bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of intensive parameters on the mafic paragenesis of nepheline syenites: the Monte de Trigo alkaline suite, southeastern Brazil
Authors: Enrich G. E. R. , Ruberti E. , Azzone R. G. , Rosa P. A. S. , Gomes C. B.
Published: August 2024

The Monte de Trigo Alkaline Suite is a Late Cretaceous syenite–gabbroid occurrence from the Serra do Mar Alkaline Province, southeastern Brazil. It has a zoned nepheline syenitic stock with nepheline syenite I (NSI), the most SiO
2
-undersaturated, in the centre, surrounded by nepheline syenite II (NSII) and alkali feldspar syenite with nepheline (SN). Synplutonic miaskitic and agpaitic nepheline microsyenite (MNM and ANM, respectively) dykes cut across the stock. Extensive fractionation of alkali feldspar and mafic minerals is attributed to the formation of the syenitic facies and dykes. Mineral chemical data indicate that SN crystallized at relatively high silica activity (
a
SiO
2
; 0.5–0.7),
a
H
2
O (0.24–0.11) and
f
O
2
(difference from the fayalite–magnetite–quartz buffer in log units, ΔFMQ + 0.2 to ΔFMQ − 0.2), in contrast to NSII and NSI (
a
SiO
2
, ∼0.41;
a
H
2
O, 0.05–0.02; and
f
O
2
, ΔFMQ − 1.4 to ΔFMQ − 1.1). These parameters vary with magma evolution towards the phonolite eutectic and appear to control variations in paragenesis, from hastingsite + biotite ± diopside/hedenbergite in SN to hastingsite in NSII and hastingsite + hedenbergite in NSI. The MNM have high
a
H
2
O (0.31) and hastingsite + biotite + aegirine–augite assemblages. In contrast, the ANM are characterized by an F-rich anhydrous agpaitic assemblage.
CalMe: A Tangible Environment To Enhance Pupils Group Work Regulation
Authors: Bertolo David , Faedda Stephane , Olry Alexis , Veytizou Julien , Vivian Robin , Fleck Stéphanie
Published: August 2024

A large number of studies highlight the importance of regulation in collaborative learning. Nevertheless, only some studies describe how to get or support pupils to learn to regulate group work in school. In this context, we aim to understand if a specifically designed tangible environment can promote a regulated collaboration process during a face-to-face activity in school. Therefore, we conducted a two-year design-based research (DBR) study. This article describes the DBR cycles in detail and the steps we have executed to develop, test, implement, and evaluate a set of tangible artifacts called CalMe (for Collective attention led by a Mediated environment). First, we identified three specific dimensions that interfere with collaborative learning in the classroom: team building and collective decision-making, task regulation awareness, and oversolicitation limitation. Second, we proposed design choices leading to the first iteration of a CalMe device that meets these needs. We then assessed usability and acceptability before the pedagogical validation steps. Third, through a pilot study, we evaluated the pedagogical potential of the second iteration of the CalMe device in a real context of use in an elementary school class. We collected and analyzed data from surveys, focus groups, log data, and video recordings through all the steps. Moreover, to allow for duplication of the study, we propose and detail our methodological approach. This study shows an empirical example of a DBR process that allows responding as closely as possible to the needs of both pupils and teachers. This work also provides input to teachers regarding a better understanding of collaborative problem-solving activities. Although there is still room for improvement on specific dimensions related to task regulation, such as better management of ambient noise or work tempo, the results indicate that the CalMe device allows for a regulated collaboration process in schools. It shows an HCI design process that can be an example of how to influence classroom activities through technology to promote positive collaborative learning experiences.
Cost-Efficient Deep Neural Network Placement in Edge Intelligence-Enabled Internet of Things
Authors: Tian Hao , Xu Xiaolong , Wu Hongyue , Zhao Qingzhan , Dai Jianguo , Khan Maqbool
Published: August 2024

Edge intelligence (EI) integrates edge computing and artificial intelligence empowering service providers to deploy deep neural networks (DNNs) on edge servers in proximity to users to provision intelligent applications (e.g., autonomous driving) for ubiquitous Internet of Things (IoT) in smart cities, which facilitates the quality of experience (QoE) of users and improves the processing and energy efficiency. However, considering DNN is typically computational-intensive and resource-hungry, conventional placement approaches ignore the influence of multi-dimensional resource requirements (processor, memory, etc.), which may degrade the real-time performance. Moreover, with the increasing scale of geo-distributed edge servers, centralized decision-making is still challenging to find the optimal strategies effectively. To overcome these shortcomings, in this paper we propose a game theoretic DNN placement approach in EI-enabled IoT. First, a DNN placement optimization problem is formulated to maximize system benefits, which is proven to be

\(\mathcal {N}\mathcal {P} \)

-hard and model the original problem as an exact potential game (EPG). Moreover, an
EP
G-based DNN m
o
del p
l
acement algorithm, named EPOL, is designed for edge servers to make sub-optimal strategies independently and theoretical analysis is possessed to guarantee the performance of EPOL. Finally, real-world dataset based experimental results corroborate the superiority and effectiveness of EPOL.
A Reversible Perspective on Petri Nets and Event Structures
Authors: Melgratti Hernán , Mezzina Claudio Antares , Pinna G. Michele
Published: August 2024

Event structures have emerged as a foundational model for concurrent computation, explaining computational processes by outlining the events and the relationships that dictate their execution. They play a pivotal role in the study of key aspects of concurrent computation models, such as causality and independence, and have found applications across a broad range of languages and models, spanning realms like persistence, probabilities, and quantum computing. Recently, event structures have been extended to address reversibility, where computational processes can undo previous computations. In this context, reversible event structures provide abstract representations of processes capable of both forward and backward steps in a computation. Since their introduction, event structures have played a crucial role in bridging operational models, traditionally exemplified by Petri nets and process calculi, with denotational ones, i.e., algebraic domains. In this context, we revisit the standard connection between Petri nets and event structures under the lenses of reversibility. Specifically, we introduce a subset of contextual Petri nets, dubbed
reversible causal nets
, that precisely correspond to reversible prime event structures. The distinctive feature of reversible causal nets lies in deriving causality from inhibitor arcs, departing from the conventional dependence on the overlap between the postset and preset of transitions. In this way, we are able to operationally explain the full model of reversible prime event structures.
Multi-Model Style-Aware Diffusion Learning for Semantic Image Synthesis
Authors: Niu Yunfang , Wu Lingxiang , Zhang Yufeng , Zhu Yousong , Zhu Guibo , Wang Jinqiao
Published: August 2024

Semantic image synthesis aims to generate images from given semantic layouts, which is a challenging task that requires training models to capture the relationship between layouts and images. Previous works are usually based on Generative Adversarial Networks (GAN) or autoregressive (AR) models. However, the GAN model's training process is unstable, and the AR model’s performance is seriously affected by the independent image encoder and the unidirectional generation bias. Due to the above limitations, these methods tend to synthesize unrealistic, poorly aligned images and only consider single-style image generation. In this paper, we propose a Multi-model Style-aware Diffusion Learning (MSDL) framework for semantic image synthesis, including a training module and a sampling module. In the training module, a layout-to-image model is introduced to transfer the learned knowledge from a model pretrained with massive weak correlated text-image pairs data, making the training process more efficient. In the sampling module, we designed a map-guidance technique and creatively designed a multi-model style-guidance strategy for creating images in multiple styles, e.g., oil painting, Disney Cartoon, and pixel style. We evaluate our method on Cityscapes, ADE20K, and COCO-Stuff, making visual comparisons and computing with multiple metrics such as FID, LPIPS, etc. Experimental results demonstrate that our model is highly competitive, especially in terms of fidelity and diversity.
MSSA: Multi-Representation Semantics-Augmented Set Abstraction for 3D Object Detection
Authors: Liu Huaijin , Du Jixiang , Zhang Yong , Zhang Hongbo , Zeng Jiandian
Published: August 2024

Accurate recognition and localization of 3D objects is a fundamental research problem in 3D computer vision. Benefiting from transformation-free point cloud processing and flexible receptive fields, point-based methods have become accurate in 3D point cloud modeling, but still fall behind voxel-based competitors in 3D detection. We observe that the set abstraction module, commonly utilized by point-based methods for downsampling points, tends to retain excessive irrelevant background information, thus hindering the effective learning of features for object detection tasks. To address this issue, we propose MSSA, a Multi-representation Semantics-augmented Set Abstraction for 3D object detection. Specifically, we first design a backbone network to encode different representation features of point clouds, which extracts point-wise features through PointNet to preserve fine-grained geometric structure features, and adopts VoxelNet to extract voxel features and BEV features to enhance the semantic features of key points. Second, to efficiently fuse different representation features of keypoints, we propose a Point feature-guided Voxel feature and BEV feature fusion (PVB-Fusion) module to adaptively fuse multi-representation features and remove noise. At last, a novel Multi-representation Semantic-guided Farthest Point Sampling (MS-FPS) algorithm is designed to help set abstraction modules progressively downsample point clouds, thereby improving instance recall and detection performance with more important foreground points. We evaluate MSSA on the widely used KITTI dataset and the more challenging nuScenes dataset. Experimental results show that compared to PointRCNN, our method improves the AP of “moderate” level for three classes of objects by 7.02%, 6.76%, and 5.44%, respectively. Compared to the advanced point-voxel-based method PV-RCNN, our method improves the AP of “moderate” level by 1.23%, 2.84%, and 0.55% for the three classes, respectively.
Frequency Response of the Diffuse-Charge Dynamics in Electrochemical Systems with a Graphene Electrode
Authors: Yavarian Mahdi , Melnik Roderick , Mišković Z. L.
Published: August 2024

We investigate the frequency response of diffuse-charge dynamics related to a 1:1 symmetric electrolyte containing a graphene electrode by solving the governing Poisson-Nernst-Planck equations subjected to appropriate boundary conditions in the asymptotic limit ε = λ

D
/H → 0, where λ

D
is the Debye screening length and H is the half-thickness of the electrolyte. Using the method of matched asymptotic expansion, we first solve the leading order non-linear problem for equilibrium state at a nonzero applied DC voltage in the presence of Stern layer(s). Then, we extend the leading order asymptotic analysis to derive an analytic expression for the impedance of the graphene-based electrochemical cell when a small AC voltage perturbation is added to the applied DC voltage. Finally, we use a suitable scaling of the impedance parameters to expose the impacts of the ion concentration and the DC bias voltage on the frequency response for possible applications involving the graphene-electrolyte interface.
Unveiling the Interplay of Structural and Electrochemical Degradation of LiNi0.85Mn0.05Co0.05O2 Cathode Material for Li-Ion Batteries
Authors: Goldbach D. , Gluch J. , Gaus M. , Graf T. , Käbitz S. , Krewer U.
Published: August 2024

Nickel-rich layered oxides, crucial for high-energy-density Li-ion batteries, face challenges in cycle life due to intricate chemo-mechanical degradation. This study pioneers a comprehensive approach, integrating nano X-ray computed tomography and advanced electrochemical methods, to untangle the interplay of degradation mechanisms in complex composite electrodes. The evolution of cracking in Nickel-rich cathodes is meticulously quantified under diverse operating conditions. Surprisingly, our findings unveil that, contrary to conventional wisdom, crack formation is not the primary driver of capacity decay in Nickel-rich cathodes. Instead, the limiting factor emerges from the interplay between cycling-induced cracks and a progressively growing resistivity. Cracks, amplifying electrochemically active surfaces, foster side reactions, elevating resistance, and consequently diminishing capacity and current rate capability. This novel insight redirects attention to the dynamic resistivity growth, pinpointing operating conditions as a critical contributor. This work not only advances our understanding of Nickel-rich cathode degradation but also provides a framework for strategic mitigation strategies.
Review—MOS-Based Benzene, Toluene, Ethylbenzene, and Xylene Gas Sensors
Authors: Sharma Neha , Shekhawat Pushpendra Singh , Nakate Umesh T. , Choudhury Sandip Paul
Published: August 2024

Gas sensing technology has evolved over the last 50 years but there has been a lacuna to understand the sensing mechanism. The understanding becomes even more complicated when gases like Benzene, Toluene, Ethyl Benzene, and Xylene (BTEX) are sensed using conventional gas sensors. BTEX gases have inert chemical behaviour, making it difficult to detect such gases using the widely explored metal-oxide-semiconductors (MOS). BTEX gases are generated in petroleum and other industries and hence their detection at low ppm is a necessity as it is carcinogenic in nature and possesses a threat to human health. For efficient sensing of such gases, a variety of materials including quantum dots, nano-flakes of different geometry, carbon-based materials etc. are being explored. This review focuses on the different materials and their properties which makes them efficient sensors to detect BTEX gases. Polymer-based materials are out of the scope of this review article as the topic deserves a separate article because of its vastness. In future scope, probable materials which can prove to be a good BTEX gas sensor are discussed.
An Electrochemical Study Using Experimental Design for the Determination of Prucalopride Succinate via the Optimized Ion Selective Electrode
Authors: Hadad Ghada M. , Abdelsalam Randa A. , Ahmed Bassant S. , Hamdy Abdallah M.
Published: August 2024

Prucalopride succinate (PCP) was determined by potentiometry using an ion-selective electrode to obtain the most optimum ion-selective electrode. A screening study was carried out to determine the best membrane components, in which a PCP selective electrode was investigated with dioctyl phthalate as a plasticizer in a polymeric polyvinyl chloride polymeric matrix. Sensors were fabricated using phosphotungstic acid as an exchanger and β-cyclodextrin as an ionophore. Then, an optimization process was carried out, which involved the detection of significant factors affecting membrane response variables followed by the establishment of Box Behnken design in which levels of the selected factors, namely, percent of matrix, a ratio of plasticizer: polyvinyl chloride, and Log of soaking concentration were carefully selected (three levels for each factor). The optimized membrane was examined by measuring the slope, LOQ, linearity of PCP, and response time as response variables. Linear responses of PCP within the concentration ranges of 9.99 × 10−8−3.39 × 10−5 mol l−1 were obtained, and a slope of 61.591 ± 1.112 was observed. The selectivity coefficients of the developed sensors indicated excellent selectivity for PCP. The proposed sensor displayed useful analytical characteristics for the sensitive and selective determination of PCP.
Designing A Selective Electrochemical Nanosensor Based on Molecularly Imprinted Polymer for Detection of Pirfenidone
Authors: Selcuk Ozge , Uslu Bengi
Published: August 2024

In this study, an electrochemical determination of pirfenidone(PIR), an antifibrotic drug, was developed for the first time with a bare glassy carbon electrode(GCE) and a molecularly imprinted polymer(MIP)-based nanosensor. A molecularly imprinted polymer(MIP) incorporating o-phenylenediamine(o-PD), chitosan(CHIT), ionic liquid(IL), and diamond nanoparticles(DiaNPs) was utilized to modify a glassy carbon electrode(GCE), developing a stable and selective electrochemical nanosensor(MIP/CHIT@IL@DiaNPs/GCE) for PIR detection. The designed MIP/CHIT@IL@DiaNPs/GCE was characterized by electrochemical impedance spectroscopy(EIS), cyclic voltammetry(CV), scanning electron microscopy(SEM) and atomic force microscopy(AFM). The [Fe(CN)6]3−/4− redox couple was used as a probe to characterize the nanosensor by using voltammetric methods. Under optimum conditions, the bare GCE showed a linear response in the concentration range of 9.90 μM to 260.0 μM for the determination of PIR, and the detection limit was calculated to be 2.48 μM. While, the MIP/CHIT@IL@DiaNPs/GCE nanosensor exhibited good sensitivity with a linear range of 30.0 pM−1.0 nM and a detection limit of 9.29 pM. To demonstrate the applicability of the developed nanosensors to real samples, the determination was made from Pirfect® tablet and human serum.
Application of the Point Defect Model to the Oscillatory Anodic Oxidation of Illuminated n-Type Silicon in the Presence of Fluoride Ions Using Electrochemical Impedance Spectroscopy
Authors: Duportal Malo , Tosolini Anton , Wiehl Juliane C. , Murakami Yukiteru , Krischer Katharina
Published: August 2024

This work aims to provide insight into the oscillations occurring during the anodic electrooxidation of Si in fluoride-containing electrolytes using electrochemical impedance spectroscopy (EIS). The EIS measurements were conducted within less than a tenth of the oscillation periods allowing changes in the electrical properties of the silicon/oxide/electrolyte interfaces to be monitored during an oscillatory cycle. Application of the power law model to the experimental data revealed a significant change in resistivity at the oxide/semiconductor interface while the properties at the oxide/electrolyte interface remained constant and the oxide layer varied only by about 1 nm around an average value of about 4.9 nm. The application of the point defect model to the semiconductor/oxide/F−-containing electrolyte interface suggests that the oscillations are linked to the time delay between the production of oxygen vacancies at the Si/oxide interface and their consumption at the oxide/electrolyte interface.
Electrochemical Synthesis of Urea from Carbon Dioxide and Nitrite at Cobalt Phthalocyanine-Ion Liquid Electrodes
Authors: Bornak Mona , Akther Jasmeen , Song Chaojie , Fatih Khalid , Ali Ahmed H. , Stockmann T. Jane , Pickup Peter G.
Published: August 2024

Electrochemical coreduction of carbon dioxide and nitrogen oxyanion/oxide pollutants are attractive processes for simultaneous environmental remediation and sustainable production of urea. The development of suitable technology requires catalysts and electrodes that provide higher efficiencies by decreasing the overpotential required and increasing the faradaic efficiency. Electrode design is a key element in this process through which the environment of the catalyst can be manipulated to optimize activity and selectivity. Here, ionic liquids have been used to control the coreduction of carbon dioxide and nitrite at a cobalt phthalocyanine catalyst. Increasing the hydrophobicity of the catalyst layer with a mixture of 1-butylpyridinium hexafluorophosphate and trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)imide was found to increase the faradaic efficiency for urea formation to 27% at the lowest overpotential (−0.064 V vs RHE), from 3% for a Nafion binder. Modulation of the electronic structure, arrangement (aggregation vs adsorption on the carbon support) and/or mobility (via solubilization) of the CoPc catalyst appear to play a role in determining the rate and faradaic efficiency of urea production. Combining the CoPc catalyst with a carbon supported Cu cocatalyst increased the rate of urea production by 195% at –0.064 V.
Roles of Interdigitated Electrode Geometry in Non-Faradaic Impedimetric Biosensors
Authors: Assaifan Abdulaziz K. , Almansour Rawan A. , Alessa Jana A. , Alhudaithy Soliman , Fakhouri Abdulaziz S. , Alsaleh Ahmad A.
Published: August 2024

In this work, we investigate the effect of interdigitated electrode fingers width and gap on the performance of biosensors. Two different configurations of interdigitated electrodes were utilized; one consists of 50 μm wide fingers with a gap of 50 μm, and the other consists of 100 μm wide fingers with a 100 μm gap. First, the active surface area of both interdigitated electrodes was investigated. Then, the surface electronic parameters were investigated using faradaic and non-faradaic electrochemical impedance spectroscopy modes. Both interdigitated electrodes were then functionalized with LDL-antibodies through a standard chemical functionalization route and were utilized for the detection of LDL-antigen of cholesterol. The biosensor with 50 μm width and gap demonstrated better sensitivity and limit of detection of 6.08 nF/log(ng/ml) and 40 pg ml−1, respectively. Biosensors with 100 μm finger width and gap sensitivity and detection limit are 5.16 nF/log(ng/ml) and 300 pg ml−1, respectively. The enhanced sensitivity and limit of detection for the first biosensor is due to the increased surface area, enhanced electric field, and less diffusion of ions onto the biosensor surface. The study reported here suggests room for improving the geometry of many interdigitated electrodes for enhanced non-faradaic biosensing performances.
Al-doped ZnO Nanostars for Electrochemical miRNA-21 Biosensors
Authors: Sun Bo , Tang Huize , Gao Guosheng , Qian Yujia , Shen Qiang , Liang Lingyan , Cao Hongtao
Published: August 2024

The accurate and cost-effective detection of miRNAs, which are strongly associated with numerous diseases and disorders, poses significant technical challenges due to their small size, low concentration, and sequence similarity. In this study, we address these challenges by developing an Al-doped ZnO nanostar working electrode for electrochemical biosensors targeting miRNA-21 detection, employing a simple hydrothermal growth method. The introduction of Al doping modifies the nanostructure of the nanostars, enhancing their affinity for DNA probing and enabling tunability of the working electrode’s conductivity. This enhancement is achieved through the formation of a high-density, uniformly distributed nanostar structure, leading to improved electron transfer rates and increased surface area for miRNA binding. The nanostar biosensors, optimized with the appropriate Al content, exhibit satisfactory analytical properties, including a wide linear range from 1 pM to 10 nM, a low detection limit of 3.98 pM, reproducibility, and excellent selectivity for miRNA assays. Notably, real-time detection is achievable, demonstrating promising potential for point-of-care testing.
Nursing Students’ Personality Traits and Their Attitude toward Artificial Intelligence: A Multicenter Cross‐Sectional Study
Authors: Salem Gihan Mohamed Mohamed , El-Gazar Heba Emad , Mahdy Abeer Yahia , Alharbi Talal Ali F. , Zoromba Mohamed Ali
Published: August 2024

Background. Despite the importance of studying factors contributing to nursing students’ attitudes toward artificial intelligence, yet according to our knowledge, no study has addressed the relationship between personality traits and the attitude of nursing students toward artificial intelligence. Aim. This study aimed to unveil whether nursing students’ personality traits are related to their attitude toward AI. Methods. This multicenter cross‐sectional study included 218 nursing students from three governmental universities across various regions of the Kingdom of Saudi Arabia. Data were gathered online, utilizing the Big Five Inventory, the General Attitudes toward Artificial Intelligence Scale, and a demographic questionnaire. Descriptive statistics, Pearson’s correlation, and regression analysis were employed. The research complied with the STROBE checklist. Results. Findings indicated that nursing students with a high score in the openness trait displayed positive attitudes toward artificial intelligence. Conversely, those who scored high in neuroticism and agreeableness exhibited fewer positive attitudes toward artificial intelligence and more negative attitudes toward artificial intelligence. Additionally, nursing students who ranked high in conscientiousness showed a negative attitude toward artificial intelligence. Conclusion. Except for extraversion, personality traits appear to predict attitudes toward artificial intelligence. Implications for Nursing Management. The current study provides a foundation for understanding how generative AI can be integrated into nursing education and practice in a manner that is both effective and considerate of the diverse psychological profiles of students.
Post‐Settlement Support Impact on the Welfare of Emerging Farmers’ Households in Limpopo Province, South Africa
Authors: Maesela Lesedi M. , Belete Abenet , Senyolo Grany M.
Published: August 2024

Several policies and programs have been implemented to improve the welfare of households in rural South Africa through commercialization. Post‐settlement support (PSS) refers to any kind of assistance that emerging farmers received from the government following land restoration. This paper examines the impact of PSS on the welfare of emerging farmers under the land restitution program in Limpopo Province, South Africa. The study involved a simple random sampling method to select 200 emerging farmers. The primary data were analyzed using descriptive statistics and the endogenous switching regression model. Descriptive statistics revealed that ~71% of land restitution beneficiaries received PSS after acquiring their land. The result of the selection model showed that farm characteristics (farming experience, location, and soil quality), and institutional factors (transportation and market participation) influenced the receiving of the PSS by the farmers. The outcome model showed that PSS positively influences household welfare. In addition, demographic factors (gender and household size), farm characteristics (soil quality), and institutional factors (market participation and farmer association membership) influenced the consumption expenditure per capita, hence affecting household welfare. The government should continue supporting female beneficiaries with access to market, training, and extension services for linkages with farmers’ associations as the PSS increases the household welfare.
Nasal Anthropometry: An Assessment Among the Akan and Ewe Ethnic Groups in Ghana
Authors: Robertson Juliet , Abaidoo Chrissie Stansie , Okwan Daniel Kobina , Tetteh Joshua , Adjei-Antwi Collins , Bempah Samuel , Ampofo Michael
Published: August 2024

The distribution of nasal types has been reported to be influenced by climatic adaptation as the nose is involved in conditioning inhaled air. Previous studies have reported differential nasal types and dimensions among varying populations which is very beneficial in planning for rhinoplasty and in forensic identification. However, there is inadequate data on nasal types and dimensions of the various ethnic groups in the Ghanaian population. Since it is inappropriate to apply nasal dimensions of one ethnic group to another, the current study sought to assess the nasal types and dimensions of Akans and Ewes in the Ghanaian population. Nasal height, nasal length, nasal tip protrusion, morphological nose width, and anatomical nose width were measured from 202 participants (116 Akans and 86 Ewes) aged 18–27 years belonging to the Akan and Ewe ethnic groups. Nasal index was calculated, and the frequencies of the nasal types among the two ethnic groups were determined. Ewe significantly had greater nasal length and nasal tip protrusion than the Akans. For both ethnic groups, sexual dimorphism was observed in morphological nose width and anatomical nose width, with males having greater values than females. The platyrrhine (broad nose) nasal type was predominant among the Akan and Ewe ethnic groups. The average nasal dimensions of the Akan and Ewe ethnic groups for the Ghanaian population have been reported in the present study, which will be useful in rhinoplasty intended for individuals belonging to these ethnic groups and in identification.
Integrative Modeling of Signaling Network Dynamics Identifies Cell Type–Selective Therapeutic Strategies for FGFR4-Driven Cancers
Authors: Shin Sung-Young , Chew Nicole J. , Ghomlaghi Milad , Chüeh Anderly C. , Jeong Yunhui , Nguyen Lan K. , Daly Roger J.
Published: August 2024

Oncogenic FGFR4 signaling represents a potential therapeutic target in various cancer types, including triple-negative breast cancer and hepatocellular carcinoma. However, resistance to FGFR4 single-agent therapy remains a major challenge, emphasizing the need for effective combinatorial treatments. Our study sought to develop a comprehensive computational model of FGFR4 signaling and to provide network-level insights into resistance mechanisms driven by signaling dynamics. An integrated approach, combining computational network modeling with experimental validation, uncovered potent AKT reactivation following FGFR4 targeting in triple-negative breast cancer cells. Analyzing the effects of cotargeting specific network nodes by systematically simulating the model predicted synergy of cotargeting FGFR4 and AKT or specific ErbB kinases, which was subsequently confirmed through experimental validation; however, cotargeting FGFR4 and PI3K was not synergistic. Protein expression data from hundreds of cancer cell lines was incorporated to adapt the model to diverse cellular contexts. This revealed that although AKT rebound was common, it was not a general phenomenon. For example, ERK reactivation occurred in certain cell types, including an FGFR4-driven hepatocellular carcinoma cell line, in which there is a synergistic effect of cotargeting FGFR4 and MEK but not AKT. In summary, this study offers key insights into drug-induced network remodeling and the role of protein expression heterogeneity in targeted therapy responses. These findings underscore the utility of computational network modeling for designing cell type–selective combination therapies and enhancing precision cancer treatment.

 Significance: Computational predictive modeling of signaling networks can decipher mechanisms of cancer cell resistance to targeted therapies and enable identification of more effective cancer type–specific combination treatment strategies.
Targeting Catechol-O-Methyltransferase Induces Mitochondrial Dysfunction and Enhances the Efficacy of Radiotherapy in Glioma
Authors: Jiao Meng , Pirozzi Christopher J. , Yu Chen , Bao Xuhui , Hu Mengjie , Pan Dong , Littleton Sejiro , Reynolds Nathan , Saban Daniel R. , Li Fang , Li Chuan-Yuan
Published: August 2024

Radiotherapy (RT) is commonly used to try to eliminate any remaining tumor cells following surgical resection of glioma. However, tumor recurrence is prevalent, highlighting the unmet medical need to develop therapeutic strategies to enhance the efficacy of RT in glioma. Focusing on the radiosensitizing potential of the currently approved drugs known to cross the blood-brain barrier can facilitate rapid clinical translation. Here, we assessed the role of catechol-O-methyltransferase (COMT), a key enzyme to degrade catecholamines and a drug target for Parkinson’s disease, in glioma treatment. Analysis of The Cancer Genome Atlas data showed significantly higher COMT expression levels in both low-grade glioma and glioblastoma compared to normal brain tissues. Inhibition of COMT by genetic knockout or FDA-approved COMT inhibitors significantly sensitized glioma cells to RT in vitro and in vivo. Mechanistically, COMT inhibition in glioma cells led to mitochondria dysfunction and increased mitochondrial RNA release into the cytoplasm, activating the cellular antiviral double-stranded RNA sensing pathway and type I interferon (IFN) response. Elevated type I IFNs stimulated the phagocytic capacity of microglial cells, enhancing RT efficacy. Given the long-established safety record of the COMT inhibitors, these findings provide a solid rationale to evaluate them in combination with RT in patients with glioma.

Significance: Inhibition of catechol-O-methyltransferase, a well-established drug target in Parkinson’s disease, interferes with mitochondrial electron transport and induces mitochondrial double-stranded RNA leakage, activating type I interferon signaling and sensitizing glioma to radiotherapy.
Blood Leukocyte DNA Methylation Markers of Periodontal Disease and Risk of Lung Cancer in a Case–Control Study Nested in the CLUE II Cohort
Authors: Mulvaney Rachel , Pan Yongyi , Zhao Naisi , Teles Flavia , Lu Jiayun , Platz Elizabeth A. , Kelsey Karl T. , Michaud Dominique S.
Published: August 2024

Background:

Periodontal disease and DNA methylation markers have separately been associated with lung cancer risk. Examining methylation levels at genomic regions previously linked to periodontal disease may provide insights on the link between periodontal disease and lung cancer.

Methods:

In a nested case–control study drawn from the CLUE II cohort, we measured DNA methylation levels in 208 lung cancer cases and 208 controls. We examined the association between 37 DNA-methylated 5′—C—phosphate—G—3′ (CpG) sites at three genomic regions, homeobox 4 (HOXA4), zinc finger protein (ZFP57), and a long noncoding RNA gene located in Chr10 (ENSG00000231601), and lung cancer risk.

Results:

Statistically significant associations with lung cancer risk were observed for all 14 CpG sites from HOXA4 (OR ranging 1.41–1.62 for 1 SD increase in the DNA methylation level, especially within 15 years) and 1 CpG site on gene ENSG00000231601 (OR = 1.34 for 1 SD increase in the DNA methylation level). Although CpG sites on gene ZFP57 were not associated with lung cancer risk overall, statistically significant inverse associations were noted for six CpG sites when restricting follow-up to 15 years (OR = 0.73–0.77 for 1 SD increase in the DNA methylation level).

Conclusions:

Key methylation levels associated with periodontal disease are also associated with lung cancer risk. For both HOXA4 and ZFP57, the associations were stronger within 15 years of follow-up, which suggest that, if causal, the impact of methylation is acting late in the natural history of lung cancer.

Impact:

Identifying biological pathways that link periodontal disease and lung cancer could provide new opportunities for lung cancer detection and prevention.
FDA Approval Summary: Asciminib for Ph+ CML in Chronic Phase Treated with Two or More Tyrosine Kinase Inhibitors and for the T315I Mutation
Authors: Pamuk Gulsum E. , Chow Edwin C.Y. , Ionan Alexei C. , Chen Haiyan , Lee Shwu-Luan , Hsu Vicky , Grimstein Manuela , Zheng Nan , Sun Jielin , Charlab Rosane , Gehrke Brenda J. , Vallejo Jonathon , Ehrlich Lori A. , de Claro R. Angelo , Theoret Marc R.
Published: August 2024

On October 29, 2021, FDA granted accelerated approval to asciminib (SCEMBLIX; Novartis), a tyrosine kinase inhibitor (TKI), for the treatment of adult patients with Philadelphia chromosome positive chronic myeloid leukemia (Ph+ CML) in chronic phase (CP), previously treated with two or more TKIs, and granted traditional approval to asciminib for adult patients with Ph+ CML in CP with the T315I mutation. The first indication was approved based on major molecular response (MMR) at 24 weeks in the ASCEMBL study, a randomized trial comparing asciminib with bosutinib in patients who had failed two or more TKIs. This indication was ultimately granted traditional approval on October 12, 2022, based on safety data and MMR rate at 96 weeks of 38% [95% confidence interval (CI), 30–46] in the asciminib arm versus 16% (95% CI, 8–26) in the bosutinib arm (P value: 0.001). The second indication was approved based on MMR rate by 96 weeks of 49% (95% CI, 34–64) in the single-arm CABL001X2101 study. The most common (≥20%) adverse reactions included upper respiratory tract infections, musculoskeletal pain, headache, fatigue, nausea, rash, and diarrhea. The most common (≥20%) laboratory abnormalities were thrombocytopenia, neutropenia, anemia, lymphopenia, hypertriglyceridemia, hyperuricemia, and increases in creatine kinase, alanine aminotransferase, aspartate aminotransferase, lipase, and amylase. This manuscript describes the basis for approval of these indications.
Supplementary Figure S2 from MYC Family Amplification Dictates Sensitivity to BET Bromodomain Protein Inhibitor Mivebresib (ABBV075) in Small-Cell Lung Cancer
Authors: Plotnik Joshua P. , Zha Zheng , Feng Weiguo , Lee Irene , Riehm Jacob , McClure Ryan A. , Sandoval Stephanie , Uziel Tamar , Murphy Erin , Lu Xin , Lam Lloyd T.
Published: August 2024

Supplementary Figure S2
Supplementary Figure S1 from MYC Family Amplification Dictates Sensitivity to BET Bromodomain Protein Inhibitor Mivebresib (ABBV075) in Small-Cell Lung Cancer
Authors: Plotnik Joshua P. , Zha Zheng , Feng Weiguo , Lee Irene , Riehm Jacob , McClure Ryan A. , Sandoval Stephanie , Uziel Tamar , Murphy Erin , Lu Xin , Lam Lloyd T.
Published: August 2024

Supplementary Figure S1
Table S5 from DROSHA Regulates Mesenchymal Gene Expression in Wilms Tumor
Authors: Tiburcio Patricia D.B. , Desai Kavita , Kim Jiwoong , Zhou Qinbo , Guo Lei , Xiao Xue , Zhou Li , Yuksel Aysen , Catchpoole Daniel R. , Amatruda James F. , Xu Lin , Chen Kenneth S.
Published: August 2024

Fusions
Supplementary Figure legends and Table names from DROSHA Regulates Mesenchymal Gene Expression in Wilms Tumor
Authors: Tiburcio Patricia D.B. , Desai Kavita , Kim Jiwoong , Zhou Qinbo , Guo Lei , Xiao Xue , Zhou Li , Yuksel Aysen , Catchpoole Daniel R. , Amatruda James F. , Xu Lin , Chen Kenneth S.
Published: August 2024

Supplementary Figure legends and Table names
Supplementary Data from Pediatric Chordoma: A Tale of Two Genomes
Authors: O’Halloran Katrina , Hakimjavadi Hesamedin , Bootwalla Moiz , Ostrow Dejerianne , Kerawala Rhea , Cotter Jennifer A. , Yellapantula Venkata , Kaneva Kristiyana , Wadhwani Nitin R. , Treece Amy , Foreman Nicholas K. , Alexandrescu Sanda , Velazquez Vega Jose , Biegel Jaclyn A. , Gai Xiaowu
Published: August 2024

Rare mtDNA variants of adult chordomas
Supplementary figure 6 from Kinesin Facilitates Phenotypic Targeting of Therapeutic Resistance in Advanced Prostate Cancer
Authors: Archer Maddison , Begemann Diane , Gonzalez-Kozlova Edgar , Nepali Prerna R. , Labanca Estefania , Shepherd Peter , Dogra Navneet , Navone Nora , Kyprianou Natasha
Published: August 2024

RNAseq validation by RT-PCR
Supplementary figure 16 from Kinesin Facilitates Phenotypic Targeting of Therapeutic Resistance in Advanced Prostate Cancer
Authors: Archer Maddison , Begemann Diane , Gonzalez-Kozlova Edgar , Nepali Prerna R. , Labanca Estefania , Shepherd Peter , Dogra Navneet , Navone Nora , Kyprianou Natasha
Published: August 2024

Gene expression analysis
Supplementary figure 1 from Kinesin Facilitates Phenotypic Targeting of Therapeutic Resistance in Advanced Prostate Cancer
Authors: Archer Maddison , Begemann Diane , Gonzalez-Kozlova Edgar , Nepali Prerna R. , Labanca Estefania , Shepherd Peter , Dogra Navneet , Navone Nora , Kyprianou Natasha
Published: August 2024

Migration assay images
Data from Pediatric Chordoma: A Tale of Two Genomes
Authors: O’Halloran Katrina , Hakimjavadi Hesamedin , Bootwalla Moiz , Ostrow Dejerianne , Kerawala Rhea , Cotter Jennifer A. , Yellapantula Venkata , Kaneva Kristiyana , Wadhwani Nitin R. , Treece Amy , Foreman Nicholas K. , Alexandrescu Sanda , Velazquez Vega Jose , Biegel Jaclyn A. , Gai Xiaowu
Published: August 2024

Abstract
Little is known about the genomic alterations in chordoma, with the exception of loss of SMARCB1, a core member of the SWI/SNF complex, in poorly differentiated chordomas. A TBXT duplication and rs2305089 polymorphism, located at 6q27, are known genetic susceptibility loci. A comprehensive genomic analysis of the nuclear and mitochondrial genomes in pediatric chordoma has not yet been reported. In this study, we performed WES and mtDNA genome sequencing on 29 chordomas from 23 pediatric patients. Findings were compared with that from whole-genome sequencing datasets of 80 adult patients with skull base chordoma. In the pediatric chordoma cohort, 81% of the somatic mtDNA mutations were observed in NADH complex genes, which is significantly enriched compared with the rest of the mtDNA genes (P = 0.001). In adult chordomas, mtDNA mutations were also enriched in the NADH complex genes (P < 0.0001). Furthermore, a progressive increase in heteroplasmy of nonsynonymous mtDNA mutations was noted in patients with multiple tumors (P = 0.0007). In the nuclear genome, rare likely germline in-frame indels in ARID1B, a member of the SWI/SNF complex located at 6q25.3, were observed in five pediatric patients (22%) and four patients in the adult cohort (5%). The frequency of rare ARID1B indels in the pediatric cohort is significantly higher than that in the adult cohort (P = 0.0236, Fisher’s exact test), but they were both significantly higher than that in the ethnicity-matched populations (P < 5.9e−07 and P < 0.0001174, respectively).

Implications: germline ARID1B indels and mtDNA aberrations seem important for chordoma genesis, especially in pediatric chordoma.
Table S3 from Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancer
Authors: Matusiak Magdalena , Hickey John W. , van IJzendoorn David G.P. , Lu Guolan , Kidziński Lukasz , Zhu Shirley , Colburg Deana R.C. , Luca Bogdan , Phillips Darci J. , Brubaker Sky W. , Charville Gregory W. , Shen Jeanne , Loh Kyle M. , Okwan-Duodu Derick K. , Nolan Garry P. , Newman Aaron M. , West Robert B. , van de Rijn Matt
Published: August 2024

Supplementary Table 3. CODEX imiging cycles record
Figure S3 from Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancer
Authors: Matusiak Magdalena , Hickey John W. , van IJzendoorn David G.P. , Lu Guolan , Kidziński Lukasz , Zhu Shirley , Colburg Deana R.C. , Luca Bogdan , Phillips Darci J. , Brubaker Sky W. , Charville Gregory W. , Shen Jeanne , Loh Kyle M. , Okwan-Duodu Derick K. , Nolan Garry P. , Newman Aaron M. , West Robert B. , van de Rijn Matt
Published: August 2024

Thus Figure shows CD274 gene scRNAseq expression across different cell types and datasets.
Supplementary Table 12 from Activating Point Mutations in the MET Kinase Domain Represent a Unique Molecular Subset of Lung Cancer and Other Malignancies Targetable with MET Inhibitors
Authors: Pecci Federica , Nakazawa Seshiru , Ricciuti Biagio , Harada Guilherme , Lee Jessica K. , Alessi Joao V. , Barrichello Adriana , Vaz Victor R. , Lamberti Giuseppe , Di Federico Alessandro , Gandhi Malini M. , Gazgalis Dimitris , Feng William W. , Jiang Jie , Baldacci Simon , Locquet Marie-Anaïs , Gottlieb Felix H. , Chen Monica F. , Lee Elinton , Haradon Danielle , Smokovich Anna , Voligny Emma , Nguyen Tom , Goel Vikas K. , Zimmerman Zachary , Atwal Sumandeep , Wang Xinan , Bahcall Magda , Heist Rebecca S. , Iqbal Sumaiya , Gandhi Nishant , Elliott Andrew , Vanderwalde Ari M. , Ma Patrick C. , Halmos Balazs , Liu Stephen V. , Che Jianwei , Schrock Alexa B. , Drilon Alexander , Jänne Pasi A. , Awad Mark M.
Published: August 2024

Characteristics of 129 NSCLC cases harboring oncogenic / likely oncogenic MET TKD mutations from cohort #2.
Supplementary Figure 9 from Activating Point Mutations in the MET Kinase Domain Represent a Unique Molecular Subset of Lung Cancer and Other Malignancies Targetable with MET Inhibitors
Authors: Pecci Federica , Nakazawa Seshiru , Ricciuti Biagio , Harada Guilherme , Lee Jessica K. , Alessi Joao V. , Barrichello Adriana , Vaz Victor R. , Lamberti Giuseppe , Di Federico Alessandro , Gandhi Malini M. , Gazgalis Dimitris , Feng William W. , Jiang Jie , Baldacci Simon , Locquet Marie-Anaïs , Gottlieb Felix H. , Chen Monica F. , Lee Elinton , Haradon Danielle , Smokovich Anna , Voligny Emma , Nguyen Tom , Goel Vikas K. , Zimmerman Zachary , Atwal Sumandeep , Wang Xinan , Bahcall Magda , Heist Rebecca S. , Iqbal Sumaiya , Gandhi Nishant , Elliott Andrew , Vanderwalde Ari M. , Ma Patrick C. , Halmos Balazs , Liu Stephen V. , Che Jianwei , Schrock Alexa B. , Drilon Alexander , Jänne Pasi A. , Awad Mark M.
Published: August 2024

Genomic characterization of NSCLC cases harboring oncogenic / likely oncogenic MET TKD mutations in cohort #2. (A) Oncoprint summarizing the genomic profile and (B) the TMB value of the 78 NSCLC cases with oncogenic / likely oncogenic MET TKD mutations without other concurrent driver alterations according to NCCN guidelines. (C) Comparison of the genomic profile of NSCLC cases with oncogenic / likely oncogenic MET TKD mutations (N=78) and METex14-altered NSCLC (N=2036)
Supplementary Figure 20 from Activating Point Mutations in the MET Kinase Domain Represent a Unique Molecular Subset of Lung Cancer and Other Malignancies Targetable with MET Inhibitors
Authors: Pecci Federica , Nakazawa Seshiru , Ricciuti Biagio , Harada Guilherme , Lee Jessica K. , Alessi Joao V. , Barrichello Adriana , Vaz Victor R. , Lamberti Giuseppe , Di Federico Alessandro , Gandhi Malini M. , Gazgalis Dimitris , Feng William W. , Jiang Jie , Baldacci Simon , Locquet Marie-Anaïs , Gottlieb Felix H. , Chen Monica F. , Lee Elinton , Haradon Danielle , Smokovich Anna , Voligny Emma , Nguyen Tom , Goel Vikas K. , Zimmerman Zachary , Atwal Sumandeep , Wang Xinan , Bahcall Magda , Heist Rebecca S. , Iqbal Sumaiya , Gandhi Nishant , Elliott Andrew , Vanderwalde Ari M. , Ma Patrick C. , Halmos Balazs , Liu Stephen V. , Che Jianwei , Schrock Alexa B. , Drilon Alexander , Jänne Pasi A. , Awad Mark M.
Published: August 2024

Equilibration of interactions that drives ATP affinity in the presence MET R1170Q mutant. (A) Representative structure of ATP bound MET R1170Q with the regions of interest highlighted [hinge site (green), and mutation site (blue)]. (B) Mutation at position 1170 facilitates the formation of a hydrogen bonding network. (C) Interatomic distances for non solvent mediated hydrogen bonding.
Supplementary Figure 18 from Activating Point Mutations in the MET Kinase Domain Represent a Unique Molecular Subset of Lung Cancer and Other Malignancies Targetable with MET Inhibitors
Authors: Pecci Federica , Nakazawa Seshiru , Ricciuti Biagio , Harada Guilherme , Lee Jessica K. , Alessi Joao V. , Barrichello Adriana , Vaz Victor R. , Lamberti Giuseppe , Di Federico Alessandro , Gandhi Malini M. , Gazgalis Dimitris , Feng William W. , Jiang Jie , Baldacci Simon , Locquet Marie-Anaïs , Gottlieb Felix H. , Chen Monica F. , Lee Elinton , Haradon Danielle , Smokovich Anna , Voligny Emma , Nguyen Tom , Goel Vikas K. , Zimmerman Zachary , Atwal Sumandeep , Wang Xinan , Bahcall Magda , Heist Rebecca S. , Iqbal Sumaiya , Gandhi Nishant , Elliott Andrew , Vanderwalde Ari M. , Ma Patrick C. , Halmos Balazs , Liu Stephen V. , Che Jianwei , Schrock Alexa B. , Drilon Alexander , Jänne Pasi A. , Awad Mark M.
Published: August 2024

Time resolved interaction distances of ATP in the presence of MET WT and MET H1094Y mutant. (A) Hydrogen bonding between P1157 backbone carbonyl and ATP, (B) Inter ring center distances for Y1158-ATP π–π stacking interactions, and (C) Hydrogen bonding between M1159 backbone amine and ATP distances for ATP interactions between MET wild-type (orange) and MET H1094Y (blue) over the last 500 ns of each trajectory.