bluuebunny/crossref_metadata_2025_split huggingface dataset:
Android malware detection via efficient application programming interface call sequences extraction and machine learning classifiers
Authors: Wang Tanjie , Xu Yueshen , Zhao Xinkui , Jiang Zhiping , Li Rui 
Published: December 2022

AbstractMalware detection is an important task for the ecosystem of mobile applications (APPs), especially for the Android ecosystem, and is vital to guarantee the user experience of Android APPs. There have been some exiting methods trying to solve the problem of malware detection, but the methods suffer from several defects, such as high time complexity and mediocre accuracy, which seriously decrease the practicability of existing methods. To solve these problems, in this study, we propose a novel Android malware detection framework, where we contribute an efficient Application Programming Interface (API) call sequences extraction algorithm and an investigation of different types of classifiers. In API call sequences extraction, we propose an algorithm for transforming the function call graph from a multigraph into a directed simple graph, which successfully avoids the unnecessary repetitive path searching. We also propose a pruning search, which further reduces the number of paths to be searched. Our algorithm greatly reduces the time complexity. We generate the transition matrix as classification features and investigate three types of machine learning classifiers to complete the malware detection task. The experiments are performed on real‐world Android Packages (APKs), and the results demonstrate that our method significantly reduces the running time and produces high detection accuracy.
Comparison of Gingival Recession of Mandibular Incisors of Class III Patients Immediately after Compensatory or Surgical Orthodontic Treatment
Authors: Saab Fábio Jorge , de Freitas Daniel Salvatore , Cotrin Paula , Oliveira Renata Cristina , Valarelli Fabricio Pinelli , de Oliveira Ricardo Cesar Gobbi , Salmeron Samira , Pinzan Vercelino Célia Regina Maio , Freitas Karina Maria Salvatore 
Published: December 2022

Abstract
Objective This study aimed to compare gingival recession in mandibular anterior teeth in patients with Class III malocclusion, immediately after compensatory or surgical orthodontic treatment.
Materials and Methods The sample consisted of 40 patients with Class III malocclusion, divided into two groups: Group 1 (compensatory), 20 patients treated with compensatory orthodontics, with a mean initial age of 20.26 years (standard deviation [SD] . = 7.44), mean final age of 23.07 years (SD = 7.32), and mean treatment time of 2.81 years (SD =0.84). Group 2 (surgical), who undergone orthodontic–surgical treatment, with a mean initial age of 23.08 years (SD =5.48), mean final age of 25.43 years (SD =5.12), and mean treatment time of 2.35 years (SD =1.56). Intraoral photographs taken before and after removal of the fixed orthodontic appliance were used to measure the gingival recession, from the cervical of the mandibular incisors from the most cervical point of the gingival margin to the cementoenamel junction. In the initial and final cephalograms, the position of the mandibular incisors was measured. The intergroup comparison was performed using the independent t-test.
Results The results showed that there was no statistically significant difference in the gingival recession at the beginning, at the end, and of changes with treatment between the compensatory and surgical groups.
Conclusion It was concluded that the compensatory and surgical orthodontic treatments for Class III malocclusion showed similar results regarding the gingival recession of the mandibular incisors.
Highlights on Drug and Ion Release and Recharge Capacity of Antimicrobial Removable Prostheses
Authors: Abualsaud Reem , Gad Mohammed M. 
Published: December 2022

AbstractThis article aimed to review the ion and drug release, recharge abilities, and antimicrobial properties of drug/ion-releasing removable prostheses, and to assess their capability in preventing and inhibiting denture stomatitis as well preventing caries and reversing carious lesions. Data was collected from published scientific papers listed in PubMed database from January 1975 to December 2021. English full-text articles, involving clinical or in vitro studies, focusing on removable prostheses and are concerned with drug/ion release and rechargeability as a way to prevent or inhibit denture stomatitis or dental caries were included. The relevant articles reported that ion- or drug-modified polymethylmethacrylate acts as a reservoir for these ions and drugs and is capable of releasing significant amounts with sustained release effect. Recharging of modified resin resulted in greater sustainability of ion and drug release, thus improving the long-term effects of protection against demineralization and reducing the adhesion of Streptococcus mutans and Candida albicans. Modifications of removable prostheses with rechargeable ions and drugs enhance remineralization, hinder demineralization, and reduce microbial adhesion in difficult-to-access areas. Selection of denture base for clinical use will consider its ability to act as an ion/drug reservoir that is capable of release and recharge.
In situ turning defects of exfoliated Ti
3
C
2
MXene into Fenton-like catalytic active sites
Authors: Jiang Yue , Baimanov Didar , Jin Shan , Cheuk-Fung Law Japhet , Zhao Pengcheng , Tang Juanjuan , Peng Jian , Wang Liming , Leung Kelvin Sze-Yin , Sheng Wenchao , Lin Sijie 
Published: December 2022

Controllable in situ formation of nanoclusters with discrete active sites is highly desirable in heterogeneous catalysis. Herein, a titanium oxide–based Fenton-like catalyst is constructed using exfoliated Ti
3
C
2
MXene as a template. Theoretical calculations reveal that a redox reaction between the surface Ti-deficit vacancies of the exfoliated Ti
3
C
2
MXene and H
2
O
2
molecules facilitates the in situ conversion of surface defects into titanium oxide nanoclusters anchoring on amorphous carbon (TiO
x
@C). The presence of mixed-valence Ti
δ+
(δ = 0, 2, 3, and 4) within TiO
x
@C is confirmed by X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) characterizations. The abundant surface defects within TiO
x
@C effectively promote the generation of reactive oxygen species (ROS) leading to superior and stable Fenton-like catalytic degradation of atrazine, a typical agricultural herbicide. Such an in situ construction of Fenton-like catalysts through defect engineering also applies to other MXene family materials, such as V
2
C and Nb
2
C.
Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models
Authors: Teuscher Kevin B. , Chowdhury Somenath , Meyers Kenneth M. , Tian Jianhua , Sai Jiqing , Van Meveren Mayme , South Taylor M. , Sensintaffar John L. , Rietz Tyson A. , Goswami Soumita , Wang Jing , Grieb Brian C. , Lorey Shelly L. , Howard Gregory C. , Liu Qi , Moore William J. , Stott Gordon M. , Tansey William P. , Lee Taekyu , Fesik Stephen W. 
Published: December 2022

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P
7
units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.
A synaptic filtering mechanism in visual threat identification in mouse
Authors: Wu Qiwen , Li E. , Zhang Yifeng 
Published: December 2022

Predator detection is key to animal’s survival. Superior colliculus (SC) orchestrates the animal’s innate defensive responses to visually detected threats, but how threat information is transmitted from the retina to SC is unknown. We discovered that narrow-field neurons in SC were key in this pathway. Using in vivo calcium imaging and optogenetics-assisted interrogation of circuit and synaptic connections, we found that the visual responses of narrow-field neurons were correlated with the animal’s defensive behaviors toward visual stimuli. Activation of these neurons triggered defensive behaviors, and ablation of them impaired the animals’ defensive responses to looming stimuli. They receive monosynaptic inputs from looming-sensitive OFF-transient alpha retinal ganglion cells, and the synaptic transmission has a unique band-pass feature that helps to shape their stimulus selectivity. Our results describe a cell-type specific retinotectal connection for visual threat detection, and a coding mechanism based on synaptic filtering.
Negative but Not Positive Alcohol-Related Consequences Tend to Occur Above the Heavy Episodic Drinking Threshold: A Daily Study of Young Adult Heavy Drinkers
Authors: Merrill Jennifer E , Labhart Florian , Perks Siobhan N 
Published: December 2022

AbstractAimsThis study used event-level data to identify the threshold (i.e. number of standard alcoholic drinks) at which specific negative and positive alcohol-related consequences are likely to occur.MethodsNinety-six college students aged 18–20 reporting weekly heavy episodic drinking (HED) or at least one negative alcohol-related consequence in the past 2 weeks completed ecological momentary assessment over 28 days. Participants reported number of standard drinks consumed and negative (e.g. nausea) and positive (e.g. new friend) alcohol-related consequences on 492 drinking nights. The area under the receiver operating characteristic (AUROC) curve measured the ability of an increasing number of drinks consumed to discriminate between nights with versus without a given consequence. The Youden Index method was used to identify the optimal threshold of drinks for each consequence. Thresholds were examined for each consequence by participants’ biological sex and heavy drinking status.ResultsAcross subgroups, most consequences occurred on nights where participants reported higher consumption levels relative to nights where consequences did not occur. Thresholds for negative consequences ranged between four and nine drinks and thresholds for positive consequences were between three and six drinks.ConclusionsMany negative consequences are likely to occur following the traditional HED threshold of 4+/5+ drinks (females/males), with more severe consequences occurring at slightly higher thresholds. Positive consequences are likely to occur at lower thresholds. There may be an optimal number of drinks that maximize positive while minimizing negative consequences for heavy drinking college students.
Response of seed germination and seedling emergence ofHaloxylon ammodendronto rain frequency and temperature change from four desert ecosystems, Northwest China
Authors: Zhu Yajuan , Jia Zhiqing , Wang Guoje , Ning Husen , Ji Xiaomin , Luo Qinghong 
Published: December 2022

AbstractClimate change will result in variation of rain frequency and amount and warming in arid zones, which is expected to affect seed germination and seedling emergence in desert ecosystems. However, the effects of unpredictable rainfall and increasing temperature on seed germination and seedling emergence of dominant desert plants remain unclear across different deserts, which are important for population regeneration and community succession in desert ecosystems. Seed germination and seedling emergence of Haloxylon ammodendron across four deserts in Northwest China were examined at different rain frequencies with same total amount, and constant and alternating temperatures, to investigate their response to climate change. Rain frequency determined seed germination and seedling emergence of H. ammodendron in the Tengger Desert, Badain Jaran Desert, Gurbantonggut Desert and Mutthar Desert, which was maximal at rain frequency of 10 times per month and decreased with a decrease of rain frequency. Temperature was not a restricting factor for seed germination of H. ammodendron in the Tengger Desert, Badain Jaran Desert and Gurbantonggut Desert, varying from 10 °C to 25 °C and from 20/10 °C to 30/15 °C, respectively. However, the highest temperature of 25 °C and 30/15 °C inhibited seed germination of H. ammodendron in the Mutthar Desert. Thus, H. ammodendron has an opportunistic germination strategy. Under climate change in the future, seed germination and seedling emergence of H. ammodendron would be restricted by the combination of less frequent rainfall and increased temperature in desert ecosystems. The regeneration of the H. ammodendron community should be promoted by irrigation and seedling transplant.
Genes related to cell wall metabolisms are targeted by miRNAs in immature tomato fruits under drought stress
Authors: Asakura Hiroko , Tanaka Mayui , Tamura Tomoko , Saito Yoshikazu , Yamakawa Takashi , Abe Keiko , Asakura Tomiko 
Published: December 2022

ABSTRACTThe metabolism of tomato fruits changes when plants experience drought stress. In this study, we investigated changes in microRNA (miRNA) abundance and detected 32 miRNAs whose expression changes in fruit. The candidate target genes for each miRNA were predicted from the differentially expressed genes identified by transcriptome analysis at the same fruit maturation stage. The predicted targeted genes were related to cell wall metabolisms, response to pathogens, and plant hormones. Among these, we focused on cell wall metabolism-related genes and performed a dual luciferase assay to assess the targeting of their mRNAs by their predicted miRNA. As a result, sly-miR10532 and sly-miR7981e suppress the expression of mRNAs of galacturonosyltransferase-10 like encoding the main enzyme of pectin biosynthesis, while sly-miR171b-5p targets β-1,3-glucosidase mRNAs involved in glucan degradation. These results will allow the systematic characterization of miRNA and their target genes in the tomato fruit under drought stress conditions.
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference
Authors: Li Huiyu , Shen Chen , Wang Gongji , Sun Qinru , Yu Kai , Li Zefeng , Liang XingGong , Chen Run , Wu Hao , Wang Fan , Wang Zhenyuan , Lian Chunfeng 
Published: December 2022

Abstract
The time since deposition (TSD) of a bloodstain, i.e., the time of a bloodstain formation is an essential piece of biological evidence in crime scene investigation. The practical usage of some existing microscopic methods (e.g., spectroscopy or RNA analysis technology) is limited, as their performance strongly relies on high-end instrumentation and/or rigorous laboratory conditions. This paper presents a practically applicable deep learning-based method (i.e., BloodNet) for efficient, accurate, and costless TSD inference from a macroscopic view, i.e., by using easily accessible bloodstain photos. To this end, we established a benchmark database containing around 50,000 photos of bloodstains with varying TSDs. Capitalizing on such a large-scale database, BloodNet adopted attention mechanisms to learn from relatively high-resolution input images the localized fine-grained feature representations that were highly discriminative between different TSD periods. Also, the visual analysis of the learned deep networks based on the Smooth Grad-CAM tool demonstrated that our BloodNet can stably capture the unique local patterns of bloodstains with specific TSDs, suggesting the efficacy of the utilized attention mechanism in learning fine-grained representations for TSD inference. As a paired study for BloodNet, we further conducted a microscopic analysis using Raman spectroscopic data and a machine learning method based on Bayesian optimization. Although the experimental results show that such a new microscopic-level approach outperformed the state-of-the-art by a large margin, its inference accuracy is significantly lower than BloodNet, which further justifies the efficacy of deep learning techniques in the challenging task of bloodstain TSD inference. Our code is publically accessible via https://github.com/shenxiaochenn/BloodNet. Our datasets and pre-trained models can be freely accessed via https://figshare.com/articles/dataset/21291825.
An evolution-based machine learning to identify cancer type-specific driver mutations
Authors: Kim Donghyo , Ha Doyeon , Lee Kwanghwan , Lee Heetak , Kim Inhae , Kim Sanguk 
Published: December 2022

AbstractIdentifying cancer type-specific driver mutations is crucial for illuminating distinct pathologic mechanisms across various tumors and providing opportunities of patient-specific treatment. However, although many computational methods were developed to predict driver mutations in a type-specific manner, the methods still have room to improve. Here, we devise a novel feature based on sequence co-evolution analysis to identify cancer type-specific driver mutations and construct a machine learning (ML) model with state-of-the-art performance. Specifically, relying on 28 000 tumor samples across 66 cancer types, our ML framework outperformed current leading methods of detecting cancer driver mutations. Interestingly, the cancer mutations identified by sequence co-evolution feature are frequently observed in interfaces mediating tissue-specific protein–protein interactions that are known to associate with shaping tissue-specific oncogenesis. Moreover, we provide pre-calculated potential oncogenicity on available human proteins with prediction scores of all possible residue alterations through user-friendly website (http://sbi.postech.ac.kr/w/cancerCE). This work will facilitate the identification of cancer type-specific driver mutations in newly sequenced tumor samples.
Biophysical informatics reveals distinctive phenotypic signatures and functional diversity of single-cell lineages
Authors: Chan Trevor J , Zhang Xingjian , Mak Michael 
Published: December 2022

Abstract

Motivation
In this work, we present an analytical method for quantifying both single-cell morphologies and cell network topologies of tumor cell populations and use it to predict 3D cell behavior.

Results
We utilized a supervised deep learning approach to perform instance segmentation on label-free live cell images across a wide range of cell densities. We measured cell shape properties and characterized network topologies for 136 single-cell clones derived from the YUMM1.7 and YUMMER1.7 mouse melanoma cell lines. Using an unsupervised clustering algorithm, we identified six distinct morphological subclasses. We further observed differences in tumor growth and invasion dynamics across subclasses in an in vitro 3D spheroid model. Compared to existing methods for quantifying 2D or 3D phenotype, our analytical method requires less time, needs no specialized equipment and is capable of much higher throughput, making it ideal for applications such as high-throughput drug screening and clinical diagnosis.

Availability and implementation
https://github.com/trevor-chan/Melanoma_NetworkMorphology.

Supplementary information
Supplementary data are available at Bioinformatics online.
Expression patterns of NKCC1 in neurons and non-neuronal cells during cortico-hippocampal development
Authors: Kurki Samu N , Uvarov Pavel , Pospelov Alexey S , Trontti Kalevi , Hübner Antje K , Srinivasan Rakenduvadhana , Watanabe Masahiko , Hovatta Iiris , Hübner Christian A , Kaila Kai , Virtanen Mari A 
Published: December 2022

Abstract
The Na-K-2Cl cotransporter NKCC1 is widely expressed in cells within and outside the brain. However, our understanding of its roles in brain functions throughout development, as well as in neuropsychiatric and neurological disorders, has been severely hindered by the lack of reliable data on its developmental and (sub)cellular expression patterns. We provide here the first properly controlled analysis of NKCC1 protein expression in various cell types of the mouse brain using custom-made antibodies and an NKCC1 knock-out validated immunohistochemical procedure, with parallel data based on advanced mRNA approaches. NKCC1 protein and mRNA are expressed at remarkably high levels in oligodendrocytes. In immature neurons, NKCC1 protein was located in the somata, whereas in adult neurons, only NKCC1 mRNA could be clearly detected. NKCC1 immunoreactivity is also seen in microglia, astrocytes, developing pericytes, and in progenitor cells of the dentate gyrus. Finally, a differential expression of NKCC1 splice variants was observed, with NKCC1a predominating in non-neuronal cells and NKCC1b in neurons. Taken together, our data provide a cellular basis for understanding NKCC1 functions in the brain and enable the identification of major limitations and promises in the development of neuron-targeting NKCC1-blockers.
Single voxel autocorrelation uncovers gradients of temporal dynamics in the hippocampus and entorhinal cortex during rest and navigation
Authors: Bouffard Nichole R , Golestani Ali , Brunec Iva K , Bellana Buddhika , Park Jun Young , Barense Morgan D , Moscovitch Morris 
Published: December 2022

Abstract
During navigation, information at multiple scales needs to be integrated. Single-unit recordings in rodents suggest that gradients of temporal dynamics in the hippocampus and entorhinal cortex support this integration. In humans, gradients of representation are observed, such that granularity of information represented increases along the long axis of the hippocampus. The neural underpinnings of this gradient in humans, however, are still unknown. Current research is limited by coarse fMRI analysis techniques that obscure the activity of individual voxels, preventing investigation of how moment-to-moment changes in brain signal are organized and how they are related to behavior. Here, we measured the signal stability of single voxels over time to uncover previously unappreciated gradients of temporal dynamics in the hippocampus and entorhinal cortex. Using our novel, single voxel autocorrelation technique, we show a medial-lateral hippocampal gradient, as well as a continuous autocorrelation gradient along the anterolateral-posteromedial entorhinal extent. Importantly, we show that autocorrelation in the anterior-medial hippocampus was modulated by navigational difficulty, providing the first evidence that changes in signal stability in single voxels are relevant for behavior. This work opens the door for future research on how temporal gradients within these structures support the integration of information for goal-directed behavior.