sbhatu Desta Berhe , Nyerere Andrew Kimang’a , Gebrehiwot Abrha Gebreselema
Published: January 2024

Objective. This study aims to investigate the bacterial biofilm-inhibitory effect of mushroom extracts. Methods. Mushrooms were collected from Arabuko-Sokoke and Kakamega forests and identified using morphological and molecular approaches. Auricularia auricula-judae, Microporus xanthopus, Termitomyces umkowaani, Trametes elegans, and Trametes versicolor were extracted by chloroform, 70% ethanol, and hot water. Extracts were tested against Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus (ATCC25923). Data were analyzed using SPSS ver. 20.0. Results. Chloroform, 70% ethanol, and hot water extracts of A. auricula-judae (50 μg/mL) showed statistically significant antibiofilm activities against P. aeruginosa, E. coli, and S. aureus (p≤0.05). M. xanthopus extracts (250 μg/mL) revealed significantly significant antibiofilm activities against each test bacterium (p≤0.05). All extracts of T. umkowaani (250 μg/mL) exhibited statistically significant antibiofilm activities against S. aureus only (p≤0.05). Chloroform extract of T. elegans (250 μg/mL) showed the best antibiofilm activity (69.75 ± 0.01%) against S. aureus. All T. versicolor extracts (250 μg/mL) indicated the best antibiofilm activities against S. aureus. Conclusions. Being the first study of its kind to be conducted in Kenya, it added a novel concept to the body of knowledge already known about medical biotechnology research. It offers a fresh understanding of the various varieties of mushrooms found in Kenya, their potential biological function in the production of drugs, particularly those that combat drug resistance, and perhaps even a peek at their bioactive elements. Wild mushrooms, a hidden gem, might help to reopen the pipeline of new antibiotics that have been on the decline. However, further research is required to determine the potential mechanism(s) of action of the extracts that are in charge of the apparent antibiofilm activity.
Serial Multiple Mediation of Mastery and Sleep Quality in the Relationship between Caregiving Burden and Anxiety among Parental Caregivers of Children with Leukemia in China
Authors: Jiang Weikang , Chen Jinzhu , Sun Wenjun , Wang Yang
Published: January 2024

Objective. The emerging literature on caregiving posits that anxiety is fairly prevalent and could vary with factors such as caregiving burden, mastery, and sleep quality. Little work has explained the possible dynamics between those variables. This study therefore aims to investigate the multiple serial mediations of mastery and sleep quality in the relationship between caregiving burden and anxiety among Chinese parental caregivers of children with leukemia. Method. Data were taken from a convenient sample (n = 342) from a nonprofit organization that provides psycho‐social support to oncological patients and their families nationwide in China. The following standardized self‐reported questionnaires were administered to parents of children with leukemia: Zarit Care Burden Scale, Personal Mastery Scale, Insomnia Severity Index, and Generalized Anxiety Disorder. A serial multiple mediation model (PROCESS model 6) was employed to test the mediation hypothesis. Result. It was demonstrated that caregiving burden was positively and significantly correlated with caregivers’ anxiety. Bootstrap analyses indicate that there were direct and indirect effects of caregiving burden on anxiety, and it was mediated by mastery. In addition, sleep quality mediated the effects of caregiving burden and mastery on anxiety, respectively. Conclusion. Taken together, for parental caregivers of children with leukemia in China, caregiving burden is a primary stressor and can trigger anxiety. Low mastery and poor sleep quality are the secondary stressors that could lead to negative psychological outcomes for the caregiver.
Multidimensional Intergenerational Relationship and Social Participation among Late‐Life Migrants in China: The Role of Depressive Symptom
Authors: Ruan Yong-Xin , Wang Juan
Published: January 2024

Chinese adults will migrate to reunite with their children in later life, with social participation being an essential element of their successful adaptation. As children are older adults’ primary source of support, this study aimed to investigate both the direct and indirect effects of multiple dimensions of intergenerational relationship quality on social participation through the incidence of depressive symptom. A cross‐sectional survey was conducted in Shenzhen, China, with late‐life migrants aged 50 years and above. Totally, 397 participants were included in this analysis. The intergenerational relationship was measured using the Intergenerational Relationship Quality Scale for Aging Chinese Parents, which covers four dimensions: structural‐associational solidarity, affectual closeness, consensual‐normative solidarity, and intergenerational conflicts. However, as the structural‐associational solidarity and affectual closeness dimensions did not have acceptable reliability, the four‐dimension model was instead validated by using exploratory factor analysis and confirmatory factor analysis. The same four‐factor model was confirmed, with the noted exception that item 10 (helping with housework) was deleted on the basis that it presented weak factor loading. Bootstrapping was used to examine the direct and indirect effects of the four dimensions on social participation through depressive symptom. The results showed that only affective closeness and intergenerational conflict were associated with social participation. Depressive symptom was a partial mediator of the correlation between affective closeness and social participation, whereas depressive symptom did not have any mediating effect on the other dimensions of intergenerational relationship quality and social participation. These findings highlight the importance of affectual closeness and intergenerational conflict in the social participation of late‐life migrants in China.
Brain Tumor Detection and Classification Using IFF‐FLICM Segmentation and Optimized ELM Model
Authors: Dash Suvashisa , Siddique Mohammed , Mishra Satyasis , Gelmecha Demissie J. , Satapathy Sunita , Rathee Davinder Singh , Singh Ram Sewak
Published: January 2024

Brain cancer deaths are significantly increased in all categories of aged persons due to the abnormal growth of brain tumor tissues in the brain. The death rate can be controlled by accurate early stage brain tumor diagnosis. The detection and classification of brain tumors play a crucial role in early diagnosis and treatment planning. Brain tumor detection and classification have become challenging and time‐consuming for domain‐specific radiologists and pathologists in medical image analysis. So, automatic detection and classification are essential to reduce the time of diagnosis. In recent years, machine learning classifiers have played an essential role in automatically classifying brain tumors. In this research, an approach based on an improved fuzzy factor fuzzy local information C means (IFF‐FLICM) segmentation and hybrid modified harmony search and sine cosine algorithm (MHS‐SCA) optimized extreme learning machine (ELM) is proposed for brain tumor detection and classification. The IFF‐FLICM algorithm is utilized to accurately segment the brain’s magnetic resonance (MR) images to identify the tumor regions. The Mexican hat wavelet transform is employed for feature extraction from the segmented images. The extracted features from the segmented regions are fed into the MHS‐SCA‐ELM classifier for classification. The MHS‐SCA is proposed to optimize the weights of the ELM model to improve the classification performance. Five distinct multimodal and unimodal benchmark functions are considered for optimization to demonstrate the robustness of the proposed MHS‐SCA optimization technique. The image Dataset‐255 is considered for this study. The quality measures such as SSIM and PSNR are considered for segmentation. The proposed IFF‐FLICM segmentation achieved a peak signal‐to‐noise ratio (PSNR) of 37.24 dB and a structural similarity index (SSIM) of 0.9823. The proposed MHS‐SCA‐based ELM model achieved a sensitivity, specificity, and accuracy of 98.78%, 99.23%, and 99.12%. The classification performance results of the proposed MHS‐SCA‐ELM model are compared with MHS‐ELM, SCA‐ELM, and PSO‐ELM models, and the comparison results are presented.
Lactate Utilization Enables Metabolic Escape to Confer Resistance to BET Inhibition in Acute Myeloid Leukemia
Authors: Monteith Andrew J. , Ramsey Haley E. , Silver Alexander J. , Brown Donovan , Greenwood Dalton , Smith Brianna N. , Wise Ashley D. , Liu Juan , Olmstead Sarah D. , Watke Jackson , Arrate Maria P. , Gorska Agnieszka E. , Fuller Londa , Locasale Jason W. , Stubbs Matthew C. , Rathmell Jeffrey C. , Savona Michael R.
Published: January 2024

Impairing the BET family coactivator BRD4 with small-molecule inhibitors (BETi) showed encouraging preclinical activity in treating acute myeloid leukemia (AML). However, dose-limiting toxicities and limited clinical activity dampened the enthusiasm for BETi as a single agent. BETi resistance in AML myeloblasts was found to correlate with maintaining mitochondrial respiration, suggesting that identifying the metabolic pathway sustaining mitochondrial integrity could help develop approaches to improve BETi efficacy. Herein, we demonstrated that mitochondria-associated lactate dehydrogenase allows AML myeloblasts to utilize lactate as a metabolic bypass to fuel mitochondrial respiration and maintain cellular viability. Pharmacologically and genetically impairing lactate utilization rendered resistant myeloblasts susceptible to BET inhibition. Low-dose combinations of BETi and oxamate, a lactate dehydrogenase inhibitor, reduced in vivo expansion of BETi-resistant AML in cell line and patient-derived murine models. These results elucidate how AML myeloblasts metabolically adapt to BETi by consuming lactate and demonstrate that combining BETi with inhibitors of lactate utilization may be useful in AML treatment.

Significance:

Lactate utilization allows AML myeloblasts to maintain metabolic integrity and circumvent antileukemic therapy, which supports testing of lactate utilization inhibitors in clinical settings to overcome BET inhibitor resistance in AML.

See related commentary by Boët and Sarry, p. 950
KDM5C-Mediated Recruitment of BRD4 to Chromatin Regulates Enhancer Activation and BET Inhibitor Sensitivity
Authors: Qiang Yulong , Fan Jiachen , Xie Chuanshuai , Yan Leilei , Song Xiaofei , Zhang Nan , Lin Yan , Xiong Jie , Zhang Wei , Liu Yu , Wei Lei , Li Yu , Chen Shizhen , Liang Kaiwei , Li Feng
Published: January 2024

The BET family member BRD4 is a bromodomain-containing protein that plays a vital role in driving oncogene expression. Given their pivotal role in regulating oncogenic networks in various cancer types, BET inhibitors (BETi) have been developed, but the clinical application has been impeded by dose-limiting toxicity and resistance. Understanding the mechanisms of BRD4 activity and identifying predictive biomarkers could facilitate the successful clinical use of BETis. Herein, we show that KDM5C and BRD4 cooperate to sustain tumor cell growth. Mechanistically, KDM5C interacted with BRD4 and stimulated BRD4 enhancer recruitment. Moreover, binding of the BRD4 C-terminus to KDM5C stimulated the H3K4 demethylase activity of KDM5C. The abundance of both KDM5C-associated BRD4 and H3K4me1/3 determined the transcriptional activation of many oncogenes. Notably, depletion or pharmacologic degradation of KDM5C dramatically reduced BRD4 chromatin enrichment and significantly increased BETi efficacy across multiple cancer types in both tumor cell lines and patient-derived organoid models. Furthermore, targeting KDM5C in combination with BETi suppressed tumor growth in vivo in a xenograft mouse model. Collectively, this work reveals a KDM5C-mediated mechanism by which BRD4 regulates transcription, providing a rationale for incorporating BETi into combination therapies with KDM5C inhibitors to enhance treatment efficacy.

Significance:

BRD4 is recruited to enhancers in a bromodomain-independent manner by binding KDM5C and stimulates KDM5C H3K4 demethylase activity, leading to synergistic effects of BET and KDM5C inhibitor combinations in cancer.
Data from Prevalence of Aflatoxin-Associated TP53R249S Mutation in Hepatocellular Carcinoma in Hispanics in South Texas
Authors: Jiao Jingjing , Niu Weibo , Wang Ying , Baggerly Keith , Ye Yuanqing , Wu Xifeng , Davenport Dewitt , Almeda Jose Luis , Betancourt-Garcia Monica M. , Forse R. Armour , Stevenson Heather L. , Watt Gordon P. , McCormick Joseph B. , Fisher-Hoch Susan P. , Beretta Laura
Published: January 2024

Abstract
We aimed to determine whether aflatoxin dietary exposure plays a role in the high incidence of hepatocellular carcinoma (HCC) observed among Hispanics in South Texas. We measured TP53R249S somatic mutation, hallmark of aflatoxin etiology in HCC, using droplet digital PCR and RFLP. TP53R249S mutation was detected in 3 of 41 HCC tumors from Hispanics in South Texas (7.3%). We also measured TP53R249S mutation in plasma cell-free DNA (cfDNA) from 218 HCC patients and 96 Hispanic subjects with advanced fibrosis or cirrhosis, from South Texas. The mutation was detected only in Hispanic and Asian HCC patients, and patients harboring TP53R249S mutation were significantly younger and had a shorter overall survival. The mutation was not detected in any Hispanic subject with advanced fibrosis or cirrhosis. Genes involved in cell-cycle control of chromosomal replication and in BRCA1-dependent DNA damage response were enriched in HCCs with TP53R249S mutation. The E2F1 family members, E2F1 and E2F4, were identified as upstream regulators. TP53R249S mutation was detected in 5.7% to 7.3% of Hispanics with HCC in South Texas. This mutation was associated with a younger age and worse prognosis. TP53R249S was however not detected in Hispanics in South Texas with cirrhosis or advanced fibrosis. Aflatoxin exposure may contribute to a small number of HCCs in Hispanics in South Texas, but the detection of TP53R249S mutation in plasma cfDNA is not a promising biomarker of risk assessment for HCC in subjects with cirrhosis or advanced fibrosis in this population. Cancer Prev Res; 11(2); 103–12. ©2017 AACR.
Pim Kinase Inhibitors Increase Gilteritinib Cytotoxicity in FLT3-ITD Acute Myeloid Leukemia Through GSK-3β Activation and c-Myc and Mcl-1 Proteasomal Degradation
Authors: Lee Jonelle K. , Chatterjee Aditi , Scarpa Mario , Bailey Christopher M. , Niyongere Sandrine , Singh Prerna , Mustafa Ali Moaath K. , Kapoor Shivani , Wang Yin , Silvestri Giovannino , Baer Maria R.
Published: January 2024

Acute myeloid leukemia (AML) with fms-like tyrosine kinase 3 internal tandem duplication (FLT3-ITD) has poor outcomes. FLT3-ITD drives constitutive and aberrant FLT3 signaling, activating STAT5 and upregulating the downstream oncogenic serine/threonine kinase Pim-1. FLT3 inhibitors are in clinical use, but with limited and transient efficacy. We previously showed that concurrent treatment with Pim and FLT3 inhibitors increases apoptosis induction in FLT3-ITD–expressing cells through posttranslational downregulation of Mcl-1. Here we further elucidate the mechanism of action of this dual targeting strategy. Cytotoxicity, apoptosis and protein expression and turnover were measured in FLT3-ITD–expressing cell lines and AML patient blasts treated with the FLT3 inhibitor gilteritinib and/or the Pim inhibitors AZD1208 or TP-3654. Pim inhibitor and gilteritinib cotreatment increased apoptosis induction, produced synergistic cytotoxicity, downregulated c-Myc protein expression, earlier than Mcl-1, increased turnover of both proteins, which was rescued by proteasome inhibition, and increased efficacy and prolonged survival in an in vivo model. Gilteritinib and Pim inhibitor cotreatment of Ba/F3-ITD cells infected with T58A c-Myc or S159A Mcl-1 plasmids, preventing phosphorylation at these sites, did not downregulate these proteins, increase their turnover or increase apoptosis induction. Moreover, concurrent treatment with gilteritinib and Pim inhibitors dephosphorylated (activated) the serine/threonine kinase glycogen synthase kinase-3β (GSK-3β), and GSK-3β inhibition prevented c-Myc and Mcl-1 downregulation and decreased apoptosis induction. The data are consistent with c-Myc T58 and Mcl-1 S159 phosphorylation by activated GSK-3β as the mechanism of action of gilteritinib and Pim inhibitor combination treatment, further supporting GSK-3β activation as a therapeutic strategy in FLT3-ITD AML.

Significance:

FLT3-ITD is present in 25% of in AML, with continued poor outcomes. Combining Pim kinase inhibitors with the FDA-approved FLT3 inhibitor gilteritinib increases cytotoxicity in vitro and in vivo through activation of GSK-3β, which phosphorylates and posttranslationally downregulates c-Myc and Mcl-1. The data support efficacy of GSK-3β activation in FLT3-ITD AML, and also support development of a clinical trial combining the Pim inhibitor TP-3654 with gilteritinib.
Longitudinal Position and Cancer Risk in the United States Revisited
Authors: Niu Jin , Brown Charlotte , Law Michael , Colacino Justin A. , Ritov Ya'acov
Published: January 2024

The debate over daylight saving time (DST) has surged, with interests in the effects of sunlight exposure on health. Prior studies simulated DST and standard time conditions by analyzing different locations within time zones and neighboring areas across time zone borders. We analyzed cancer incidence rates from various longitudinal positions within time zones and at time zone borders in the contiguous United States. Using data from State Cancer Profiles (2016–2020), we analyzed total cancer of 19 types and specific rates for eight cancers, adjusted for age and includes all demographics. log-linear regression is used to replicate a previous study, and spatial regression models are employed to explore discontinuities at borders. Cancer rate differences lack statistical significance within time zones and near borders for total cancer and most individual cancers. Exceptions included breast, prostate, and liver and bile duct cancers, which exhibited significant relationships with relative position at the 95% significance level. Breast and liver and bile duct cancers saw decreases, while prostate cancer incidence increased from west to east within time zones. Relative position does not have a significant impact on cancer incidence, hence cancer development in general. Isolated exceptions may warrant further investigation as more data become available. Our findings challenge prior research, revealing numerous inconsistencies. These disparities urge a reconsideration of the potential disparities in human health associated with DST and standard time. They offer insights contribute to the ongoing discussion surrounding the retention or abandonment of DST.

Significance:

In this article, we investigate the relation between the epidemiology of cancer incidence in the United States and time zone–related longitudinal positions. Our results differ from previous research, which were based on a subset of our data, and show that the time zone effect on cancer incidence rate is not significant. Our research provides implications on the implementation of DST by suggesting that there is no cancer-risk associated reason to prefer one time over the other. Our study also uses regression discontinuity design using natural splines, a more advanced statistical method, to increase robustness of our result. Our findings challenge prior research, revealing numerous inconsistencies. These disparities urge a reconsideration of the potential disparities in human health associated with DST and standard time. They offer insights contribute to the ongoing discussion surrounding the retention or abandonment of DST.
Anterior Segment Optical Coherence Tomography Findings in Capsular Block Syndrome with Improvement in Myopia following Neodymium-Yttrium Aluminum Garnet Laser Treatment
Authors: Okemoto Hajime , Mito Tsuyoshi , Kawamorita Takushi , Sasaki Hiroshi
Published: January 2024

Introduction: Lacteocrumenasia is a relatively rare postoperative complication of cataract surgery. It is classified as a late-onset type of capsular block syndrome (CBS) and is often accompanied by myopia; however, its mechanism is not clearly understood. Case Presentation: We report a case of a 62-year-old male patient having CBS with myopia. The patient was treated with neodymium-yttrium aluminum garnet (Nd-YAG) laser posterior capsulotomy. We measured and compared the depth of the intraocular lens using anterior segment optical coherence tomography (AS-OCT) before and after laser treatment. Treatment resulted in refraction improvement of more than 1.0 diopters. The intraocular lens depth before and after Nd-YAG laser irradiation had very mild changes of less than 0.05 mm, which did not explain the refractive changes. Conclusion: Myopia in the early-onset type of CBS is caused by anterior deviation of the intraocular lens; however, the evaluation of this case using AS-OCT suggested that an abnormal intraocular lens position may not be involved in late-onset CBS.