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Abstract Background Ferroptosis is a unique mode of cell death that is iron-dependent and associated with oxidative stress and lipid peroxidation. Oxidative stress and ferroptosis are essential mechanisms leading to metabolic abnormalities in cells and have been popular areas in cancer research. Methods Initially, 76 oxidative stress and ferroptosis-related genes (OFRGs) were acquired by intersecting the gene sets from oxidative stress and ferroptosis. Afterwards, optimal OFRGs were screened using PPI networks, and individuals were separated into two OFRG subtypes (K = 2). Subsequently, we successfully constructed and verified a prognostic signature comprising SLC7A2, Cadherin 19 (CDH19), and CCN1. To further uncover potential biomarkers of gastric cancer (GC), we examined the expression level of CDH19, investigated the effects of knocking down CDH19 on the biological behavior of GC cells, and explored whether CDH19 is involved in ferroptosis and oxidative stress processes. Results According to the findings, individuals in the low-risk scoring group have less infiltration of immune suppressive cells, fewer occurrences of immune escape and dysfunction, greater efficacy in chemotherapy and immunotherapy, and better survival outcomes. The qRT-PCR assay indicated that CDH19 expression was significantly higher in GC cells. Through experiments, we demonstrated that knocking down CDH19 can affect the transcription levels of ACSL4 and GPX4, increase intracellular iron ion concentration and accumulation of reactive oxygen species (ROS), and inhibit the proliferation and migration of GC cells. Conclusion We developed an OFRG-related signature to predict the prognosis and treatment responsiveness of individuals with GC and identified CDH19 as a possible therapeutic target for GC.

Natural processes are substantially impacted by human activity, and assessing human activity has significant ramifications for regional ecological conservation. The study developed an extended human footprint (HF) assessment model based on the theory of ecological effects and human pressures to evaluate human disturbances in the urban agglomerations of the Yellow River Basin using data from 2005 to 2020, revealing the spatiotemporal pattern in the region. The conclusions show that the HF value of urban agglomeration in the Yellow River Basin has steadily increased from 2005 to 2020, primarily driven by mining intensity and road construction. High HF areas are primarily concentrated in urban areas in the south-central of the region, with a tendency to spread outward. Medium HF areas are mainly distributed in the eastern part of the study area, and the spatial distribution increases year by year, extending outward from the center area. The moderately low and HF areas are mostly found in the mountainous areas of the northwest. Among the urban agglomerations in the Yellow River Basin, the Central Plains UA and Shandong Peninsula UA are the areas most heavily affected by human disturbance. The conclusions are instructive for the high-quality development of urban agglomerations in the Yellow River Basin.

BackgroundHIGD1B (HIG1 Hypoxia Inducible Domain Family Member 1B) is a protein-coding gene linked to the occurrence and progression of various illnesses. However, its precise function in gastric cancer (GC) remains unclear.MethodsThe expression of HIGD1B is determined through the TCGA and GEO databases and verified using experiments. The association between HIGD1B and GC patients’ prognosis was analyzed via the Kaplan-Meier (K-M) curve. Subsequently, the researchers utilized ROC curves to assess the diagnostic capacity of HIGD1B and employed COX analysis to investigate risk factors for GC. The differentially expressed genes (DEGs) were then subjected to functional enrichment analysis, and a nomogram was generated to forecast the survival outcome and probability of GC patients. Additionally, we evaluated the interaction between HIGD1B and the immune cell infiltration and predicted the susceptibility of GC patients to therapy.ResultsHIGD1B is markedly elevated in GC tissue and cell lines, and patients with high HIGD1B expression have a poorer outcome. In addition, HIGD1B is related to distinct grades, stages, and T stages. The survival ROC curves of HIGD1B and nomogram for five years were 0.741 and 0.735, suggesting appropriate levels of diagnostic efficacy. According to Cox regression analysis, HIGD1B represents a separate risk factor for the prognosis of gastric cancer (p

BackgroundGastric cancer (GC) poses a global health challenge due to its widespread prevalence and unfavorable prognosis. Although immunotherapy has shown promise in clinical settings, its efficacy remains limited to a minority of GC patients. Manganese, recognized for its role in the body’s anti-tumor immune response, has the potential to enhance the effectiveness of tumor treatment when combined with immune checkpoint inhibitors.MethodsGene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases was utilized to obtain transcriptome information and clinical data for GC. Unsupervised clustering was employed to stratify samples into distinct subtypes. Manganese metabolism- and immune-related genes (MIRGs) were identified in GC by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. We conducted gene set variation analysis, and assessed the immune landscape, drug sensitivity, immunotherapy efficacy, and somatic mutations. The underlying role of NPR3 in GC was further analyzed in the single-cell RNA sequencing data and cellular experiments.ResultsGC patients were classified into four subtypes characterized by significantly different prognoses and tumor microenvironments. Thirteen genes were identified and established as MIRGs, demonstrating exceptional predictive effectiveness in GC patients. Distinct enrichment patterns of molecular functions and pathways were observed among various risk subgroups. Immune infiltration analysis revealed a significantly greater abundance of macrophages and monocytes in the high-risk group. Drug sensitivity analysis identified effective drugs for patients, while patients in the low-risk group could potentially benefit from immunotherapy. NPR3 expression was significantly downregulated in GC tissues. Single-cell RNA sequencing analysis indicated that the expression of NPR3 was distributed in endothelial cells. Cellular experiments demonstrated that NPR3 facilitated the proliferation of GC cells.ConclusionThis is the first study to utilize manganese metabolism- and immune-related genes to identify the prognostic MIRGs for GC. The MIRGs not only reliably predicted the clinical outcome of GC patients but also hold the potential to guide future immunotherapy interventions for these patients.

Abstract Most of the current studies on carbon emission reduction have been focusing on the urban and industrial levels, overlooking policy assessment studies on the carbon emissions of construction enterprises in the Yangtze River Economic Belt (YREB). To explore the impact of smart city policy (SCP) on the carbon emissions of construction enterprises, this paper constructs a theoretical framework model for evaluating SCP based on the Political-Economic-Sociocultural-Technological-Environmental-Legal (PESTEL) model and the perspective of the pollution halo hypothesis. In addition, this paper adopts panel data of 110 cities covered by the YREB from 2004 to 2021 and verifies the SCP impact mechanism on the carbon emissions of construction enterprises in the YREB through the difference-in-differences (DID) method, the propensity score matching (PSM) method, and the analysis of mediating effects and moderating effects. The conclusions are as follows: (1) the SCP significantly curbs the carbon emissions of the construction enterprises in the YREB pilot cities; (2) the SCP has a regional qualitative effect on the carbon emissions of the construction enterprises in the YREB and it curbs the carbon emissions of the construction enterprises in the upstream and downstream regions; (3) R&D and FDI are important transmission mechanisms; and (4) new urbanization construction has a positive moderating effect on the carbon emission reduction effect of the SCP on construction enterprises. As a research precedence, this paper reveals for the first time the mechanism of the SCP on the carbon emissions of construction enterprises in the YREB through the lens of the PESTEL model and the pollution halo hypothesis; the paper not only enriches the research related to urban policies but also provides new evidence from Chinese construction enterprises for assessing the impacts of pilot cities.

Abstract The ‘Belt and Road’ (B&R) Initiative has received attention from environmental researchers. However, there are no studies explaining the impact of the B&R policy on the green development (GD) of construction enterprises. We aim to find a mechanism for how the B&R policy impacts the GD level of construction enterprises. Consequently, on the basis of a fixed effects model, we consider the B&R policy and the background of GD in the construction industry and construct a model of the GD level of construction enterprises. Meanwhile, we use panel data for 28 provincial administrative regions of the Chinese government from 2010 to 2020 and analyse the implications of the B&R policy on the GD level of construction enterprises using Stata 16.0. The main conclusions are as follows. (1) A positive promotion effect is evident in the planned focus areas of the B&R policy on construction enterprises’ GD levels. (2) Research and development (R&D), regional development, education, labour productivity and investment in sewage treatment significantly affect the intensity of CO2 emissions of regional construction enterprises, thus increasing and hindering the GD of construction enterprises. Taking the findings of this study into account, this study contributes to the econometrics of construction enterprises in the area of sustainable development. Additionally, it provides policy ideas for the government to further build a green B&R.

IntroductionThe relationship between oral and gut microbiota in alcohol dependence (AD) is not well understood, particularly the effects of oral microbiota on the intestinal microbiota. The current study aimed to explore the association between oral and gut microbiota in AD to clarify whether oral microbiota could ectopically colonize into the gut.Methods16S rRNA sequence libraries were used to compare oral and gut microbial profiles in persons with AD and healthy controls (HC). Source Tracker and NetShift were used to identify bacteria responsible for ectopic colonization and indicate the driver function of ectopic colonization bacteria.ResultsThe α-diversity of oral microbiota and intestinal microbiota was significantly decreased in persons with AD (all p

BackgroundSaliva secretion and oral microbiota change in rhythm with our biological clock. Dysbiosis of the oral microbiome and alcohol consumption have a two-way interactive impact, but little is known about whether the oral microbiome undergoes diurnal changes in composition and function during the daytime in patients with alcohol dependence (AD).MethodsThe impact of alcohol consumption on the diurnal salivary microbiome was examined in a case-control study of 32 AD patients and 21 healthy control (HC) subjects. We tested the changes in microbial composition and individual taxon abundance by 16S rRNA gene sequencing.ResultsThe present study is the first report showing that alcohol consumption enhanced the richness of the salivary microbiome and lowered the evenness. The composition of the oral microbiota changed significantly in alcohol-dependent patients. Additionally, certain genera were enriched in the AD group, including Actinomyces, Leptotrichia, Sphaerochaeta and Cyanobacteria, all of which have pathogenic effects on the host. There is a correlation between liver enzymes and oral microbiota. KEGG function analysis also showed obvious alterations during the daytime.ConclusionAlcohol drinking influences diurnal changes in the oral microbiota, leading to flora disturbance and related functional impairment. In particular, the diurnal changes of the oral microbiota may open avenues for potential interventions that can relieve the detrimental consequences of AD.

Key Encapsulation Mechanism (KEM) is a foundational cryptography primitive, which can provide secure symmetric cryptographic key material for transmission by using public key algorithms. Until now, many Chosen-Ciphertext (IND-CCA) secure KEM schemes are constructed from Chosen-Plaintext (IND-CPA) or One-Way (OW-CPA) secure PKE via the generic Fujisaki-Okamoto (FO) transformations (TCC 2017). However, the security relies on the Random Oracle Model (ROM). To the best of our knowledge, there are no IND-CCA secure KEM schemes based on Learning Parity with Noise (LPN) assumption that can against post quantum attacks in the standard model. In this work, we propose the first direct construction of LPN-based KEM, which is secure in the standard model. In particular, we use double-trapdoor technique to answer adversary's decryption queries correctly and a Target Collision Resistant (TCR) hash function to check the validity of the ciphertext. The encapsulated key is determined by a special LPN problem (with no random oracle required). The scheme is IND-CCA secure against post-quantum attacks under the low-noise LPN assumptions by a series of games and the security reduction is tight. Compared with previous schemes on 128-bit security level, our CCA-secure scheme only holds 50.78MB public keys, 62.50MB secret keys and 4.54KB ciphertexts, which is more efficient than the schemes of Döttling et al. (ASIACRYPT 2012), Kiltz et al. (PKC 2014) and Yu et al. (CRYPTO 2016) ((7.27GB, 7.24GB, 7.03KB), (80.89MB, 46.23MB, 6.80KB) and (70.95MB, 70.65MB, 86.50KB) respectively).

A microgrid is a flexible and localized grid that can disconnect from the main grid and operate independently on the traditional and/or renewable resource. It also can work with the main grid, and even provide power to the main grid when it has excess power to help relieve the pressure of energy. The flow of power between main grid and microgrid is monitored by smart meter, which kept the end user's privacy information and his/her energy usage in real time. Hence, ensuring the privacy and security of these information is a considerable challenge. In this paper, we investigate the relationship between microgrids and the main grid, and design a quantum-resistant lightweight authentication and key agreement (AKA) protocol based on fog computing. The proposed protocol provides the mutual authentication and generates a session key between a smart meter and a fog node. More importantly, it can resist against quantum computing attacks, as the security of our scheme relies on the hardness of the learning parity with noise (LPN) problem, an NP-complete problem. Finally, we evaluate the performance of our proposed protocol and prove that our protocol is more lightweight and efficient.

The prognosis of malignant gliomas remains poor, with median survival fewer than 20 months and a 5-year survival rate merely 5%. Their primary location in the central nervous system (CNS) and its immunosuppressive environment with little T cell infiltration has rendered cancer therapies mostly ineffective, and breakthrough therapies such as immune checkpoint inhibitors (ICIs) have shown limited benefit. However, tumor immunotherapy is developing rapidly and can help overcome these obstacles. But for now, malignant gliomas remain fatal with short survival and limited therapeutic options. Oncolytic virotherapy (OVT) is a unique antitumor immunotherapy wherein viruses selectively or preferentially kill tumor cells, replicate and spread through tumors while inducing antitumor immune responses. OVTs can also recondition the tumor microenvironment and improve the efficacy of other immunotherapies by escalating the infiltration of immune cells into tumors. Some OVTs can penetrate the blood-brain barrier (BBB) and possess tropism for the CNS, enabling intravenous delivery. Despite the therapeutic potential displayed by oncolytic viruses (OVs), optimizing OVT has proved challenging in clinical development, and marketing approvals for OVTs have been rare. In June 2021 however, as a genetically engineered OV based on herpes simplex virus-1 (G47Δ), teserpaturev got conditional and time-limited approval for the treatment of malignant gliomas in Japan. In this review, we summarize the current state of OVT, the synergistic effect of OVT in combination with other immunotherapies as well as the hurdles to successful clinical use. We also provide some suggestions to overcome the challenges in treating of gliomas.

In complex Industrial Internet of Things (IIoT) application systems, there may exist a variety of functional sub-systems which provide divergent services to the users and the relationship among these services could be strong, which is evidently very common in practice. As one such IoT application, the smart city is designed to use intelligent services in an environment where transport, environment, energy, living, governance, and civic components are integrated to operate the city in a smart and efficient manner. Surprisingly, however, the current state-of-the-art on blockchain does not show the progress on diversified services of the complex IIoT applications. This paper tends to fill the gap and presents a scalable block graph platform and consensus protocol for the complex IIoT applications by adopting the limited resources of IIoT devices. The platform and consensus protocol are generic in the sense that they can support any practical service. The directed acyclic graph represents a significant exhibition in improving the scalability of blockchains and supports our proposed consensus protocol in substance; moreover, the detailed syntax of the block graph is defined. The consensus protocol is showed to be secure against disloyal voting, sybil attack, and 51% attack. The real use case of smart city demonstrates the effectiveness of the proposal.

In this study, a novel prefabricated light-steel beam–column connection consisting of a thin-walled rectangular hollow section column and two cold-formed steel truss beams is proposed and investigated by carrying out experimental tests. Eight cruciform beam–column connection specimens with different configurations are fabricated and tested to failure under monotonic static loading. First, failure mode and the loading–displacement curve of each specimen are investigated. Consequently, the effect of three variables, including truss-beam configuration, truss-beam type, and with or without sleeve tube reinforcing the column, on the static bearing capacity of the proposed connection and the deflection of the truss beams are investigated. It is found that plug welding the sleeve to the column can significantly increase the static bearing capacity of the proposed connection. In addition, fillet welding connecting the column and the channel connectors to accommodate the end of the truss beams is crucial to the static bearing capacity of the proposed beam–column connection. Because beam–column connections with single-truss beams have a higher load-bearing capacity and require less material and assembly work, it is recommended to adopt this type of configuration for the proposed connection.

In-vehicle electronic control unit (ECU) communications generally count on private protocols (defined by the manufacturers) under controller area network (CAN) specifications. Parsing the private protocols for a particular vehicle model would be of great significance in testing the vehicle’s resistance to various attacks, as well as in designing efficient intrusion detection and prevention systems (IDPS) for the vehicle. This paper proposes a suite of methods for parsing ECU private protocols on in-vehicle CAN network. These methods include an algorithm for parsing discrete variables (encoded in a discrete manner, e.g., gear state), an algorithm for parsing continuous variables (encoded in a continuous manner, e.g., vehicle speed), and a parsing method based on upper-layer protocols (e.g., OBD and UDS). Extensive verifications have been performed on five different brands of automobiles (including an electric vehicle) to demonstrate the universality and the correctness of these parsing algorithms. Some parsing tips and experiences are also presented. Our continuous-variables parsing algorithm could run in a semi-automatic manner and the parsing algorithm from upper-layer protocols could execute in a completely automatic manner. One might view the results obtained by our parsing algorithms as an important indicator of penetration testing on in-vehicle CAN network.

Bitcoin is promoted as decentralized cryptocurrency by using pseudonym to achieve anonymity. Unfortunately, numerous seminal works have demonstrated that Bitcoin only offers weak anonymity in practice. Indeed, the practical technologies of clustering and flow analysis are much effective for tracing Bitcoin transaction and thereby revealing the owner involved. Otherwise said, user's privacy in Bitcoin has been sadly degenerated to be linkable. In this paper, we propose a completely decentralized scheme that can provide full anonymity in Bitcoin. The idea behind the output is to exploit a secure escrow address, which is consensual by all the involved users. The escrow address is generated from the trick of cryptographically secure distributed key generation and can then be used for mixing transactions in Bitcoin. Our protocol is secure against malicious adversaries. The users can jointly perform the protocol and successfully accomplish the transaction without the help of any (trusted) third party and no extra fees. Besides, our proposal is completely compatible with the current Bitcoin architecture.

An internet of vehicles allows intelligent automobiles to interchange messages with other cars, traffic management departments, and data analysis companies about vehicle identification, accident detection, and danger warnings. The implementation of these features requires Internet of Things system support. Smart cars are generally equipped with many (hundreds or even thousands of) sensors and microcomputers so that drivers gain more information about travel. The connection between the in-vehicle network and the Internet can be leveraged by the attackers in a malicious manner and thus increases the number of ways the in-vehicle network can now be targeted. Protecting increasingly intelligent vehicle systems becomes more difficult, especially because a network of many different devices makes the system more vulnerable than ever before. The paper assumes a generic threat model in which attackers can access the controller area network (CAN) bus via common access points (e.g., Bluetooth, OBD-II, Wi-Fi, physical access, and cellular communication, etc). A machine learning based simplified attention (SIMATT)-security control unit (SECCU) symmetry framework is proposed towards a novel and lightweight anomaly detecting mechanism for the in-vehicle network. For this framework, we propose two new models, SECCU and SIMATT, and obtain state-of-the-art anomaly detecting performance when fusing the former to the latter. Regardless of the training phase or the detection phase, we strive to minimize the computational cost and thereby obtain a lightweight anomaly detection method. In particular, the SECCU model has only one layer of 500 computing cells and the SIMATT model has been improved to reduce its computational costs. Through substantial experiment comparisons (with various classical algorithms, such as LSTM, GRU, GIDS, RNN, or their variations), it is demonstrated that the SIMATT-SECCU framework achieves an almost optimal accuracy and recall rate.

With the development and popularization of information technology and intelligence device, the diversity of different device making forensic analysis of existing equipment cannot meet today's networking and storage technology requirements, and exhibit complex operation, low efficiency, on high speed disk image storage and massive data correlation. An efficient distributed forensics system based on Hadoop technique, which can support multiple concurrent media scene forensics work, was designed and implemented, and through the dispatch control services would be evidence of different data storage media to a different distributed data storage server, each forensic task runtime could monopolize a forensic medium to achieve a parallel multiple media forensic analysis. Data show that responsible acknowledge duration will be 0.1 s for a 2～4 GB text file.