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Colorectal cancer (CRC) remains a malignancy tumor with high metastasis and poor prognosis. We aimed to explore the effect of circular RNA (circRNA) hsa_circ_0006732 in the progression of CRC. Hsa_circ_0006732 expression in CRC tissues and cell lines were detected using qRT-PCR. The relationship between hsa_circ_0006732 expression and clinicopathologic characteristics of patients with CRC was analyzed. Loss-of-function assay was conducted to determine the regulatory effect of hsa_circ_0006732 on CRC cell proliferation, migration and invasion by using the CCK-8, wound-healing assay and transwell assays. Protein expression changes on epithelial mesenchymal transition (EMT)-related factors were detected by western blotting. The downstream signaling pathway was investigated by bioinformatics, dual-luciferase reporter assay. Rescue assay was further examined for prediction validation. It was found that hsa_circ_0006732 was highly expressed in CRC tissues and cell lines. Downregulation of hsa_circ_0006732 suppressed the proliferation, migration, invasion and EMT of CRC cells. Further mechanistic investigations proved that hsa_circ_0006732 functioned as a competitive endogenous RNA (ceRNA) by directly sponging of miR-127-3p, which further affected the expression of Ras-related protein Rab-3D (Rab3D). Taken together, these findings indicated that hsa_circ_0006732 might be an oncogene in CRC through the regulation of the miR-127-5p/RAB3D axis. Thus, hsa_circ_0006732 might serve as a potential therapeutic target for the treatment of CRC.

Background: The Ebola virus has started to infect humans from time to time since then and has led to several outbreaks. Due to urbanisation growth, invasion of forested areas, and close interaction with wildlife animals, the spread of the Ebola virus has caused the deadliest diseases to animals and humans. To date, the Ebola virus disease (EVD) claimed many lives of human beings and a greater number of cases were observed in the African region. Hence, a review was carried out to analyse the trends in EVD outbreaks, morbidity and mortality among EVD patients, efficacy and safety of drugs approved for the treatment of EVD. Method: The literature on EVD outbreaks, safety, and efficacy of EVD drugs were searched on Science Direct, PubMed, and Google Scholar using the MeSH terms such as ̈Ebola, Ebola virus disease, Outbreak, Epidemic, Safety, Efficacy, for the period of 2016–2020. In addition to that. Centers for Disease Control & Prevention (CDC), World Health Organization (WHO), US Food & Drug Administration, and UpToDate websites also searched for the latest reports, guidelines, approved drugs, etc. Results: There are only a few treatment options available for EVD to date, the most commonly used drugs for EVD are ZMapp, Inmazeb, and Ebanga. The review found that among these three drugs, ZMapp Plus is superior in the treatment of EVD with the current standard of care of 91.2%. INMAZEB when given at a 3 ml/kg IV dose reduced the mortality rate by 17% in subjects with EVD. Ebanga has shown a mortality rate of 35.1% when given a 50 mg/kg single IV dose. The most observed adverse effects were fever, tachycardia, diarrhoea, vomiting, hypotension, tachypnea, and chills. Conclusion: Overall, Inmazeb is the preferred drug of choice over ZMapp or other drugs for the treatment of EVD, and Ebanga is a choice in patients with cardiovascular complications. In addition to that, supportive care is very essential to control the mortality rate.

Supplemental material, sj-docx-1-cre-10.1177_02692155231172295 for Dose, Content, and Context of Usual Care in Stroke Upper Limb Motor Interventions: A Systematic Review by Sarah P Newton, Emily J Dalton, Jia Y Ang, Marlena Klaic, Vincent Thijs and Kathryn S Hayward in Clinical Rehabilitation

Supplemental material, sj-docx-1-tva-10.1177_15248380221150951 for Prevalence of Alcohol and Other Drug Use in Patients Presenting to Hospital for Violence-Related Injuries: A Systematic Review by Georgina Lau, Jia Y. Ang, Nayoung Kim, Belinda J. Gabbe, Biswadev Mitra, Paul M. Dietze, Sandra Reeder, Debbie Scott and Ben Beck in Trauma, Violence, & Abuse

Supplemental material, sj-docx-1-tva-10.1177_15248380221150951 for Prevalence of Alcohol and Other Drug Use in Patients Presenting to Hospital for Violence-Related Injuries: A Systematic Review by Georgina Lau, Jia Y. Ang, Nayoung Kim, Belinda J. Gabbe, Biswadev Mitra, Paul M. Dietze, Sandra Reeder, Debbie Scott and Ben Beck in Trauma, Violence, & Abuse

Recent studies in many kinds of mammals have established the existence of multiple γ rhythms in the cerebral cortex subserving different functions. In the primary visual cortex (V1), visually induced γ rhythms are dependent on stimulus features. However, experimental findings of γ power induced by varying the size of the drifting grating are inconsistent. Here, we reinvestigated the spatial summation properties of visually induced spike and γ rhythm activities in mouse V1. Our results show that drifting sinusoidal grating stimuli mainly induce 2 γ band rhythms, including a low-frequency band (25–45 Hz) and a high-frequency band (55–75 Hz). Unlike previous findings, we discovered that visually induced γ power could also exhibit extrareceptive field (ERF) modulatory properties. The modulation by ERF stimulation could be either suppressive, countersuppressive, or nonsuppressive, mostly similar to the local spike activity. Moreover, further analysis of the neuron group exhibiting surround suppression in both spike and γ activity revealed that the strength of the surround suppression and the receptive field size showed moderate correlations between measurements by spike and γ rhythm activity. Our findings improve the understanding of the characteristics and neural mechanisms of induced γ rhythms in visual spatial summation.

CH4@C60 was the first example an organic molecule has been embedded in C60, and by far the largest molecule. CH4 can rotate freely in the molecular cage, and the carbon skeleton structure of the C60 has no obvious deformation. The electronic structure of CH4@C60 and interaction between C60 and CH4 were studied under quantum mechanical calculation method. The different reaction sites on C-C bonds in C60 and the weak Van der Waals interaction between CH4 and C60 were shown clearly. These results and the orbital interaction between CH4 and C60 were helpful for understanding and further application of this unique biggest organic molecule CH4 contained in C60 structure so far.

In digestive system, colorectal cancer (CRC) is a common malignant tumor. The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of the rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in CRC, and the aberrant activation of this pathway is associated with tumorigenesis. We aimed to explore the role of Rho GTPase activating protein 9 (ARHGAP9) in the progression of CRC as well as its regulatory effects on the PI3K/AKT/mTOR pathway.The expression of ARHGAP9 in CRC tumor tissues and cell lines were detected using reverse transcription-quantitative PCR (qRT-PCR). 5-ethynyl-2'-deoxyuridine (EdU) assay was applied to test the cell proliferation. Cell migration and invasion were both assessed through transwell assay. Xenograft mouse models were constructed to explore the effects of ARHGAP9 on CRC in vivo. The expressions of PI3K/AKT/mTOR-activating factors and epithelial-mesenchymal transition (EMT)-related factors were all determined using western blot. LY294002 was employed to block PI3K/AKT/mTOR pathway in CRC cells.The expression of ARHGAP9 was down-regulated in CRC tumor tissues and cell lines when compared to normal tissues and cells. The over-expression of ARHGAP9 inhibited cell proliferation, invasion, migration and EMT in CRC cell lines while the knockdown of ARHGAP9 promoted them. In addition, ARHGAP9 up-regulation inhibited the activation of PI3K/AKT/mTOR signaling pathway in CRC cell lines while ARHGAP9 down-regulation led to an opposite effect. The over-expression of ARHGAP9 suppressed CRC tumor growth in vivo. When the PI3K/AKT/mTOR pathway was blocked in CRC cells, the effects of ARHGAP9 knockdown on cell proliferation, migration, invasion and EMT were all overturned.ARHGAP9 inhibited the malignant phenotypes of CRC cells via interdicting PI3K/AKT/mTOR signaling pathway.

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A small molecule probe for simultaneous detection of HSA and SO2 via their distinct fluorescent signals was designed recently. This effective tool provided a significant boost in understand underlying mechanism of synergistic action between SO2 and HSA in disease. The structure and fluorescent character of this probe molecule were studied under density functional theory in this work. The different stable conformations of probe C23 were found through theoretical method which explained the no experimental fluorescent character of the probe itself. The electron excitation analysis indicated the charge transfer process in the restricted C23 (binding to the hydrophobic cavity of HSA) and CS (C23 reaction with SO2) when the molecules were under optical excitation. The theoretical results could be helpful for understanding the electronical properties in the probe and providing the insights for designing new probe molecules.

Covalent functionalization of graphene is recently developed from the formation of sp3 hybridized carbon atom (sp3-C) to the sp3 hybridized nitrogen (sp3-N) at the anchoring site. Here, we investigated the electronic structures and transport properties of the zigzag graphene nanoribbons functionalized by covalently bonding of p-aminophenol (p-AP) molecule. First principles results demonstrate that the formed sp3-N plays a vital role in determining the electronic structure and transport properties of the system, resulting in a halfmetallic characteristic with a perfect spin-filtering behavior (100%). Interestingly, the performance of the spin-filtering is find to be insensitive to the sub-structures of the molecule. Our findings reveal the importance of sp3-N and suggest a new mechanism for realizing high-performance spin-filtering devices with functionalized graphene.

Software reuse, especially partial reuse, poses legal and security threats to software development. Since its source codes are usually unavailable, software reuse is hard to be detected with interpretation. On the other hand, current approaches suffer from poor detection accuracy and efficiency, far from satisfying practical demands. To tackle these problems, in this paper, we propose \textit{ISRD}, an interpretation-enabled software reuse detection approach based on a multi-level birthmark model that contains function level, basic block level, and instruction level. To overcome obfuscation caused by cross-compilation, we represent function semantics with Minimum Branch Path (MBP) and perform normalization to extract core semantics of instructions. For efficiently detecting reused functions, a process for "intent search based on anchor recognition" is designed to speed up reuse detection. It uses strict instruction match and identical library call invocation check to find anchor functions (in short anchors) and then traverses neighbors of the anchors to explore potentially matched function pairs. Extensive experiments based on two real-world binary datasets reveal that \textit{ISRD} is interpretable, effective, and efficient, which achieves $97.2\%$ precision and $94.8\%$ recall. Moreover, it is resilient to cross-compilation, outperforming state-of-the-art approaches.

Binary similarity analysis is critical to many code-reuse-related issues, where function matching is its fundamental task. “ 1-to-1 ” mechanism has been applied in most binary similarity analysis works, in which one function in a binary file is matched against one function in a source file or binary file. However, we discover that the function mapping is a more complex problem of “ 1-to-n ” (one binary function matches multiple source functions or binary functions) or even “ n-to-n ” (multiple binary functions match multiple binary functions) due to the existence of function inlining , different from traditional understanding. In this article, we investigate the effect of function inlining on binary similarity analysis. We carry out three studies to investigate the extent of function inlining, the performance of existing works under function inlining, and the effectiveness of existing inlining-simulation strategies. Firstly, a scalable and lightweight identification method is designed to recover function inlining in binaries. 88 projects (compiled in 288 versions and resulting in 32,460,156 binary functions) are collected and analyzed to construct four inlining-oriented datasets for four security tasks in the software supply chain, including code search, OSS (Open Source Software) reuse detection, vulnerability detection, and patch presence test. Datasets reveal that the proportion of function inlining ranges from 30–40% when using O3 and sometimes can reach nearly 70%. Then, we evaluate four existing works on our dataset. Results show most existing works neglect inlining and use the “1-to-1” mechanism. The mismatches cause a 30% loss in performance during code search and a 40% loss during vulnerability detection. Moreover, most inlined functions would be ignored during OSS reuse detection and patch presence test, thus leaving these functions risky. Finally, we analyze two inlining-simulation strategies on our dataset. It is shown that they miss nearly 40% of the inlined functions, and there is still a large space for promotion. By precisely recovering when function inlining happens, we discover that inlining is usually cumulative when optimization increases. Thus, conditional inlining and incremental inlining are recommended to design a low-cost and high-coverage inlining-simulation strategy.

Deep learning systems are known to be vulnerable to adversarial samples, which are implemented to change the prediction results by adding small perturbations to benign samples. It is significant to defend against an adversarial attack in critical fields such as automatic drive. In this paper, we propose an interpretation area-guided detection method of adversarial samples, which can improve the performance of the typical feature squeezing method by combining the generated interpretation results. Specifically, we divide the input image into two main parts, the interpretation part, and the non-interpretation part. Then we only squeeze the non-interpretation part, which can reduce the side-effect for benign samples. We evaluate our approach on two widely used datasets, and the results demonstrate that our approach outperforms the original feature squeezing method.

In recent years, deep learning is increasingly prevalent in the field of Software Engineering (SE). Especially, representation learning, which can learn vectors from the syntactic and semantics of the code, offers much convenience and promotion for the downstream tasks such as code search and vulnerability detection. In this work, we introduce our two applications of leveraging representation learning for software analysis, including defect prediction and vulnerability detection.

Dysregulation of microRNA contributes to multiple tumorigenic processes. Although downregulation of miR-199a-3p has been shown in many cancers, its effects on esophageal squamous cell carcinoma (ESCC) and the regulatory mechanism are still obscure. Here, we aim to evaluate the biological function and underlying mechanisms of miR-199a-3p in ESCC as well as its value to clinical treatment of ESCC. We first analyzed expression of miR-199a-3p in esophageal cancer by bioinformatic analysis and found that there were different opinions about expression of miR-199a-3p in esophageal cancer, and the following qRT-PCR assay demonstrated which was markedly downregulated in ESCC cells. Next, we increased the expression of miR-199a-3p in ESCC cells using miR-199a-3p mimics and demonstrated that overexpression of miR-199a-3p significantly inhibited cell proliferation, migration and invasion, as well as induced cell cycle retard and promoted apoptosis in ESCC. Furthermore, we explored the functional targets of miR-199a-3p and identified that overexpression of miR-199a-3p inhibited mTOR/p70S6K pathway, but stimulated PI3K/Akt pathway. Finally, we demonstrated that overexpression of miR-199a-3p enhanced proliferation-inhibiting effects of MK2206, an inhibitor of Akt, to ESCC cells, which might be related that MK2206 eliminated the activation of miR-199a-3p to p-Akt. These findings discover that miR-199a-3p might participate in the carcinogenesis process of ESCC, which provides a new insight for treatment of ESCC.

The great influence of Bitcoin has promoted the rapid development of blockchain-based digital currencies, especially the altcoins, since 2013. However, most altcoins share similar source codes, resulting in concerns about code innovations. In this paper, an empirical study on existing altcoins is carried out to offer a thorough understanding of various aspects associated with altcoin innovations. Firstly, we construct the dataset of altcoins, including source code repositories, GitHub fork relations, and market capitalizations (cap). Then, we analyze the altcoin innovations from the perspective of source code similarities. The results demonstrate that more than 85% of altcoin repositories present high code similarities. Next, a temporal clustering algorithm is proposed to mine the inheritance relationship among various altcoins. The family pedigrees of altcoin are constructed, in which the altcoin presents similar evolution features as biology, such as power-law in family size, variety in family evolution, etc. Finally, we investigate the correlation between code innovations and market capitalization. Although we fail to predict the price of altcoins based on their code similarities, the results show that altcoins with higher innovations reflect better market prospects., Comment: 10 pages

OP16, a derivative of the novel ent-kaurene diterpenoid compound separated from Rabdosia rubescens, has been confirmed for its efficacy and safety in the treatment of esophageal squamous cell carcinoma (ESCC) in our previous study. However, the precise mechanisms of tumor lethality mediated by OP16 have not yet been fully characterized. To investigate the effects and molecular mechanism of OP16 on autophagy and apoptosis of ESCC cells. Effects and mechanism of OP16 on autophagy of ESCC cells were first detected by Western blot, immunofluorescence, mRFP-GFP-LC3 adenovirus infection and transmission electron microscope. Next, function of autophagy and apoptosis induced by OP16 on cell death was investigated by flow cytometry and CCK-8 assay. Finally, molecular mechanism of OP16 affecting autophagy and apoptosis of ESCC cells was explored by Western blot. We demonstrated that OP16 could induce autophagy by promoting the formation of autophagosome and autolysosome, and promote autophagic cell death in ESCC. Furthermore, we also found that OP16 could promote cell apoptosis by activating mitochondria apoptosis pathway in ESCC. Finally, we demonstrated that OP16 affecting autophagy and mitochondria apoptosis pathway was mediated by phosphorylation of Akt. Our data show that OP16 could promote cell death through affecting autophagy and mitochondria apoptosis pathway mediated by Akt in ESCC, which enriches the theoretical mechanism of anti-tumor effects of OP16 and provides a basis for treatment of OP16 on ESCC.

Autophagy plays critical roles in tumorigenesis, while the effects of autophagy on chemoresistance of cancer cells had great disparity. This study aims to explore the impacts of autophagy on the sensitivity and resistance of gastric cancer cells to cisplatin (DDP). We firstly demonstrated that there was stronger autophagy activity in gastric cancer SGC-7901 cells than that in DDP-resisting SGC-7901/DDP cells. Then, we discovered that inhibiting autophagy by chloroquine (CQ) significantly enhanced the proliferation-inhibiting and apoptosis-inducing effects of DDP to SGC-7901 and SGC-7901/DDP cells. Moreover, CQ could partially reverse the resistance of SGC-7901/DDP cells to DDP in a concentration-dependent manner. However, the autophagy inducer everolimus (RAD001) had no obvious effects on the sensitivity of gastric cells to DDP. Mechanistically, we demonstrated that CQ might enhance the sensitivity of SGC-7901cells and improve the resistance of SGC-7901/DDP cells to DDP through inhibiting the mTORC1 pathway, especially to SGC-7901/DDP cells. Additionally, we found interfering Beclin-1 using Beclin-1 shRNA also enhanced the proliferation-inhibiting and apoptosis-inducing effects of DDP on gastric cancer cells by inhibiting phosphorylation of Akt. Our study shows that inhibiting autophagy could improve the chemoresistance and enhanced sensitivity of gastric cancer cells to DDP and provide a rationale for the administration of cisplatin combined with CQ for treating patients with gastric cancer.

Software plagiarism seriously impedes the healthy development of open source software. To fight against code obfuscation and inherent non-determinism of thread scheduling applied against software plagiarism detection, we proposed a new dynamic birthmark called DYnamic Key Instruction Sequence (DYKIS) and a framework called Thread-oblivious dynamic Birthmark (TOB) for the purpose of reviving the existing birthmarks and a thread-aware dynamic birthmark called Thread-related System call Birthmark (TreSB). Though many approaches have been proposed for software plagiarism detection, they are still limited to satisfy the following highly desired requirements: the applicability to handle binary, the capability to detect partial plagiarism, the resiliency to code obfuscation, the interpretability on detection results, and the scalability to process large-scale software. In this position paper, we discuss and outline the research opportunities and challenges in the field of software plagiarism detection in order to stimulate brilliant innovations and direct our future research efforts.

Additional file 4. Graphs 1 to 210 (pages 1 to 35).

Additional file 7. Graphs 631 to 840 (pages 106 to 140).

Additional file 6. Graphs 421 to 630 (pages 71 to 105).

Additional file 8. Graphs 841 to 1050 (pages 141 to 175).

Additional file 1. Figures S1 to S10, and additional text on the causal ordering of variables.

Additional file 5. Graphs 211 to 420 (pages 36 to 70).

Additional file 3. Index and notes on supplementary graphs 1 to 205 (page 1 to 205).

Public health taxes on less healthy food and beverage products have been shown to be effective in various settings. However, it is unclear if observed reductions in the quantity of taxed products purchased is a result of price increases due to the tax or the accompanying messaging and if the effects are influenced by the level of support for such taxes within the population. 941 adults residing in Singapore were randomized and asked to shop in one of four versions of a fully functional on-line experimental grocery store: 1) no tax control; 2) implicit tax showing only post-tax prices (i.e., 20 % higher than control prices) on high-in-calorie products; 3) fake tax showing pre-tax prices and a label falsely indicating that the price includes a 20 % tax on high-in-calorie products; and 4) explicit tax showing the same label as in 3) and an actual 20 % price increase applied to the high-in-calorie products. The proportion of high-in-calorie products purchased was 14 % in the control arm. We were unable to reject the null hypothesis of no effect in the implicit tax arm compared to control (0.08, 95 % CI -3.31 to 1.77) or in the fake tax arm compared to the control (2.59, 95 % CI -5.04 to 0.00) but observed a statistically significant 3.35 percentage point decrease (95 % CI -6.01 to -0.5) in the explicit tax arm compared to control. We were unable to reject the null hypothesis of no effect in any of the outcomes related to diet quality. Individuals who support the tax showed greater responsiveness to the explicit and fake taxes compared to those who do not (price elasticities of demand of -1.38 and -0.51 respectively). Results suggest that reductions in the proportions of high-in-calorie products purchased may be largely attributable to explicit messaging rather than to price increases. However, even when effective, policymakers should recognize that changes in purchasing patterns may not improve diet quality and that results may not generalize to other areas where levels of support differ.

Natural Language Processing (NLP) is an important technology that motivates the form of AI applications today. Many NLP libraries are available for researchers and developers to perform standard NLP tasks (such as segmentation, tokenization, lemmatization, POS tagging, and NER) without the need to develop from scratch. However, there are some challenges in selecting the most suitable library such as data type, performance, and the compatibility. In this paper, we assessed five popular NLP libraries for performing the standard processing tasks on datasets crawled from different online news sources in Malaysia. The obtained results are analysed and differences of those libraries are listed. The goal of this study is to provide a clear view for users to select the suitable NLP library for their text analysis task.

Ferroptosis is a newly discovered process of cell death that differs from apoptosis, autophagy, and pyroptosis. It is closely related to tumor formation, diseases that damage tissue, and neurodegenerative diseases. Activation of the extracellular regulated protein kinase (EPK) pathway and acylCOA synthetase long-chain family member 4 (ACSL4) are indicative of ferroptosis. During ferroptosis, the mitochondrial volume becomes smaller and the double membrane density increases. The process of ferroptosis involves disruption of the material redox reaction, and changes in the levels of cystine, glutathione, NADPH, and increase of GPX4, NOX, and ROS. Iron increases significantly in ferroptosis. Divalent iron ions can greatly promote lipid oxidation, ROS accumulation, and thus promote ferroptosis. The occurrence and progress of ferroptosis are influenced by multiple factors and signaling pathways. Keywords: Ferroptosis, Iron; Lipid, Active oxygen, Inhibitor, Inducer

System identification is one of the method to construct a plant mathematical model from experimental data. This method has been widely applied in the automatic control, aviation, spaceflight medicine, society economics and other fields more. With the rapid growth of the science and technology, the system identification technique has increasingly grown in various applications. Since most of the system identification devices are off-line base, this means that the system identification can only be done after collecting the data and process through a computer devices. This paper will show how to process system identification method with real-time system. This method required a microcontroller as the medium to perform. That’s why the system identification method will be programmed into a microcontroller, based on Least Square Method. Later, the system will be tested on a RC circuit to see the effect of the signal and the mathematical model obtained. The data will undergo the system identification toolbox for process using ARX and ARMAX model. On the other hand, the data will also be collected using the microcontroller created for analysis purpose. To ensure the validity of the model some verification methods are performed. Results show that the Least Square Method using Microcontroller base has the capability to work as a system identification tools.