Interference-induced generation of a chirp-free short isolated attosecond pulse in the water window region with multicolor laser fields.

Compensating for the intrinsic attosecond chirp (atto-chirp) of wideband high-order harmonics in the water window region is a significant challenge, in order to obtain isolated attosecond pulses (IAPs) with a width of tens of attoseconds (as). Here, we propose to realize the generation of IAP with duration as short as 20 as, central energy of 365 eV, and bandwidth exceeding 150 eV from chirp-free high harmonics generated by a four-color driving laser, without the necessity for atto-chirp compensation with natural materials. Unlike any other gating methods that an IAP arises from only one electron ionization event, we take advantage of the interference between harmonic radiation produced by multiple ionizing events. We further demonstrate that such chirp-free short IAP survives after taking account of macroscopic propagation effects. Given that the synthesized multicolor laser field can also effectively increase the harmonic flux, this work provides a practical way for experiments to generate the broad bandwidth chirp-free IAPs in the water window region.

Value delivery in green consumption: the effect of advertisement value proposition on consumer perception and purchase intention.

Amid the expanding green consumer market, companies are increasingly emphasizing their eco-friendly contributions in advertising. This study delves into the value delivery process within green consumption, guided by the service-dominant logic (S-D logic). A survey-based experiment with 589 responses reveals that the information frame in advertising significantly impacts consumer value perceptions and purchase intentions. Notably, the temporal frame of advertising plays a pivotal role, influencing consumers' value perceptions. Future framing enhances emotional value perceptions, while past framing promotes environmental value perceptions. This research enhances our understanding of value delivery mechanisms in green consumption and holds valuable implications for marketers of sustainable products.

Notoginsenoside R1 restrains the proliferation and migration of airway smooth muscle cells isolated from rats with chronic obstructive pulmonary disease.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a common disorder that is characterized by systemic and lung inflammation. Notoginsenoside R1 (NGR1) displays anti-inflammatory properties in numerous diseases. We aimed to explore the function and mechanism of NGR1 in COPD. MATERIALS AND METHODS: COPD rats were established through cigarette smoke exposure, lipopolysaccharide injection, and cold stimulation. Rat airway smooth muscle cells (ASMCs) were separated and identified. Then, ASMCs were treated with NGR1 (25 or 50 µM) and cigarette smoke extract (CSE). Thereafter, the vitality, proliferation, and migration of ASMCs were measured. Additionally, cell cycle, inflammation-related factors, α-SMA, and PI3K/AKT pathway-related marker expressions of the ASMCs were also detected. Molecular docking experiments were conducted to explore the interaction of NGR1 to PI3K, TGF-ß, p65, and AKT. Moreover, 740 Y-P (a PI3K/Akt pathway agonist) were used to validate the mechanism of NGR1 on COPD. RESULTS: NGR1 inhibited the proliferation and migration, but caused cell cycle arrest for CSE-triggered ASMCs. Furthermore, NGR1 not only decreased IL-1ß, IL-6, IL-8, and TNF-α contents, but also reduced α-SMA expression in CSE-stimulated ASMCs. Moreover, NGR1restrainedTGF-ß1 expression, PI3K, p65, and AKT phosphorylation in CSE-stimulated ASMCs. Molecular docking experiments showed NGR1 exhibited a strong binding ability to PI3K, TGF-ß1, p65, and AKT. Notably, the effects of NGR1 on the proliferation and migration of CSE-induced ASMCs were reversed by 740 Y-P. CONCLUSIONS: NGR1 can restrain the proliferation and migration of CSE-induced ASMCs, indicating that NGR1 may be a therapeutic candidate for treating COPD.

A biomarker panel of secondary hypertension is simultaneously quantified by coupling of magnetic solid-phase extraction and liquid chromatography-tandem mass spectrometry.

RATIONALE: Secondary hypertension is often caused by activation of complex multi-organ endocrine systems, while renin activity indicated by angiotensins (Angs), aldosterone (ALD) and cortisol (COR) in such systems are generally accepted as its diagnostic markers. As antibody-based methods cannot offer comparable quantification for these biomarkers, a liquid chromatography (LC)-tandem mass spectrometry (MS/MS)-based approach was developed to quantify them simultaneously and accurately. METHODS: Five different beads for magnetic solid-phase extraction (MSPE) were evaluated towards their enrichment efficiency for these biomarkers. An LC system with optimized elution gradient and a triple-quadrupole MS with tuned parameters were coupled to quantitatively monitor the extracted analytes. The method performance was further examined such as linearity, precision, stability, recovery rate and matrix effect. Based on the developed method, the abundance of Ang II, ALD and COR in plasma was measured and the quantification was compared with that derived from commercial ELISA kits. RESULTS: As compared with other MSPEs, Angs, ALD and COR were highly enriched by the HLB magnetic beads with satisfactory recoveries. These analytes were simultaneously quantified by LC/MS/MS and all the method parameters for quantification were well matched with the requirements of clinical testing. Comparison of the quantitative results derived from ELISA and LC/MS/MS exhibited that the two methods offered basically comparable values with Pearson r values at 0.896, 0.895 and 0.835, respectively. The stability test for plasma Angs at room temperature indicated that the abundance of Ang II was relatively stable within 3 h, whereas that of Ang I and Ang 1-7 was time-dependently changed. CONCLUSIONS: Coupling of HLB beads and LC/MS/MS thus enables simultaneous quantification of a set of biomarkers related to secondary hypertension.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Molecular mechanism of the NOS/NOX regulation of antibacterial activity in Eriocheir sinensis.

To elucidate the role of nitric oxide synthase (NOS), which produces the free radical nitric oxide (NO), and nicotinamide adenine dinucleotide phosphate oxidase (NOX), which produces the superoxide anion (O2-), in the innate immunity of Eriocheir sinensis, the full lengths of the NOS and NOX genes were cloned via rapid amplification of the cDNA ends and then expressed in the prokaryotic form to obtain the recombinant proteins, NOS-HIS and NOX-HIS. Through bacterial binding and stimulation experiments, the molecular mechanisms of NOS and NOX in the innate immunity of E. sinensis were explored. Based on the results, NOS and NOX were 5900 bp and 4504 bp long, respectively, and were evolutionarily conserved. Quantitative real-time PCR revealed that NOS and NOX were expressed in all studied tissues, and both were expressed in the highest amounts in hemocytes. NOS-HIS and NOX-HIS could bind to bacteria with different binding powers; their binding ability to gram-positive bacteria was higher than that of binding to gram-negative bacteria. After stimulation with Aeromonas hydrophila, NOS expression was significantly up-regulated at 3, 6, and 48 h, and NOX expression was significantly down-regulated at 3, 12, 24, and 48 h. After bacterial stimulation, the NOS enzyme activity in the serum of E. sinensis was also significantly up-regulated at 6 and 48 h, and the NOX enzyme activity was significantly down-regulated at 12 and 48 h, aligning with the gene expression trend. Moreover, the related free radical molecules, NO, O2-, and H2O2, tended to decrease after bacterial stimulation. Overall, the gene expression and enzyme activity of NOS and NOX had been changed respectively, and the contents of a series of free radical molecules (NO, O2- and H2O2) were induced in E. sinensis after bacterial stimulation, which then exert antibacterial immunity.

Maternal serum polyols and its link to gestational diabetes mellitus: A population-based nested case-control study.

CONTEXT: Sugar alcohols (also called polyols) confer a"healthy"sugar substitute. One of possible reasons to support the safe use in pregnant women is their natural origin and the presence of polyols in maternal and fetal samples during normal human gestation. But little is known about the association between circulating sugar alcohols levels and maternal metabolic disorders during pregnancy. OBJECTIVE: We aimed to detect the concentration of the polyols in participants with and without GDM, and to investigate the association between maternal serum levels of polyols and gestational diabetes mellitus (GDM), as well as newborn outcomes. DESIGN: A nested population-based case-control study was conducted in 109 women with and without GDM. Maternal concentrations of serum erythritol, sorbitol, and xylitol at fasting state were quantified using a time-of-flight mass spectrometry system. RESULT: In women with GDM, serum concentrations of erythritol and sorbitol were higher, but serum concentrations of xylitol were lower, compared with those in women without GDM. Per 1-SD increment of Box-Cox transformed concentrations of erythritol and sorbitol were associated with the increased odds of GDM by 43% and 155% (95% CI 1.07-1.92 and 95 CI%: 1.77-3.69), while a decreased odd was found for xylitol by 25% (95 CI%: 0.57-1.00). Additionally, per 1-SD increase of Box-Cox transformed concentrations of serum sorbitol was associated with a 52% increased odd of large-for-gestational-age newborns controlling for possible confounders (95% CI 1.00-2.30). CONCLUSIONS: Maternal circulating sugar alcohols levels during pregnancy were significantly associated with GDM. These findings provide the potential roles of polyols on maternal metabolic health during pregnancy.

The mid-term outcomes of aortic-root repair is not inferior to Bentall procedure in acute type-A aortic dissection.

OBJECTIVE: Bentall procedure used to be standard operation for involved aortic root in acute type A aortic dissection (ATAAD). But aortic root repair for preserving valve is still controversial in ATAAD. This study aimed to evaluate the midterm outcomes of aortic root repair by comparing with Bentall approach. METHODS: A retrospective analysis of 1075 ATAAD patients with aortic root involvement was conducted. The patients were divided into aortic root repair group (n = 447) and Bentall group (n = 628). The propensity score matching analysis (PSMA) was used to adjust the baseline. RESULTS: The median follow-up was 44 months (interquartile range, 17-65 months; range, 1-130 months). The 30-day mortality in the repair and replacement groups was 15.0 % and 12.9 % (P = 0.327) respectively; the late overall mortality was 15.9 % and 14.0 % (P = 0.394) respectively. The Kaplan-Meier 10-year survival and free-from-reoperation was 86.0 % and 92.5 % respectively in the repair group. After PSMA, the cumulative survival rate [Hazard Ratio (HR) 0.685; 95 % Confidence Interval (CI) 0.457-1.027; P = 0.747]) and reoperation rate (HR 0.308; 95 % CI 0.070-1.355; P = 0.157) was not significantly higher in the repair group than in the Bentall group. CONCLUSION: The mid-term outcome of aortic root repair is probably not inferior to Bentall procedure. Therefore, root repair is an alternative approach in ATAAD with the advantage of preserving native valve.

Tandem Addition/Cyclization/Halogenation Reaction of Difluoromethylated N-Acylhydrazones with Allyltrimethylsilanes.

As novel difluoromethyl building blocks, difluoromethylated N-acylhydrazones react with allyltrimethylsilanes and the halogen source via a tandem addition/cyclization/halogenation strategy, which produces various difluoromethylpyrazoline compounds in good yields. The method features mild reaction conditions, broad substrate scopes, and a transition metal-free process with easy operation. It also proves that difluoromethylated N-acylhydrazones are useful difluoromethyl building blocks for the construction of difluoromethylated nitrogen heterocycles.

Unveiling FOS as a Potential Diagnostic Biomarker and Emetine as a Prospective Therapeutic Agent for Diabetic Nephropathy.

Background: Diabetic nephropathy (DN) is one of the primary causes of end-stage renal disease, yet effective therapeutic targets remain elusive. This study aims to identify novel diagnostic biomarkers and potential therapeutic candidates for DN. Methods: Differentially expressed genes (DEGs) in GSE96804 and GSE142025 were identified and functional enrichment analysis was performed. Diagnostic biomarkers were selected using machine learning algorithms and evaluated by Receiver Operating Characteristic analysis. c-Fos expression was validated in an established DN mouse model. Immune infiltration levels were assessed with Single-Sample Gene Set Enrichment Analysis. Co-expression analysis revealed regulatory relationships involving FOS. cMAP predicted potential therapeutic candidates. Transcriptome sequencing and experiments in RAW264.7 cells was performed to investigate molecular mechanisms of emetine. Results: In both datasets, we identified 44 upregulated and 74 downregulated DEGs involved in focal adhesion, ECM-receptor interaction, and the PI3K-Akt signaling pathway. FOS emerged as a robust diagnostic marker with decreased expression in DN patients and DN mouse. Co-expression analysis revealed potential regulatory mechanisms of FOS, implicating the MAPK signaling pathway, regulation of cell proliferation and apoptotic signaling pathways. Immune dysregulation was observed in DN patients. Notably, emetine was identified as a potential therapeutic candidate. Transcriptome sequencing and experimental validation demonstrated emetine suppressed M1 macrophage polarization by inhibiting the activation of NF-κB signaling pathway, as well as reducing the expression of Il-18 and Ccl5. Conclusion: In conclusion, our study identified FOS as a promising diagnostic biomarker and emetine as a potential therapeutic candidate for DN. These findings enhance our understanding of DN pathogenesis and present novel prospects for therapeutic strategies.

Mechanochemical Synthesis of PdO2 Nanoparticles Immobilized over Silica Gel for Catalytic Suzuki-Miyaura Cross-Coupling Reactions Leading to the C-3 Modification of 1H-Indazole with Phenylboronic Acids.

The C-3 modification of 1H-indazole has produced active pharmaceuticals for the treatment of cancer and HIV. But, so far, this transformation has seemed less available, due to the lack of efficient C-C bond formation at the less reactive C-3 position. In this work, a series of silica gel-supported PdO2 nanoparticles of 25-66 nm size were prepared by ball milling silica gel with divalent palladium precursors, and then employed as catalysts for the Suzuki-Miyaura cross-coupling of 1H-indazole derivative with phenylboronic acid. All the synthesized catalysts showed much higher cross-coupling yields than their palladium precursors, and could also be reused three times without losing high activity and selectivity in a toluene/water/ethanol mixed solvent. Although the palladium precursors showed an order of activity of PdCl2(dppf, 1,1'-bis(diphenylphosphino)ferrocene) > PdCl2(dtbpf, 1,1'-bis(di-tert-butylphosphino)ferrocene) > Pd(OAc, acetate)2, the synthesized catalysts showed an order of C1 (from Pd(OAc)2) > C3 (from PdCl2(dtbpf)) > C2 (from PdCl2(dppf)), which conformed to the orders of BET (Brunauer-Emmett-Teller) surface areas and acidities of these catalysts. Notably, the most inexpensive Pd(OAc)2 can be used as a palladium precursor for the synthesis of the best catalyst through simple ball milling. This work provides a highly active and inexpensive series of catalysts for C-3 modification of 1H-indazole, which are significant for the large-scale production of 1H-indazole-based pharmaceuticals.

Optimized leaf storage and photosynthetic nitrogen trade-off promote synergistic increases in photosynthetic rate and photosynthetic nitrogen use efficiency.

A coordinated increase in the photosynthetic rate (A) and photosynthetic nitrogen use efficiency (PNUE) is an effective strategy for improving crop yield and nitrogen (N) utilization efficiency. PNUE tends to decrease with increasing N levels, but there are natural variations. Consequently, leaf functional N partitioning in Brassica napus genotypes under different N rates was measured to explore the optimized N allocation model for synchronously increasing A and PNUE values. The results showed that genotypes whose PNUE increased with increasing N supply (PNUE-I) produced an approximate A value with a relatively low leaf N content, owing to reduced storage N (Nstore ) and close photosynthetic N (Npsn ) content. Partial least squares path modeling showed that A was dominated by the Npsn content, and PNUE was directly influenced by A and Nstore . The A value increased with the Npsn content until the Npsn content exceeded the threshold value. The boundary line of PNUE varied with the Npsn and Nstore proportions, indicating that the optimum Npsn and Nstore proportions were 51.6% and 40.3%, respectively. The Nstore proportion of PNUE-I was closer to the thresholds and benefited from lower increments in Rubisco content and nonprotein form storage N content with improved N supply. Optimized Nstore and Npsn trade-off by regulating increments in Nstore content with increased N supply, thereby promoting coordinated increases in A and PNUE.

Free nitrous acid prediction in ANAMMOX process using hybrid deep neural network model.

Free nitrous acid (FNA) is a critical metric for stabilization of ANAMMOX but can not be directly and immediately measured by sensors or chemical measurement method, which hinders the effective management and operation for ANAMMOX. This study focuses on FNA prediction using hybrid model based on temporal convolutional network (TCN) combined with attention mechanism (AM) optimized by multiobjective tree-structured parzen estimator (MOTPE), called MOTPE-TCNA. A case study in an ANAMMOX reactor is carried out. Results show that nitrogen removal rate (NRR) is highly correlated with FNA concentration, indicating that it can forecast the operational status by predicting FNA. Then, MOTPE successfully optimizes the hyperparameters of TCN, helping TCN achieve a high prediction accuracy, and AM furtherly improves model accuracy. MOTPE-TCNA obtains the highest prediction accuracy, whose R2 value gets 0.992, increasing 1.71-11.80% compared to other models. As a deep neural network model, MOTPE-TCNA has more advantages than traditional machine learning methods in FNA prediction, which is beneficial to maintain the stable operation and easy control for ANAMMOX process.

Telomere-related prognostic biomarkers for survival assessments in pancreatic cancer.

Human telomeres are linked to genetic instability and a higher risk of developing cancer. Therefore, to improve the dismal prognosis of pancreatic cancer patients, a thorough investigation of the association between telomere-related genes and pancreatic cancer is required. Combat from the R package "SVA" was performed to correct the batch effects between the TCGA-PAAD and GTEx datasets. After differentially expressed genes (DEGs) were assessed, we constructed a prognostic risk model through univariate Cox regression, LASSO-Cox regression, and multivariate Cox regression analysis. Data from the ICGC, GSE62452, GSE71729, and GSE78229 cohorts were used as test cohorts for validating the prognostic signature. The major impact of the signature on the tumor microenvironment and its response to immune checkpoint drugs was also evaluated. Finally, PAAD tissue microarrays were fabricated and immunohistochemistry was performed to explore the expression of this signature in clinical samples. After calculating 502 telomere-associated DEGs, we constructed a three-gene prognostic signature (DSG2, LDHA, and RACGAP1) that can be effectively applied to the prognostic classification of pancreatic cancer patients in multiple datasets, including TCGA, ICGC, GSE62452, GSE71729, and GSE78229 cohorts. In addition, we have screened a variety of tumor-sensitive drugs targeting this signature. Finally, we also found that protein levels of DSG2, LDHA, and RACGAP1 were upregulated in pancreatic cancer tissues compared to normal tissues by immunohistochemistry analysis. We established and validated a telomere gene-related prognostic signature for pancreatic cancer and confirmed the upregulation of DSG2, LDHA, and RACGAP1 expression in clinical samples, which may provide new ideas for individualized immunotherapy.

Metformin Promotes Proliferation of Mouse Female Germline Stem Cells by Histone Acetylation Modification of Traf2.

Female germline stem cells (FGSCs) are adult stem cells that can both self-renew and differentiate into mature oocytes. Although small-molecule compounds are capable of regulating the development of FGSCs, the effects and mechanisms of action of metformin, a commonly used drug for diabetes, on FGSCs are largely unknown. Here, we found that metformin promoted the viability and proliferation of FGSCs through H3K27ac modification. To elucidate the mechanism by which metformin promoted FGSCs proliferation, Chromatin Immunoprecipitation Sequencing of histone 3 lysine 27 acetylation (H3K27ac) in FGSCs was performed with or without metformin-treatment. The results indicate that metformin modulates FGSCs via the mitogen-activated protein kinase (MAPK) signaling pathway, and tumor necrosis factor receptor associated factor 2 (Traf2) was identified as an important target gene for H3K27ac modification during FGSCs proliferation. Subsequent experiments showed metformin promoted FGSCs proliferation by H3K27ac modification of Traf2 to regulate MAPK signaling. Our findings deepen understanding of how H3K27ac modifications regulate FGSCs development and provide a theoretical basis for the prevention and treatment of premature ovarian failure, polycystic ovary syndrome, infertility, and related diseases.

An Adaptive Model Filtering Algorithm Based on Grubbs Test in Federated Learning.

Federated learning has been popular for its ability to train centralized models while protecting clients' data privacy. However, federated learning is highly susceptible to poisoning attacks, which can result in a decrease in model performance or even make it unusable. Most existing defense methods against poisoning attacks cannot achieve a good trade-off between robustness and training efficiency, especially on non-IID data. Therefore, this paper proposes an adaptive model filtering algorithm based on the Grubbs test in federated learning (FedGaf), which can achieve great trade-offs between robustness and efficiency against poisoning attacks. To achieve a trade-off between system robustness and efficiency, multiple child adaptive model filtering algorithms have been designed. Meanwhile, a dynamic decision mechanism based on global model accuracy is proposed to reduce additional computational costs. Finally, a global model weighted aggregation method is incorporated, which improves the convergence speed of the model. Experimental results on both IID and non-IID data show that FedGaf outperforms other Byzantine-robust aggregation rules in defending against various attack methods.

Metformin promotes female germline stem cell proliferation by upregulating Gata-binding protein 2 with histone ß-hydroxybutyrylation.

BACKGROUND: Metformin as a first-line clinical anti-diabetic agent prolongs the lifespan of model animals and promotes cell proliferation. However, the molecular mechanisms underlying the proliferative phenotype, especially in epigenetics, have rarely been reported. The aim of this study was to investigate the physiological effects of metformin on female germline stem cells (FGSCs) in vivo and in vitro, uncover ß-hydroxybutyrylation epigenetic modification roles of metformin and identify the mechanism of histone H2B Lys5 ß-hydroxybutyrylation (H2BK5bhb) in Gata-binding protein 2 (Gata2)-mediated proliferation promotion of FGSCs. METHODS: The physiological effects of metformin were evaluated by intraperitoneal injection and histomorphology. The phenotype and mechanism studies were explored by cell counting, cell viability, cell proliferation assay and protein modification omics, transcriptomics, chromatin immunoprecipitation sequencing in FGSCs in vitro. RESULTS: We found that metformin treatment increased the number of FGSCs, promoted follicular development in mouse ovaries and enhanced the proliferative activity of FGSCs in vitro. Quantitative omics analysis of protein modifications revealed that H2BK5bhb was increased after metformin treatment of FGSCs. In combination with H2BK5bhb chromatin immunoprecipitation and transcriptome sequencing, we found that Gata2 might be a target gene for metformin to regulate FGSC development. Subsequent experiments showed that Gata2 promoted FGSC proliferation. CONCLUSION: Our results provide novel mechanistic understanding of metformin in FGSCs by combining histone epigenetics and phenotypic analyses, which highlight the role of the metformin-H2BK5bhb-Gata2 pathway in cell fate determination and regulation.

A Lightweight Intelligent Network Intrusion Detection System Using One-Class Autoencoder and Ensemble Learning for IoT.

Network intrusion detection technology is key to cybersecurity regarding the Internet of Things (IoT). The traditional intrusion detection system targeting Binary or Multi-Classification can detect known attacks, but it is difficult to resist unknown attacks (such as zero-day attacks). Unknown attacks require security experts to confirm and retrain the model, but new models do not keep up to date. This paper proposes a Lightweight Intelligent NIDS using a One-Class Bidirectional GRU Autoencoder and Ensemble Learning. It can not only accurately identify normal and abnormal data, but also identify unknown attacks as the type most similar to known attacks. First, a One-Class Classification model based on a Bidirectional GRU Autoencoder is introduced. This model is trained with normal data, and has high prediction accuracy in the case of abnormal data and unknown attack data. Second, a multi-classification recognition method based on ensemble learning is proposed. It uses Soft Voting to evaluate the results of various base classifiers, and identify unknown attacks (novelty data) as the type most similar to known attacks, so that exception classification becomes more accurate. Experiments are conducted on WSN-DS, UNSW-NB15, and KDD CUP99 datasets, and the recognition rates of the proposed models in the three datasets are raised to 97.91%, 98.92%, and 98.23% respectively. The results verify the feasibility, efficiency, and portability of the algorithm proposed in the paper.

PrivacyMask: Real-world privacy protection in face ID systems.

Recent works have illustrated that many facial privacy protection methods are effective in specific face recognition algorithms. However, the COVID-19 pandemic has promoted the rapid innovation of face recognition algorithms for face occlusion, especially for the face wearing a mask. It is tricky to avoid being tracked by artificial intelligence only through ordinary props because many facial feature extractors can determine the ID only through a tiny local feature. Therefore, the ubiquitous high-precision camera makes privacy protection worrying. In this paper, we establish an attack method directed against liveness detection. A mask printed with a textured pattern is proposed, which can resist the face extractor optimized for face occlusion. We focus on studying the attack efficiency in adversarial patches mapping from two-dimensional to three-dimensional space. Specifically, we investigate a projection network for the mask structure. It can convert the patches to fit perfectly on the mask. Even if it is deformed, rotated and the lighting changes, it will reduce the recognition ability of the face extractor. The experimental results show that the proposed method can integrate multiple types of face recognition algorithms without significantly reducing the training performance. If we combine it with the static protection method, people can prevent face data from being collected.

Nucleos(t)ide analogues altered quasispecies composition of hepatitis B virus (HBV)-resistant mutations in serum HBV DNA and serum HBV RNA.

Serum hepatitis B virus (HBV) RNA is a new serological indicator reflecting viral replication with good clinical application prospects. This study aimed to clarify the dynamic changes of serum HBV RNA levels and the quasispecies of HBV RNA virus-like particles in nucleos(t)ide analogues (NAs)-experienced chronic hepatitis B (CHB) patients harboring NAs-resistant mutations and their identifiable effects on NAs resistance. We included CHB patients who were on long-term NAs treatment and with HBV DNA rebound. The longitudinally dynamics of serum HBV RNA levels were quantitatively detected, and the quasispecies differences between serum HBV DNA and serum HBV RNA were compared by high-throughput sequencing. The effect of NAs concentration pressure on altering the resistance mutations quasispecies proportion of HBV DNA and HBV RNA in cell supernatant was analyzed in vitro. A total of 447 serum samples from 36 CHB patients treated with NAs were collected. The median follow-up period was 47 months (about 4 years), and the longest follow-up period was 117 months (about 10 years). Our results showed that HBV RNA could reflect virological breakthrough in 23 (64%, 23/36) patients, and serum HBV RNA rebound earlier than HBV DNA in 12 (52%, 12/23) patients. However, serum HBV RNA remained at a consistently high level and did not fluctuate significantly with the HBV DNA rebound in 6 of 36 patients. In addition, serum HBV RNA was not consistently detectable in 7 of the 36 patients, and their serum HBV RNA was undetectable even after HBV DNA had rebounded. The proportion of drug-resistant mutations in HBV DNA was higher than that of HBV RNA by high-throughput sequencing. The results of in vitro experiments showed that the viral strains with drug-resistant mutation in HBV DNA in cell supernatants gradually become the dominant strains with the increase of NAs concentrations. Serum HBV RNA levels can reflect virological breakthrough in most NAs- treated CHB patients, but there are certain limitations. NAs alter the quasispecies composition of serum HBV DNA and serum HBV RNA, resulting in a higher detection rate of drug-resistant mutations in serum HBV DNA than in serum HBV RNA.