bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends and Variability in Temperature and Related Extreme Indices in Rwanda during the Past Four Decades
Authors: Safari Bonfils , Sebaziga Joseph Ndakize
Published: September 2023

Analysis of the trends and variability of climate variables and extreme climate events is important for climate change detection in space and time. In this study, the trends and variabilities of minimum, maximum, and mean temperatures, as well as five extreme temperature indices, are analyzed over Rwanda for the period of 1983 to 2022. The Modified Mann–Kendall test and the Theil–Sen estimator are used for the analysis of, respectively, the trend and the slope. The standard deviation is used for the analysis of the temporal variability. It is found, on average, over the country, a statistically significant (α = 0.05) positive trend of 0.17 °C/decade and 0.20 °C/decade in minimum temperature, respectively, for the long dry season and short rain season. Statistically significant (α = 0.05) positive trends are observed for spatially averaged cold days (0.84 days/decade), warm nights (0.62 days/decade), and warm days (1.28 days/decade). In general, maximum temperature represents higher variability compared to the minimum temperature. In all seasons except the long dry season, statistically significant (α = 0.05) high standard deviations (1.4–1.6 °C) are observed over the eastern and north-western highlands for the maximum temperature. Cold nights show more variability, with a standard deviation ranging between 5 and 7 days, than the cold days, warm nights, and warm days, having, respectively, standard deviations ranging between 2 and 3, 4 and 5 days, and 3 and 4, and, especially in the area covering the central, south-western, south-central, and northwestern parts of Rwanda. Temperature increase and its variability have an impact on agriculture, health, water resources, infrastructure, and energy. The results obtained from this study are important since they can serve as the baseline for future projections. These can help policy decision making take objective measures for mitigation and adaptation to climate change impacts.
Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield
Authors: Fathollahi Arman , Gheisarnejad Meysam , Boudjadar Jalil , Derakhshandeh Sayed Yaser , Khooban Mohammad Hassan
Published: September 2023

In this paper, a new design strategy is developed for the Wireless Charging Electric Transit Bus (WCETB). The technology is innovative in that the battery in the bus is charged while it is moving over the charging infrastructure. In particular, an improved version of the Whale Optimization Algorithm (IWOA) is adopted for the WCETB system in the road map of Wakefield City, located in the United Kingdom. The main challenge in the WCETB is to select the power transmitter and battery size efficiently from an economical point of view. For this purpose, both factors are considered in the objective function to achieve the benefits of WCETBs from an energy perspective. Two analytical economic design optimization models are developed in this work. The first model is the real- environment model, which considers a WCETB system operating under typical traffic conditions characterized by vehicle interactions and inherent uncertainties. In this scenario, vehicle speeds vary with time, and specific traffic routes may encounter congestion. The second model concentrates on a WCETB system operating in a traffic-free environment with minimal vehicle interactions and uncertainties. The IWOA is implemented for the WCETB to operate in the real environment. Under traffic-free environment conditions, we utilize mathematical procedures and General Algebraic Modeling System (GAMS) software to solve the optimization problem. This approach not only allows us to comprehensively analyze the WCETB system’s behavior but also examine the interactions among different components of the objective function and constraints. Finally, a comprehensive numerical analysis under various conditions, including changes in the number of buses and increases in the length of routes, is conducted.
Modeling Bland–Altman Limits of Agreement with Fractional Polynomials—An Example with the Agatston Score for Coronary Calcification
Authors: Gerke Oke , Möller Sören
Published: September 2023

Bland–Altman limits of agreement are very popular in method comparison studies on quantitative outcomes. However, a straightforward application of Bland–Altman analysis requires roughly normally distributed differences, a constant bias, and variance homogeneity across the measurement range. If one or more assumptions are violated, a variance-stabilizing transformation (e.g., natural logarithm, square root) may be sufficient before Bland–Altman analysis can be performed. Sometimes, fractional polynomial regression has been used when the choice of variance-stabilizing transformation was unclear and increasing variability in the differences was observed with increasing mean values. In this case, regressing the absolute differences on a function of the average and applying fractional polynomial regression to this end were previously proposed. This review revisits a previous inter-rater agreement analysis on the Agatston score for coronary calcification. We show the inappropriateness of a straightforward Bland–Altman analysis and briefly describe the nonparametric limits of agreement of the original investigation. We demonstrate the application of fractional polynomials, use the Stata packages fp and fp_select, and discuss the use of degree-2 (the default setting) and degree-3 fractional polynomials. Finally, we discuss conditions for evaluating the appropriateness of nonstandard limits of agreement.
Bayesian Estimation of Variance-Based Information Measures and Their Application to Testing Uniformity
Authors: Al-Labadi Luai , Hamlili Mohammed , Ly Anna
Published: September 2023

Entropy and extropy are emerging concepts in machine learning and computer science. Within the past decade, statisticians have created estimators for these measures. However, associated variability metrics, specifically varentropy and varextropy, have received comparably less attention. This paper presents a novel methodology for computing varentropy and varextropy, drawing inspiration from Bayesian nonparametric methods. We implement this approach using a computational algorithm in R and demonstrate its effectiveness across various examples. Furthermore, these new estimators are applied to test uniformity in data.
Recent Advances on Transition Metal Chalcogenide for Sodium-Ion Batteries
Authors: Wei Chunyan , Qu Dongyang , Li Qiuyu , Sun Zhonghui , Song Zhongqian , Guan Hongyu , Niu Li
Published: September 2023

Sodium-ion batteries (SIBs) are expected to replace lithium-ion batteries (LIBs) as a new generation of energy storage devices due to their abundant sodium reserves and low cost. Among the anode materials of SIBs, transition metal chalcogenides (TMXs) have attracted much attention because of their large layer spacing, narrow band gap, and high theoretical capacity. However, in practical applications, TMXs face problems, such as structural instability and poor electrical conductivity. In this review, the research progress and challenges of TMXs in SIBs in recent years are summarized, the application of nanostructure design, defect engineering, cladding engineering, and heterogeneous construction techniques and strategies in improving the electrochemical performance of TMXs anode are emphatically introduced, and the storage mechanism of sodium is briefly summarized. Finally, the application and development prospects of TMX anodes in electrochemical energy storage are discussed and prospected.
Novel Fabrication of 3-D Cell Laden Micro-Patterned Porous Structure on Cell Growth and Proliferation by Layered Manufacturing
Authors: Chu Won-Shik , Park Hyeongryool , Moon Sangjun
Published: September 2023

This study focuses on developing and characterizing a novel 3-dimensional cell-laden micro-patterned porous structure from a mechanical engineering perspective. Tissue engineering holds great promise for repairing damaged organs but faces challenges related to cell viability, biocompatibility, and mechanical strength. This research aims to overcome these limitations by utilizing gelatin methacrylate hydrogel as a scaffold material and employing a photolithography technique for precise patterned fabrication. The mechanical properties of the structure are of particular interest in this study. We evaluate its ability to withstand external forces through compression tests, which provide insights into its strength and stability. Additionally, structural integrity is assessed over time to determine its performance in in vitro and potential in vivo environments. We investigate cell viability and proliferation within the micro-patterned porous structure to evaluate the biological aspects. MTT assays and immunofluorescence staining are employed to analyze the metabolic activity and distribution pattern of cells, respectively. These assessments help us understand the effectiveness of the structure in supporting cell growth and tissue regeneration. The findings of this research contribute to the field of tissue engineering and provide valuable insights for mechanical engineers working on developing scaffolds and structures for regenerative medicine. By addressing challenges related to cell viability, biocompatibility, and mechanical strength, we move closer to realizing clinically viable tissue engineering solutions. The novel micro-patterned porous structure holds promise for applications in artificial organ development and lays the foundation for future advancements in large soft tissue construction.
Macroinvertebrate Response to Internal Nutrient Loading Increases in Shallow Eutrophic Lakes
Authors: Peng Kai , Dong Rui , Qin Boqiang , Cai Yongjiu , Deng Jianming , Gong Zhijun
Published: September 2023

In eutrophic lakes, even if external loading is controlled, internal nutrient loading delays the recovery of lake eutrophication. When the input of external pollutants is reduced, the dissolved oxygen environment at the sediment interface improves in a season without algal blooms. As an important part of lake ecosystems, macroinvertebrates are sensitive to hypoxia caused by eutrophication; however, how this change affects macroinvertebrates is still unknown. In this study, we analysed the monitoring data of northern Lake Taihu from 2007 to 2019. After 2007, the external loading of Lake Taihu was relatively stable, but eutrophication began to intensify after 2013, and the nutrients in the sediments also began to decline, which was related to the efficient use of nutrients by algal blooms. The community structure and population density of macroinvertebrates showed different responses in different stages. In particular, the density of oligochaetes and the Shannon–Wiener index showed significant differences in their response to different stages, and their sensitivity to eutrophication was significantly reduced. Under eutrophication conditions dominated by internal loading, frequent hypoxia occurs at the sediment interface only when an algal bloom erupts. When there is no bloom, the probability of sediment hypoxia is significantly reduced under the disturbance of wind. Our results indicate that the current method for evaluating lake eutrophication based on oligochaetes and the Shannon–Wiener diversity index may lose its sensitivity.
Lichens and Mosses as Biomonitors of Indoor Pollution
Authors: Paoli Luca , Bandoni Elena , Sanità di Toppi Luigi
Published: September 2023

Biomonitoring in indoor environments is a recent application, and so far, indoor air quality (IAQ) has been investigated only in a few cases using photosynthesising biomonitors. On the whole, 22 studies have been selected and reviewed, being specifically focused on the assessment of IAQ using biomonitors, such as lichens (9 papers), mosses (10), or their combination (3). In general, indoor samples face an altered light regime, ventilation, and a reduced hydration, which should be taken into consideration during the design and implementation of indoor monitoring. This review highlights critical issues (and some solutions) related to sample devitalisation (moss), hydration during exposure, preparation of the exposure device (mostly lichen and moss bags), duration of the exposure, post-exposure treatments, assessment of the vitality of the samples, as well as data elaboration and interpretation. This review evidences the feasibility and usefulness of lichen/moss monitoring in indoor environments and the need to develop standardised protocols.
Tea Tree Essential Oil Kills Escherichia coli and Staphylococcus epidermidis Persisters
Authors: Nguyen LeeAnn , DeVico Brianna , Mannan Maliha , Chang Matthew , Rada Santacruz Cristina , Siragusa Christopher , Everhart Sydney , Fazen Christopher H.
Published: September 2023

Persister cells are a small subpopulation of non-growing bacteria within a population that can survive long exposures to antibiotic treatment. Following antibiotic removal, persister cells can regrow and populate, playing a key role in the chronic reoccurrence of bacterial infections. The development of new molecules and methods to kill bacterial persisters is critical. Essential oils and other natural products have long been studied for their antimicrobial effects. Here, we studied the effectiveness of tea tree essential oil (TTO), a common component in many commercial care products, against Escherichia coli and Staphylococcus epidermidis persister cells. Using biphasic kill curve assays, we found that concentrations of 0.5% and 1.0% TTO for E. coli and S. epidermidis, respectively, completely eradicated persister cells over a period of 24 h, with the component terpinen-4-ol responsible for most of the killing. Using a colorimetric assay, it was determined that the TTO exhibited its anti-persister effects through a membrane disruption mechanism.
Peering into the Brain’s Estrogen Receptors: PET Tracers for Visualization of Nuclear and Extranuclear Estrogen Receptors in Brain Disorders
Authors: Arjmand Shokouh , Bender Dirk , Jakobsen Steen , Wegener Gregers , Landau Anne M.
Published: September 2023

Estrogen receptors (ERs) play a multitude of roles in brain function and are implicated in various brain disorders. The use of positron emission tomography (PET) tracers for the visualization of ERs’ intricate landscape has shown promise in oncology but remains limited in the context of brain disorders. Despite recent progress in the identification and development of more selective ligands for various ERs subtypes, further optimization is necessary to enable the reliable and efficient imaging of these receptors. In this perspective, we briefly touch upon the significance of estrogen signaling in the brain and raise the setbacks associated with the development of PET tracers for identification of specific ERs subtypes in the brain. We then propose avenues for developing efficient PET tracers to non-invasively study the dynamics of ERs in the brain, as well as neuropsychiatric diseases associated with their malfunction in a longitudinal manner. This perspective puts several potential candidates on the table and highlights the unmet needs and areas requiring further research to unlock the full potential of PET tracers for ERs imaging, ultimately aiding in deepening our understanding of ERs and forging new avenues for potential therapeutic strategies.
Exploring the Feasibility of Cloud-Point Extraction for Bioactive Compound Recovery from Food Byproducts: A Review
Authors: Chatzimitakos Theodoros , Athanasiadis Vassilis , Mantiniotou Martha , Kalompatsios Dimitrios , Bozinou Eleni , Giovanoudis Ioannis , Lalas Stavros I.
Published: September 2023

In recent years, the production of food biomass waste has been increasing rapidly. This necessitates urgent measures to be taken so as to utilize them. Since most food biomass waste contains useful bioactive substances, cloud-point extraction (CPE) has emerged as a promising solution to valorize waste. CPE is an extraction method employed for the extraction and preconcentration of various chemical compounds, including polyphenols and flavonoids. As with any other extraction procedure, CPE isolates the target compound(s) from the sample, resulting in increased recovery. One major advantage of CPE is that the extraction is carried out without special equipment or harmful reagents. Moreover, other significant advantages are its effectiveness, simplicity, safety, and rapidity. This review focuses on the extraction of bioactive compounds from food-based waste using CPE and highlights the important parameters that can be tuned to improve the performance of CPE. Furthermore, the potential in promoting environmentally friendly practices within the food industry is also discussed.
An Improved Harris Hawks Optimization Algorithm and Its Application in Grid Map Path Planning
Authors: Huang Lin , Fu Qiang , Tong Nan
Published: September 2023

Aimed at the problems of the Harris Hawks Optimization (HHO) algorithm, including the non-origin symmetric interval update position out-of-bounds rate, low search efficiency, slow convergence speed, and low precision, an Improved Harris Hawks Optimization (IHHO) algorithm is proposed. In this algorithm, a circle map was added to replace the pseudo-random initial population, and the population boundary number was reduced to improve the efficiency of the location update. By introducing a random-oriented strategy, the information exchange between populations was increased and the out-of-bounds position update was reduced. At the same time, the improved sine-trend search strategy was introduced to improve the search performance and reduce the out-of-bound rate. Then, a nonlinear jump strength combining escape energy and jump strength was proposed to improve the convergence accuracy of the algorithm. Finally, the simulation experiment was carried out on the test function and the path planning application of a 2D grid map. The results show that the Improved Harris Hawks Optimization algorithm is more competitive in solving accuracy, convergence speed, and non-origin symmetric interval search efficiency, and verifies the feasibility and effectiveness of the Improved Harris Hawks Optimization in the path planning of a grid map.
Design and Experiment of a Biomimetic Duckbill-like Vibration Chain for Physical Weed Control during the Rice Tillering Stage
Authors: Fang Longyu , Luo Xiwen , Wang Zaiman , Yang Wenwu , Li Hui , Song Shiyu , Xie Haoyang , Hu Jianhao , Chen Weiman , Liu Qinghai
Published: September 2023

The widespread use of chemical herbicides has jeopardized concerns about food safety and ecological consequences. To address these issues and reduce reliance on chemical herbicides, a physical weed control device was developed for the tillering stage in paddy fields. This device features a biomimetic duckbill-like vibration chain that effectively controls weed outbreaks. The chain penetrates the soft surface soil of the paddy field under gravity and rapidly stirs the soil through vibration, leading to the detachment of the weed roots anchored in the surface layer. Simultaneously, the device avoids mechanical damage to rice seedlings rooted in deeper soil. This study aimed to investigate the effects of chain structural parameters (the number of chain rows, vibration amplitude, and length of chains) and operational parameters (vibration frequency and working velocity) on weed control efficiency and rice seedling damage. Through a central composite regression field test, the optimal device structure and operational parameters were determined. The optimization results demonstrated that a vibration amplitude of 78.8 mm, a chain length of 93.47 cm, and 3.4 rows of chains, along with a vibration frequency and working velocity ranging from 0.5 to 1.25 m/s, achieved an optimal weeding effect. Under the optimal parameter combination, field test results demonstrated that approximately 80% of the weeds in the field were effectively cleared. This indicates that the design of the biomimetic duckbill-like vibration chain weeding device exhibits a relatively superior weeding performance, offering a practical solution for the management of weeds in rice fields.
Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm
Authors: Li Xin , Li Mingyang , Yu Moduo , Fan Qinqin
Published: September 2023

Distribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault reconfiguration of the distribution network is often regarded as a single-objective or multi-objective optimization problem, and its multimodality is often ignored in existing studies. Therefore, the obtained solutions may be unsuitable or infeasible when the environment changes. To improve the availability and robustness of the solutions, an improved discrete multimodal multi-objective particle swarm optimization (IDMMPSO) algorithm is proposed to solve the fault reconfiguration problem of the distribution network. To demonstrate the performance of the proposed IDMMPSO algorithm, the IEEE33-bus distribution system is used in the experiment. Moreover, the proposed algorithm is compared with other competitors. Experimental results show that the proposed algorithm can provide different equivalent solutions for decision-makers in solving the fault reconfiguration problem of the distribution network.
Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures
Authors: Lee Dong-Hee , Kim Hwi-Su , Park Ki-Woong , Park Hamin , Cho Won-Ju
Published: September 2023

In this study, we enhance the synaptic behavior of artificial synaptic transistors by utilizing nanowire (NW)-type polysilicon channel structures. The high surface-to-volume ratio of the NW channels enables efficient modulation of the channel conductance, which is interpreted as the synaptic weight. As a result, NW-type synaptic transistors exhibit a larger hysteresis window compared to film-type synaptic transistors, even within the same gate voltage sweeping range. Moreover, NW-type synaptic transistors demonstrate superior short-term facilitation and long-term memory transition compared with film-type ones, as evidenced by the measured paired-pulse facilitation and excitatory post-synaptic current characteristics at varying frequencies and pulse numbers. Additionally, we observed gradual potentiation/depression characteristics, making these artificial synapses applicable to artificial neural networks. Furthermore, the NW-type synaptic transistors exhibit improved Modified National Institute of Standards and Technology pattern recognition rate of 91.2%. In conclusion, NW structure channels are expected to be a promising technology for next-generation artificial intelligence (AI) semiconductors, and the integration of NW structure channels has significant potential to advance AI semiconductor technology.
Improving Audiology Student Training by Clinical Simulation of Tinnitus: A Glimpse of the Lived Experience of Tinnitus
Authors: Bourez Pierre H. , Vallet Guillaume T. , Fournier Philippe
Published: September 2023

Purpose: Student audiology training in tinnitus evaluation and management is heterogeneous and has been found to be insufficient. We designed a new clinical simulation laboratory for training students on psychoacoustic measurements of tinnitus: one student plays the role of the tinnitus patient, wearing a device producing a sound like tinnitus on one ear, while another student plays the role of the audiologist, evaluating their condition. The objective of the study was to test this new clinical simulation laboratory of tinnitus from the perspective of the students. Method: This study reports the findings from twenty-one audiology students (20 female and 1 male, mean age = 29, SD = 7.7) who participated in this laboratory for a mandatory audiology class at the Laval University of Quebec. Three students had hearing loss (one mild, two moderate). All students played the role of both the clinician and the patient, alternately. They also had to fill out a questionnaire about their overall experience of the laboratory. Results: The qualitative analysis revealed three main themes: “Benefits of the laboratory on future practice”, “Barriers and facilitators of the psychoacoustic assessment”, and “Awareness of living with tinnitus”. The participants reported that this experience would have a positive impact on their ability to manage tinnitus patients in their future career. Conclusion: This fast, cheap, and effective clinical simulation method could be used by audiology and other healthcare educators to strengthen students’ skills and confidence in tinnitus evaluation and management. The protocol is made available to all interested parties.
The Relationship between Technology Addiction and Attitude toward Reading: An Investigation on Pre-Service Teachers
Authors: Gerez Taşgın Fatma , Taşgın Adnan
Published: September 2023

In this study, we aimed to examine pre-service teachers’ attitudes toward reading books and their technology addictions. We used a correlational survey model. The sample of this study consisted of a Turkish pre-service teachers group studying at the Department of Turkish Education in the education faculty of a state university in Turkey. Our research used the “Attitude Scale Towards Reading” and “Technology Addiction Scale” as data collection tools. As a result of the study, we determined that the attitudes towards reading of pre-service teachers were positive. Furthermore, there was a significant difference in favor of female pre-service teachers in the sub-dimensions of book-reading love, reluctance to read, and stress. The significant difference in the online game-playing sub-dimension of technology addiction favored male pre-service teachers. On the other hand, we found a negative meaningful relationship between pre-service teachers’ technology addiction and their attitudes toward reading.
Is There an Association between the Use of Social Media and Self-Rated Health?
Authors: Ndlovu Kholisani , Ramalepe Lebogang M. , Nwogwugwu Nwamaka C. , Olutola Bukola G.
Published: September 2023

This study sought to determine the association between social media and self-rated health. This study used the 2022 Health Information National Trends Survey for American adults. A statistical analysis was conducted using Chi-square and multivariable logistic regression. Of the 6018 study participants, the majority reported that they were in excellent/very good and good health (82.9%, n = 4930). More than half (58.2%, n = 3268) of the respondents reported that they visited a social media site almost every day in the past 12 months, while 76.8% (n = 4843) reported that they never interacted with people who had similar health or medical issues on social media. There was no association between everyday visits to a social media site, interaction with people with similar health/medical issues on social media, or watching a health-related video on social media and self-rated health. Those who had full-time employment were more likely to rate their health as excellent/very good/good (AOR: 2.394, 95% Conf. Int: 1.820–3.149) compared to those with no full-time employment. Marital status, confidence in taking care of oneself, education, and current smoking were associated with self-rated health. This study showed that the use of social media which included the watching of health-related videos was not associated with self-rated health.
Exploring Substance Abuse and the Dark Tetrad in Health Sciences and Non-Health Sciences Students
Authors: Moraes Marina Carvalho de Lima , Russo Giulia Cunha , Prado Julia da Silva , Lima-Costa Ariela Raissa , Bonfá-Araujo Bruno , Schermer Julie Aitken
Published: September 2023

Substance abuse can be used as a coping strategy to manage stress related to academic activities and is a risk-taking behavior that is also associated with people with higher levels of the Dark Tetrad personality traits. Our study aimed to investigate the association between substance abuse and the Dark Tetrad in students in health and non-health sciences fields. Our sample was composed of 174 college students between 18 and 58 years old (M = 25.60; SD = 9.14). Students completed self-report psychopathy, narcissism, Machiavellianism, sadism, and substance use scales. Results suggest that men consumed more substances and scored higher on the Dark Tetrad than women. Also, when comparing fields, men from health sciences tended to score higher on dark personality traits. These results emphasize the potential risk factors associated with dark personality traits and the consumption of licit and illicit substances by college students, highlighting the need for further studies with this population and the impact of these behaviors and characteristics on future professional practice.
Inhibition of Anaplastic Lymphoma Kinase (Alk) as Therapeutic Target to Improve Brain Function in Neurofibromatosis Type 1 (Nf1)
Authors: Weiss Joseph B. , Raber Jacob
Published: September 2023

Neurofibromatosis type 1 (Nf1) is a neurodevelopmental disorder and tumor syndrome caused by loss of function mutations in the neurofibromin gene (Nf1) and is estimated to affect 100,000 people in the US. Behavioral alterations and cognitive deficits have been found in 50–70% of children with Nf1 and include specific problems with attention, visual perception, language, learning, attention, and executive function. These behavioral alterations and cognitive deficits are observed in the absence of tumors or macroscopic structural abnormalities in the central nervous system. No effective treatments for the behavioral and cognitive disabilities of Nf1 exist. Inhibition of the anaplastic lymphoma kinase (Alk), a kinase which is negatively regulated by neurofibromin, allows for testing the hypothesis that this inhibition may be therapeutically beneficial in Nf1. In this review, we discuss this area of research and directions for the development of alternative therapeutic strategies to inhibit Alk. Even if the incidence of adverse reactions of currently available Alk inhibitors was reduced to half the dose, we anticipate that a long-term treatment would pose challenges for efficacy, safety, and tolerability. Therefore, future efforts are warranted to investigate alternative, potentially less toxic and more specific strategies to inhibit Alk function.
Mesenchymal Chondrosarcoma from Diagnosis to Clinical Trials
Authors: Dudzisz-Śledź Monika , Kondracka Monika , Rudzińska Monika , Zając Agnieszka E. , Firlej Wiktoria , Sulejczak Dorota , Borkowska Aneta , Szostakowski Bartłomiej , Szumera-Ciećkiewicz Anna , Piątkowski Jakub , Rutkowski Piotr , Czarnecka Anna M.
Published: September 2023

Mesenchymal chondrosarcoma (MCS) is a rare subtype of chondrosarcoma with a poor prognosis. Although these tumors are sensitive to radiotherapy/chemotherapy, the standard treatment for localized MCS is only surgical resection, and there are no established treatment guidelines for patients with advanced and metastatic MCS. Due to the low incidence of MCS, the pathology of these tumors is still unknown, and other therapeutic options are lacking. Some studies show the potential role of the PDGF/PPI3K/AKT, PKC/RAF/MEK/ERK, and pRB pathways, and BCL2 overexpression in the pathogenesis of MCS. These findings provide an opportunity to use protein kinases and BCL2 inhibitors as potential therapy in MCS. In this review, we summarize the current knowledge about MCS diagnosis and treatment options. We show the immunological and molecular biomarkers used in the diagnosis of MCS. In addition, we discuss the known prognostic and predictive factors in MCS. Finally, we present the novel trends, including targeted therapies and ongoing clinical trials using protein kinase inhibitors and the death receptor 5 (DR5) agonist, which may be the focus of future MCS treatment studies.
Machine Learning for Digital Scoring of PRMT6 in Immunohistochemical Labeled Lung Cancer
Authors: Mahmoud Abeer M. , Brister Eileen , David Odile , Valyi-Nagy Klara , Sverdlov Maria , Gann Peter H. , Kim Sage J.
Published: September 2023

Lung cancer is the leading cause of cancer death in the U.S. Therefore, it is imperative to identify novel biomarkers for the early detection and progression of lung cancer. PRMT6 is associated with poor lung cancer prognosis. However, analyzing PRMT6 expression manually in large samples is time-consuming posing a significant limitation for processing this biomarker. To overcome this issue, we trained and validated an automated method for scoring PRMT6 in lung cancer tissues, which can then be used as the standard method in future larger cohorts to explore population-level associations between PRMT6 expression and sociodemographic/clinicopathologic characteristics. We evaluated the ability of a trained artificial intelligence (AI) algorithm to reproduce the PRMT6 immunoreactive scores obtained by pathologists. Our findings showed that tissue segmentation to cancer vs. non-cancer tissues was the most critical parameter, which required training and adjustment of the algorithm to prevent scoring non-cancer tissues or ignoring relevant cancer cells. The trained algorithm showed a high concordance with pathologists with a correlation coefficient of 0.88. The inter-rater agreement was significant, with an intraclass correlation of 0.95 and a scale reliability coefficient of 0.96. In conclusion, we successfully optimized a machine learning algorithm for scoring PRMT6 expression in lung cancer that matches the degree of accuracy of scoring by pathologists.
Protective Factors against Fear of Cancer Recurrence in Breast Cancer Patients: A Latent Growth Model
Authors: Bentley Gabriella , Zamir Osnat , Dahabre Rawan , Perry Shlomit , Karademas Evangelos C. , Poikonen-Saksela Paula , Mazzocco Ketti , Sousa Berta , Pat-Horenczyk Ruth
Published: September 2023

The current study aimed to examine the fear of cancer recurrence (FCR) trajectory and protective predictors in women coping with breast cancer (BC). The study’s model investigated whether a higher coping self-efficacy and positive cognitive–emotion regulation at the time of the BC diagnosis would lead to reduced levels of FCR at six months and in later stages (12 and 18 months) post-diagnosis. The sample included 494 women with stages I to III BC from Finland, Italy, Portugal, and Israel. They completed self-report questionnaires, including the Fear of Cancer Recurrence Inventory (FCRI-SF), the Cancer Behavior Inventory-Brief Version (CBI-B), the Cognitive–Emotion Regulation Questionnaire (CERQ short), and medical–social–demographic data. Findings revealed that a higher coping self-efficacy at diagnosis predicted lower FCR levels after six months but did not impact the FCR trajectory over time. Surprisingly, positive cognitive–emotion regulation did not predict FCR levels or changes over 18 months. FCR levels remained stable from six to 18 months post-diagnosis. This study emphasizes the importance of developing specific cancer coping skills, such as coping self-efficacy. Enhancing coping self-efficacy in the first six months after BC diagnosis may lead to lower FCR levels later, as FCR tends to persist in the following year.
Comparing Predicted Toxicities between Hypofractionated Proton and Photon Radiotherapy of Liver Cancer Patients with Different Adaptive Schemes
Authors: Nenoff Lena , Sudhyadhom Atchar , Lau Jackson , Sharp Gregory C. , Paganetti Harald , Pursley Jennifer
Published: September 2023

With the availability of MRI linacs, online adaptive intensity modulated radiotherapy (IMRT) has become a treatment option for liver cancer patients, often combined with hypofractionation. Intensity modulated proton therapy (IMPT) has the potential to reduce the dose to healthy tissue, but it is particularly sensitive to changes in the beam path and might therefore benefit from online adaptation. This study compares the normal tissue complication probabilities (NTCPs) for liver and duodenal toxicity for adaptive and non-adaptive IMRT and IMPT treatments of liver cancer patients. Adaptive and non-adaptive IMRT and IMPT plans were optimized to 50 Gy (RBE = 1.1 for IMPT) in five fractions for 10 liver cancer patients, using the original MRI linac images and physician-drawn structures. Three liver NTCP models were used to predict radiation-induced liver disease, an increase in albumin-bilirubin level, and a Child–Pugh score increase of more than 2. Additionally, three duodenal NTCP models were used to predict gastric bleeding, gastrointestinal (GI) toxicity with grades >3, and duodenal toxicity grades 2–4. NTCPs were calculated for adaptive and non-adaptive IMRT and IMPT treatments. In general, IMRT showed higher NTCP values than IMPT and the differences were often significant. However, the differences between adaptive and non-adaptive treatment schemes were not significant, indicating that the NTCP benefit of adaptive treatment regimens is expected to be smaller than the expected difference between IMRT and IMPT.
Evaluation of Real-Life Chemoimmunotherapy Combination in Patients with Metastatic Small Cell Lung Carcinoma (SCLC): A Multicentric Case–Control Study
Authors: Ezzedine Rémy , Canellas Anthony , Naltet Charles , Wislez Marie , Azarian Reza , Seferian Andrei , Giroux Leprieur Etienne
Published: September 2023

The current first-line standard treatment for advanced small cell lung cancer (SCLC) is a combination of chemotherapy and immunotherapy. However, few efficacy data are available in a real-life settings, including frail patients. The aim of this study is to describe the real-life efficacy of chemoimmunotherapy in an unselected SCLC population. We conducted a retrospective multicenter study, which compared two cohorts of patients with treatment-naive metastatic SCLC treated in six academic centers in the Greater Paris area. Cohort 1 included patients treated with chemotherapy between January 2017 and December 2018, and cohort 2 included patients treated with chemoimmunotherapy between January 2019 and December 2020. A total of 153 consecutive patients were included (cohort 1: n = 96; cohort 2: n = 57). Clinical characteristics were similar between the two cohorts. Overall survival (OS) was statistically higher in cohort 2 (median survival 15.47 months) than in cohort 1 (median survival 9.5 months) (p = 0.0001). OS for patients with a performance status ≥2 and for patients ≥70 years old was not statistically different between the two cohorts. Chemoimmunotherapy efficacy was better compared to chemotherapy alone in case of brain or liver metastases. In conclusion, the combination of chemoimmunotherapy in metastatic SCLC appears to provide a real-life OS benefit. Dedicated clinical trials are needed to test this strategy in patients with impaired performance status or advanced age.
Predicting Long-Term Care Service Demands for Cancer Patients: A Machine Learning Approach
Authors: Chien Shuo-Chen , Chang Yu-Hung , Yen Chia-Ming , Chen Ying-Erh , Liu Chia-Chun , Hsiao Yu-Ping , Yang Ping-Yen , Lin Hong-Ming , Lu Xing-Hua , Wu I-Chien , Hsu Chih-Cheng , Chiou Hung-Yi , Chung Ren-Hua
Published: September 2023

Background: Long-term care (LTC) service demands among cancer patients are significantly understudied, leading to gaps in healthcare resource allocation and policymaking. Objective: This study aimed to predict LTC service demands for cancer patients and identify the crucial factors. Methods: 3333 cases of cancers were included. We further developed two specialized prediction models: a Unified Prediction Model (UPM) and a Category-Specific Prediction Model (CSPM). The UPM offered generalized forecasts by treating all services as identical, while the CSPM built individual predictive models for each specific service type. Sensitivity analysis was also conducted to find optimal usage cutoff points for determining the usage and non-usage cases. Results: Service usage differences in lung, liver, brain, and pancreatic cancers were significant. For the UPM, the top 20 performance model cutoff points were adopted, such as through Logistic Regression (LR), Quadratic Discriminant Analysis (QDA), and XGBoost (XGB), achieving an AUROC range of 0.707 to 0.728. The CSPM demonstrated performance with an AUROC ranging from 0.777 to 0.837 for the top five most frequently used services. The most critical predictive factors were the types of cancer, patients’ age and female caregivers, and specific health needs. Conclusion: The results of our study provide valuable information for healthcare decisions, resource allocation optimization, and personalized long-term care usage for cancer patients.
Low Alanine-Aminotransferase Blood Activity Is Associated with Increased Mortality in Chronic Lymphocytic Leukemia Patients: A Retrospective Cohort Study of 716 Patients
Authors: Hellou Tamer , Dumanis Guy , Badarna Arwa , Segal Gad
Published: September 2023

Background: Chronic lymphocytic leukemia (CLL) is one of the most common hematologic malignancies, especially among elderlies. Several prognostic scores are available that utilize the characteristics of patients’ blood counts and cytogenetic anomalies—all are features of the disease rather than of the patient. Addressing the route of personalized rather than precise medicine, we refer to the assessment of patients’ status of sarcopenia and frailty. Low alanine aminotransferase (ALT) was already shown to function as a surrogate marker for sarcopenia and frailty. We decided to find a possible correlation between low ALT values and poor prognosis of CLL patients. Patients and Methods: This is a retrospective cohort study of CLL patients treated in a large, tertiary medical center, as outpatients or inpatients. Their frailty status was evaluated in a retrospective manner. We defined patients with ALT below 12 IU/L as frail and divided our cohort into two groups including a low ALT level group (ALT < 12) and a normal ALT level group (ALT ≥ 12). Results: Overall, our final analysis included 716 CLL patients, of which 161 (22.5%) had ALT levels lower than 12 IU/L. There was no significant difference in patients’ age between the two groups. Patients with the low ALT had a lower hemoglobin concentration (median 10.8 g/dL [IQR = 2.7] vs. 12.2 [IQR = 3.1]; p < 0.001) and a higher proportion of patients were classified as Binet C score [48.4% vs. 31.1%]; p < 0.001). Frail CLL patients’ survival was significantly shorter when compared to non-frail patients, in both the univariate [HR = 1.6 [95% confidence interval, CI 1.23, 2.0]; p < 0.01] and multivariate analyses [HR = 1.3 [95% CI 1.0, 1.7]; p = 0.03]. Conclusions: Sarcopenia and frailty assessment, based on blood ALT measurements, could potentially point out differences in CLL patients’ prognoses. Such assessment could serve the purpose of treatment personalization of CLL patients.
Liquid Biopsies for Colorectal Cancer and Advanced Adenoma Screening and Surveillance: What to Measure?
Authors: Eikenboom Ellis L. , Wilting Saskia M. , Deger Teoman , Srebniak Malgorzata I. , Van Veghel-Plandsoen Monique , Boers Ruben G. , Boers Joachim B. , van IJcken Wilfred F. J. , Gribnau Joost H. , Atmodimedjo Peggy , Dubbink Hendrikus J. , Martens John W. M. , Spaander Manon C. W. , Wagner Anja
Published: September 2023

Colorectal cancer (CRC) colonoscopic surveillance is effective but burdensome. Circulating tumor DNA (ctDNA) analysis has emerged as a promising, minimally invasive tool for disease detection and management. Here, we assessed which ctDNA assay might be most suitable for a ctDNA-based CRC screening/surveillance blood test. In this prospective, proof-of-concept study, patients with colonoscopies for Lynch surveillance or the National Colorectal Cancer screening program were included between 7 July 2019 and 3 June 2022. Blood was drawn, and if advanced neoplasia (adenoma with villous component, high-grade dysplasia, ≥10 mm, or CRC) was detected, it was analyzed for chromosomal copy number variations, single nucleotide variants, and genome-wide methylation (MeD-seq). Outcomes were compared with corresponding patients’ tissues and the MeD-seq results of healthy blood donors. Two Lynch carriers and eight screening program patients were included: five with CRC and five with advanced adenomas. cfDNA showed copy number variations and single nucleotide variants in one patient with CRC and liver metastases. Eight patients analyzed with MeD-seq showed clustering of Lynch-associated and sporadic microsatellite instable lesions separate from microsatellite stable lesions, as did healthy blood donors. In conclusion, whereas copy number changes and single nucleotide variants were only detected in one patient, cfDNA methylation profiles could discriminate all microsatellite instable advanced neoplasia, rendering this tool particularly promising for LS surveillance. Larger studies are warranted to validate these findings.
Treatment of High-Risk Neuroblastoma with Dinutuximab and Chemotherapy Administered in all Cycles of Induction
Authors: Cupit-Link Margaret , Federico Sara M.
Published: September 2023

Administration of chemoimmunotherapy using concurrent chemotherapy and an anti-GD2 monoclonal antibody (mAb), dinutuximab (DIN), demonstrated efficacy for the treatment of relapsed and refractory neuroblastoma. Chemoimmunotherapy, using a humanized anti-GD2 mAb, demonstrated a signal of activity in a phase 2 study for the treatment of patients with newly diagnosed high-risk neuroblastoma (HRNBL). In this single-institution retrospective study, patients with HRNBL received an Induction chemotherapy regimen plus DIN in all Induction cycles. Toxicity and response data were abstracted from the electronic medical record. Toxicities were graded by CTCAE v.5.0. The end of Induction (EOI) objective response rate was determined using the Revised International Neuroblastoma Response Criteria. Twenty-seven patients with HRNBL (23 newly diagnosed, 16 females, median age 3.9 years) started Induction chemoimmunotherapy from 27 January 2017 to 28 December 2022. All patients received DIN with all cycles of Induction therapy, and all but one patient completed Induction therapy. The most common non-hematologic grade ≥ 3 toxicities included fever (44%), hypoxemia (20%), and hypoalbuminemia (11%). End of Induction responses included eighteen with a complete response (CR), seven with a partial response (PR), one with progressive disease (PD), and zero with a minor response or stable disease. Twenty-six of twenty-seven patients (96%) completed all Induction cycles and were evaluable for a response. The EOI response of PR or better in the evaluable cohort was 96%. Dinutuximab was well tolerated with all Induction cycles, demonstrated an encouraging EOI response rate, and should be evaluated in a randomized study.