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Background. Acute generalized exanthematous pustulosis (AGEP) is a rare and serious adverse reaction of terbinafine. Understanding AGEP and terbinafine is primarily based on case reports. The purpose is to explore the clinical characteristics of terbinafine-induced AGEP, and to provide reference for clinical diagnosis and treatment. Methods. Case reports and original studies of terbinafine-induced AGEP were retrieved by searching Chinese and English databases from January, 1991, to May 31, 2022. Results. The median age of the 32 patients (17 males and 15 females) was 55 years (range: 6–84). The median time to onset of AGEP is 8 days (range: 1–77) and is usually accompanied by fever (>38°C) and elevated neutrophil levels (>8000/mm3). Four patients (12.5%) had oral mucosal involvement, and 10 patients (31.3%) developed postpustular desquamation. The lesions were mainly distributed in the trunk (43.8%), the whole body (34.4%), and the extremities (53.1%). Skin biopsy revealed subcorneal pustules (65.6%), intraepidermal cavernous pustules (43.8%), necrotic keratinocytes (15.6%), spongy hyperplasia (25.0%), neutrophil exocytosis (34.4%), and papillary dermal edema (40.6%). AGEP resolved completely in all patients at a median time of 12 days (range: 2–90) after discontinuation of terbinafine and symptomatic therapy. Conclusion. Clinicians should be aware that terbinafine-induced AGEP is a rare cutaneous adverse reaction. AGEP usually occurs within 2 weeks after administration and has a good prognosis after discontinuation.

Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent liver disease that is closely related to obesity and metabolic disorders. 5-methoxyflavone (5-MF) is a flavonoid with DNA polymerase-β inhibitory properties. In this study, we explored the effects of 5-MF on NAFLD and its potential mechanisms using oleic acid/palmitic acid-treated HepG2 cells and high-fat diet-fed C57BL/6J mice. Our results showed that 5-MF not only alleviated fat deposition and hepatic steatosis, but also improved oxidative damage. In addition, 5-MF has the effect of alleviating disorders of glucose metabolism and enhancing energy expenditure in HFD-induced obese mice. Mechanistically, reverse screening methods and molecular docking analysis were used in combination, and revealed that cytochrome P450 1A1 (CYP1A1) is the target for 5-MF. Further experiments showed that 5-MF ameliorated triglycerides deposition by inhibiting the enzyme activity and protein expression of CYP1A1. In conclusion, 5-MF provides a novel strategy for the prevention and treatment of high-fat-induced NAFLD.

Yuan-yuan Wu,1 Wen-Hui Liao,1 Zong-ling Niu,1 Si-Han Zhou,1 Tian-Tian Wu,1 Zhe Li,2 Qi-Hua Zhao,1 Jing-Yuan Xu,2 Ming-jin Xie1 1School of Chemical Science and Technology, Yunnan University, Kunming, People’s Republic of China; 2Department of Chemical Biology and Tianjin Key Laboratory on Technologies Enabling Development of Clinical Therapeutics and Diagnostics (Theranostics), School of Pharmacy, Tianjin Medical University, Tianjin, People’s Republic of ChinaCorrespondence: Ming-jin Xie, Email mjxie@ynu.edu.cnBackground: Gallium (III) metal-organic complexes have been shown to have the ability to inhibit tumor growth, but the poor water solubility of many of the complexes precludes further application. The use of materials with high biocompatibility as drug delivery carriers for metal-organic complexes to enhance the bioavailability of the drug is a feasible approach.Methods: Here, we modified the ligands of gallium 8-hydroxyquinolinate complex with good clinical anticancer activity by replacing the 8-hydroxyquinoline ligands with 5-bromo-8-hydroxyquinoline (HBrQ), and the resulting Ga(III) + HBrQ complex had poor water solubility. Two biocompatible materials, bovine serum albumin (BSA) and graphene oxide (GO), were used to synthesize the corresponding Ga(III) + HBrQ complex nanoparticles (NPs) BSA/Ga/HBrQ NPs and GO/Ga/HBrQ NPs in different ways to enhance the drug delivery of the metal complex.Results: Both of BSA/Ga/HBrQ NPs and GO/Ga/HBrQ NPs can maintain stable existence in different solution states. In vitro cytotoxicity test showed that two nanomedicines had excellent anti-proliferation effect on HCT116 cells, which shown higher level of intracellular ROS and apoptosis ratio than that of cisplatin and oxaliplatin. In addition, the superior emissive properties of BSA/Ga/HBrQ NPs and GO/Ga/HBrQ NPs allow their use for in vivo imaging showing highly effective therapy in HCT116 tumor-bearing mouse models.Conclusion: The use of biocompatible materials for the preparation of NPs against poorly biocompatible metal-organic complexes to construct drug delivery systems is a promising strategy that can further improve drug delivery and therapeutic efficacy.Graphical Abstract: Keywords: gallium complex, nanomedicine, anticancer, colorectal cells, drug delivery, in vivo imaging

Benefiting from excellent mechanical properties, large surface area, rich hydroxyl groups, good sustainability, etc., nanocellulose is highly promising for various applications. However, intense chemical treatment and long-term processing are usually required to fabricate nanocellulose. Herein, a new synthesis method of nanocellulose is developed by using ultraviolet light irradiation-assisted delignification and subsequent sonification. This method is more cost-effective, time-saving, and environmentally benign compared to most of previously reported synthesis methods of nanocellulose. The obtained nanocellulose contains a small amount of lignin, which is unfavorable for high-temperature stability and optimal transparency. However, a small amount of lignin is beneficial to mechanical properties and in-water stability. With this nanocellulose, flexible MnO

Mucin 4 (MUC4) overexpression promotes tumorigenesis and increases the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). To date, no study has reported the association between radiomics and MUC4 expression in PDAC. Thus, we aimed to explore the utility of radiomics based on multi-sequence magnetic resonance imaging (MRI) to predict the status of MUC4 expression in PDAC preoperatively.This retrospective study included 52 patients with PDAC who underwent MRI. The patients were divided into two groups based on MUC4 expression status. Two feature sets were extracted from the arterial and portal phases (PPs) of dynamic contrast-enhanced MRI (DCE-MRI). Univariate analysis, minimum redundancy maximum relevance (MRMR), and principal component analysis (PCA) were performed for the feature selection of each dataset, and features with a cumulative variance of 90% were selected to develop radiomics models. Clinical characteristics were gathered to develop a clinical model. The selected radiomics features and clinical characteristics were modeled by multivariable logistic regression. The combined model integrated radiomics features from different selected data sets and clinical characteristics. The classification metrics were applied to assess the discriminatory power of the models.There were 22 PDACs with a high expression of MUC4 and 30 PDACs with a low expression of MUC4. The area under the receiver operating characteristic (ROC) curve (AUC) values of the arterial phase (AP) model, the PP model, and the combined model were 0.732 (0.591-0.872), 0.709 (0.569-0.849), and 0.861 (0.760-0.961), respectively. The AUC of the clinical model was 0.666 (0.600-0.682). The combined model that was constructed outperformed the AP, the PP, and the clinical models (P0.05, although no statistical significance was observed in the combined modelRadiomics models based on multi-sequence MRI have the potential to predict MUC4 expression levels in PDAC.

Many factors were reported to be associated with diabetic retinopathy (DR); however, their contributions remained unclear. We aimed to evaluate the prognostic and diagnostic accuracy of logistic regression and three machine learning models based on various medical records.This was a cross-sectional study. We investigated the prevalence and associations of DR among 757 participants aged 40 years or older in the 2005-2006 National Health and Nutrition Examination Survey (NHANES). We trained the models to predict if the participants had DR with 15 predictor variables. Area under the receiver operating characteristic (AUROC) and mean squared error (MSE) of each algorithm were compared in the external validation dataset using a replicate cohort from NHANES 2007-2008.Among the 757 participants, 53 (7.00%) subjects had DR, the mean (standard deviation, SD) age was 57.7 (13.04), and 78.0% were male (n = 42). Logistic regression revealed that female gender (OR = 4.130, 95% CI: 1.820-9.380; P 0.05), HbA1c (OR = 1.665, 95% CI: 1.197-2.317; P 0.05), serum creatine level (OR = 2.952, 95% CI: 1.274-6.851; P 0.05), and eGFR level (OR = 1.009, 95% CI: 1.000-1.014, P 0.05) increased the risk of DR. The average performance obtained from internal validation was similar in all models (AUROC ≥ 0.945), and k-nearest neighbors (KNN) had the highest value with an AUROC of 0.984. In external validation, they remained robust or with modest reductions in discrimination with AUROC still ≥ 0.902, and KNN also performed the best with an AUROC of 0.982. Both logistic regression and machine learning models had good performance in the clinical diagnosis of DR.This study highlights the utility of comparing traditional logistic regression to machine learning models. We found that logistic regression performed as well as optimized machine learning methods when classifying DR patients.

The wear resistance diagram (WRD) is a useful tool for quantitatively estimating the life span of a tribological system in sheet metal forming at different load levels. However, the WRD derived from the authors’ previous research consists merely of scattered points, which make it difficult to reliably estimate the life span and its uncertainties at all load levels. Therefore, a wear resistance curve (WRC) that encompasses the life spans of all load levels is required for a broader scope of application of wear resistance estimation. In this paper, different models for the estimation of the S-N curve describing the fatigue behavior are tested to investigate their applicability in the estimation of wear resistance curves (WRC) in sheet metal forming. WRDs of different tribological systems are investigated and the results of curve fitting are evaluated. Besides the median of the estimated life spans, the WRCs of different confidence levels are also derived quantile calculation to estimate the load dependent uncertainties of tool life spans. Moreover, due to the time-consuming experiments to determine tool life, it is necessary to discuss possibilities for achieving a satisfactory estimation with the smallest possible number of tests. Therefore, the minimal number of tests and the suitable load levels for a satisfactory estimation will be discussed. After the study, several findings have been obtained:Compared to other models, Hwang and Han’s model for estimating fatigue life of composite material shows good applicability and the highest accuracy in estimating the WRC of uncoated tools.In terms of damage development, the fatigue damage of the composite material and the damage caused by wear on uncoated tools have similarities, which explains the applicability of Hwang and Han’s model for the estimation of WRC.Both higher and lower life wear data are the prerequisite for satisfactory wear estimation.

To investigate the effect of the FGFR2-CCDC6 fusion gene on cell proliferation and its mechanism of action, pCDNA3.1- FGFR2bWT, pCDNA3.1- FGFR2-CCDC6 expression plasmids were transiently transfected into Hucct-1 cells using Lipo-2000 liposomes. The effect of the fusion gene on cell proliferation was examined by MTT and the expression of FGFR2/AKT/signaling pathway proteins was detected by Western blot. Results showed that Hucct-1 cells transfected with the FGFR2-CCDC6 fusion gene showed increased FGFR2 protein expression (P0.001) and significantly higher cell proliferation capacity (P0.001) compared to normal controls. It was concluded that The FGFR2-CCDC6 fusion gene excessively activates the AKT, and ERK signaling pathway downstream of FGFR2 and plays a role in promoting cell proliferation.

Geoscientists usually use visuals like graphs and tables to explain their research to their peers or to non-specialists. However, it has been challenging to visualize how our Earth system works hidden behind complex geoscientific data effectively and intuitively to the general public. Art, as a universal language, has seen tremendous growth in the application of scientific data visualization in the last decade. Science-art collaborations become increasingly vital in creating new ways of popularizing geoscience. Here we present our recent immersive science-art interactive work titled 19 HZ, which explores the tectonic evolution and shaping of the deep sea through the visualization of submarine seismic data. The deep oceans were assumed to be quite silent. However, as more and more submarine monitoring experiments have been carried out, a hidden soundtrack under the sea was revealed, composed by marine animals like fish and mammals, and a number of natural phenomenons like submarine earthquakes and volcano activities, as well as human activities like ship-tracks. Our team (Deep Sea Light, DSL) has been working on the auralization and visualization of submarine seismic data, which offers a great opportunity to explore the dynamic world of deep oceans. Using seismic stations, we have successfully detected the activities of earthquakes, volcano eruption, and even fin whale songs. We further use the Audio Spectrum and the Touch Designer to visualize enormous soundtracks under the sea in 3D perspective and present different scenarios physically to the audience through artistic interactive devices. Under the lens of the ocean soundscape, our project will make the ambient deep-sea world more accessible to the public and convey to them how humans should listen to and understand the submarine world reverently.

As a common malignant tumor among women, ovarian cancer poses a serious threat to their health. This study demonstrates that long non-coding RNA NRSN2-AS1 is over-expressed in ovarian cancer tissues using patient sample and tissue microarrays. In addition, NRSN2-AS1 is shown to promote ovarian cancer cell proliferation and metastasis both in vitro and in vivo. Mechanistically, NRSN2-AS1 stabilizes protein tyrosine kinase 2 (PTK2) to activate the β-catenin pathway via repressing MG-53-mediated ubiquitinated degradation of PTK2, thereby facilitating ovarian cancer progression. Rescue experiments verify the function of the NRSN2-AS1/PTK2/β-catenin axis and the effects of MG53 on this axis in ovarian cancer cells. In conclusion, this study demonstrates the key role of the NRSN2-AS1/PTK2/β-catenin axis for the first time and explores its potential clinical applications in ovarian cancer.

Although the lithium-ion battery has dominated the sustainable energy field for many years, environmentally friendly and inexpensive sodium (Na) is a great contender to reduce the use of limited lithium resources. Sodium-ion batteries (SIBs) have a big catalog of cathode materials grouped into four main types: the Prussian blue analogs, organic-based materials, layered metal oxides, and polyanions, whereas the latter is characterized by sodium superionic conductors (NASICON) with its chemical formula such as Na3V2(PO4)2F3 (NVPF) gaining prevalence. Therefore, this review focuses on the most recent studies to promote the long-term stability, capacity, and energy density of NASICON’s high-potential NVPF.

To study the influence of the laser power, scanning speed, and cleaning water content on the laser cleaning effect and obtain the best cleaning parameters, this paper conducted a simulation analysis of the laser cleaning process and carried out a pulse laser cleaning of porcelain insulators experiment to verify. The results show that the cleaning rate gradually increases as the laser power increases from 20 W to 25 W. As the scanning speed increases from 1000 mm/s to 2500 mm/s, the laser overlapping rate gradually decreases, and the cleaning takes the lead in increasing and then decreasing. The appropriate cleaning water content is conducive to laser cleaning; when the water content is 0.115 g, the cleaning efficiency reaches the highest value of 98.20%. When the laser power is 25 W, and the scanning speed is 2000 mm/s, the cleaning efficiency can reach the highest value of 96.87%. This paper shows that the reasonable choice of cleaning parameters can effectively clean the insulator surface filth and obtain a better surface morphology.

To investigate the prevalence of depression and anxiety in patients undergoing maintenance hemodialysis (MHD) in Hohhot, a large city on the northern border of China, and to identify independent risk factors for depression and anxiety in these patients.Patients receiving MHD for3 months were enrolled in the four largest hemodialysis centers between September 2020 and December 2020. Depression and anxiety were assessed using the Zung self-rated depression scale (SDS) and Zung self-rated anxiety scale (SAS), respectively, with demographic and other data collected for logistic regression analyses.Among 305 MHD patients included in this study, the prevalence of depression was 55.1%, including 27.5%, 21.0%, and 6.6% with mild, moderate and severe cases, respectively. The prevalence of anxiety was 25.9%, with 20.0%, 4.6%, and 1.3% having mild, moderate, and severe cases, respectively. An independent protective factor for depression was family income of ≥1415 US dollars/month relative to157 US dollars/month (odds ratio [OR] 0.209, 95% confidence interval [CI] 0.065-0.673), and predictors of depression included ≥3 comorbidities (OR 18.527, 95% CI 1.674-205.028) and severe pruritus (OR 15.971, 95% CI 5.173-49.315). Independent predictors of anxiety included infrequent exercise (OR 3.289, 95% CI 1.411-7.664) and severe pruritus (OR 5.912, 95% CI 1.733-20.168). The correlation between depression and anxiety in these patients was significant (MHD patients in Northern China had high prevalence rates of depression (55.1%) and anxiety (25.9%). Lower family income, more comorbidities, and a higher degree of pruritus were predictors of depression, while infrequent exercise and severe pruritus were predictors of anxiety. Depression correlated significantly with anxiety. Attention should be given to family income, comorbidity, exercise, and pruritus severity for improved management of depression and anxiety among MHD patients.

In mobile crowdsensing (MCS), sensing data uploaded by dishonest workers may be false or even malicious. Thus, a reputation management system is often set up by using workers’ historical behaviours to indicate the quality of sensing data. As existing management schemes usually protect reputation update process, reputation scores are generally stored in plaintext, which may destroy the fair bidding property of a MCS system. To address this issue, we propose an anonymous reputation management system based on dual blockchain architecture, where reputation scores are masked. More precisely, one chain is used to store and update reputation scores, and another chain is responsible for publishing tasks and storing task-related data. To anonymously update and verify the reputation scores without affecting their usages in data sensing process, a kind of ring signature and Pedersen commitment are employed in smart contracts. In addition, a Schnorr signature is generated to make the reputation scores verifiable in the MCS system. We implement a prototype system on Hyperledger Fabric, and simulation results are provided for comparisons with two existing schemes.

Left bundle branch area pacing (LBBAP) has emerged as a promising physiologic pacing strategy. Though many clinical studies have established the feasibility and safety of LBBAP, the data for very elderly patients are lacking.This study aimed to assess the feasibility and safety of LBBAP in very elderly patients (≥80 years).Two hundred and forty consecutive patients who received LBBAP implantation were retrospectively enrolled in the present study. Inclusion criteria were patients with atrioventricular block, atrial fibrillation with a slow ventricular response, and heart failure with bundle branch block. The patients were divided into two groups: those aged ≥80 years and those aged80 years. LBBAP implantation was successfully performed in 48 of 53 (90.6%) very elderly patients and 162 of 187 (86.5%) counterparts. In the very elderly group, the mean (standard deviation [SD]) age was 84 (3) years, mean (SD) paced QRS duration was 112.4 (9.0), and the mean (SD) stimulus to R wave peak time was 82.0 (14.2) ms. Mean (SD) pacing thresholds and mean (SD) R wave sensing were 0.61(0.21) V and 12.1 (4.7) mV at implant. Pacing parameters in very elderly patients were similar to those in their counterparts. During a median follow-up of 6 months, pacing parameters remained stable. Five patients in the very elderly group developed complications (1 with septal perforation during the procedure, 1 with pocket hematoma, 1 with pacing threshold increase, and 2 with micro lead dislodgement during follow-up).LBBAP is safe and effective in patients ≥80 years old. LBBAP can be considered as an alternative method for delivering physiological pacing in this special population.

Password guessing is an important issue in user security and privacy protection. Using generative adversarial network (GAN) to guess passwords is a new strategy emerging in recent years, which exploits the discriminator’s evaluation of passwords to guide the update of the generator so that password guessing sets can be produced. However, the sampling process of discrete data from a categorical distribution is not differentiable so that backpropagation does not work well. In this paper, we propose a novel password guessing model named G-Pass, which consists of two main components. The first is a new network structure, which modifies the generator from the convolutional neural network (CNN) to long short-term memory- (LSTM-) based network and employs multiple convolutional layers in the discriminator to provide more informative signals for generator updating. The second is Gumbel-Softmax with temperature control for training GAN on passwords. Experimental results show the proposed G-Pass outperforms PassGAN in password quality and cracking rate. Moreover, by dynamically adjusting one parameter during the training process, a trade-off between sample diversity and quality can be achieved with our proposed model.

Excessive alcohol consumption is associated with increased morbidity and mortality, and its societal impact is substantial. The Nationwide Alcohol-related visits In Singapore Emergency departments study aims to characterise trends in ED visits involving acute and chronic alcohol consumption between 2007 and 2016.Data from the Singapore Ministry of Health, comprising all ED visits in Singapore from 2007 to 2016, were used. The data were aggregated by year and analysed for changes in prevalence and rates of ED visits for acute and chronic alcohol consumption, broken down by age, gender and ethnicity.Over the study period, the number of ED visits involving alcohol consumption increased 98.3%, from 2236 in 2007 to 4433 in 2016. During the same period, the rate per 100 000 population increased 62.4% from 48.7 to 79.1, and total ED-related costs rose by 140%, from 528 680 to 1 269 638 SGD. The increase in alcohol-related visits rates and costs was higher than non-alcohol-related visits rates and costs, which increased by 12.1% and 115% respectively. While trends in acute and chronic alcohol-related ED visits stayed stable amongst women, they rose substantially in men. Older men aged 50-69 show the highest rates and rate of increase for both acute and chronic alcohol-related ED visits.Alcohol-related visits contributed disproportionately to the increasing number of ED visits in Singapore between 2007 and 2016. Older men form the demographic with the highest rates and increase in rates of alcohol-related ED visits and form a potential group for targeted intervention.

Monoclonal antibody (mAb) based therapies may provide a valuable new treatment modality for acute and chronic lung diseases, including asthma, respiratory infections, and lung cancer. Currently mAbs are delivered via systemic administration routes, but direct delivery to the lungs via the inhaled route could provide higher concentrations at the site of disease and reduced off-target effects. Though lyophilized mAbs may be reconstituted and delivered to the lungs using nebulizers, dry powder inhalers provide a more patient-friendly delivery method based upon their fast administration time and portability. However, particle engineering processes required to prepare respirable dried powders for DPI delivery involve multiple potential stressors for mAbs, which have not been fully explored. In this study, a systematic examination of various aspects of the particle engineering process (atomization, freezing, drying, and storage) was performed to further understand their impact on mAb structure and aggregation. Using anti-streptavidin IgG1 as a model mAb, atomization settings were optimized using a design of experiments approach to elucidate the relationship between feed flow rate, formulation solid content, and atomization airflow rate and protein structural changes and aggregation. The optimized atomization conditions were then applied to spray drying and spray freezing drying particle engineering processes to determine the effects of freezing and drying on IgG1 stability and aerosol performance of the powders. IgG1 was found to be particularly susceptible to degradation induced by the expansive air-ice interface generated by spray freeze drying and this process also produced powders that exhibited decreased storage stability. This study further delineates the design space for manufacturing of respirable biologic therapies and is intended to serve as a roadmap for future development work.

The RADS process inhibits olefin hydrogenation by competitive adsorption, which is affected by temperature and Ni loading.

A programmed DNA–Au nanomachine was constructed to achieve in situ imaging of the transmembrane glycoprotein MUC1 and cytoplasmic miRNA-21 and trigger precise gene silencing therapy for breast cancer.

The high amplitude and steep overvoltage generated by the breaking of the vacuum circuit breaker in the wind farm damages the inter-turn insulation of the transformer. There is a certain difference between the simulation results of the traditional reignition model and the measured overvoltage. It is necessary to improve the simulation model to simulate the overvoltage condition of the transformer more accurately and then select appropriate overvoltage protection measures. In this paper, based on the physical process of dielectric recovery during the opening process of the vacuum circuit breaker, a model of dielectric strength recovery is built to simulate the arc reignition of the vacuum circuit breaker. The model was applied to compare the overvoltage protection effects of RC snubbers, surge arresters, and choke coils. The simulation results show that the overvoltage amplitude and reignition times calculated by the model proposed in this paper are closer to the measured values. Compared with the traditional linear curve reignition model, the accuracy was increased by 24% and 51.2%, respectively. The parameter value of RC snubbers, the connection mode of surge arresters, and the combination mode of choke coil have an influence on overvoltage suppression. Finally, a suitable suppression scheme is proposed by installing a combined arrester on the high-voltage side of the transformer and connecting a choke coil in series, which can limit the phase-to-ground voltage and the phase-to-phase voltage to 2.43 p.u and 3.24 p.u, respectively, and reduce the steepness from 157.2 kV/μs to 22.3 kV/μs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals throughout the world, which poses a serious threat to human health. COVID-19 is a systemic disease that affects tissues and organs, including the lung and liver. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. The relationship between HCC and COVID-19 has been reported in previous studies, but ICC has been rare. With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC. Transcriptional profiling of COVID-19 and ICC were obtained from the GEO database. A total of 70 common differentially expressed gene (DEGs) of both diseases were identified to investigate shared pathways. Then top-ranked 10 key DEGs (SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1) were identified as hub genes by protein-protein interaction (PPI) network analysis. In addition, transcriptional regulatory networks regulating hub genes were revealed by hub Gene-transcription factor (TF) interaction analysis and hub gene-microRNA (miRNAs) interaction analysis. This study is expected to provide new references for future research and treatment of COVID-19 and ICC.

Purpose: Diabetic retinopathy (DR) has been linked to a range of systemic risk factors, but the evidence supporting these associations is inconsistent. This study aimed to use Mendelian randomization (MR) analysis to establish genetic causal links between different risk factors and DR. Methods: The study analyzed the genetic associations between obesity, overall health status, lifestyle factors, and serum parameters with DR (n=14,584), PDR (n=8,681), and NPDR (n=2,026). Multiple MR models, multivariable MR (MVMR), and meta-analysis were used to identify significant mediators for the relationship between the risk factors and DR. Results: Genetic analysis of the 14,584 cases and 202,082 controls identified two novel genes, rs111953004 and rs9280092 on chromosome 6, with the nearest gene being HLA-DQB1 (p value of 2.146×10-160). Multiple MR models consistently showed genetic associations between obesity and DR. Overall health status, including overall rating (OR: 1.60; 95% confidence interval [CI]: 1.27-2.00), ischemic stroke (OR: 1.16; 95% CI: 1.09-1.24), and hypertension (OR: 1.07; 95% CI: 1.04-1.11) were found to increase the risk of DR. Meanwhile, moderate physical activity frequency (OR: 0.79; 95% CI: 0.68-0.92) and having a college degree (OR: 0.56; 95% CI: 0.48-0.67) were found to protect against DR according to meta-analysis. Serum parameters such as lower LDL cholesterol (OR: 0.94; 95% CI: 0.89-0.98) and higher HDL cholesterol (OR: 0.91; 95% CI: 0.88-0.94) were found to reduce the risk of DR. MVMR revealed that hypertension, coffee intake, and overall health rating were risk factors for DR. Combined meta-analysis results also suggested that alcohol consumption, coffee intake, and daytime napping might increase the risk of DR (all p Conclusions: This study established strong genetic causal links between selected risk factors and DR, which were largely mediated by obesity. Higher education level, physical activity, and better cholesterol control were associated with a decreased risk of DR.

Intrusion detection systems are crucial in fighting against various network attacks. By monitoring the network behavior in real time, possible attack attempts can be detected and acted upon. However, with the development of openness and flexibility of networks, artificial immunity-based network anomaly detection methods lack continuous adaptability and hence have poor detection performance. Thus, a novel framework for network anomaly detection with adaptive regulation is built in this paper. First, a heuristic dimensionality reduction algorithm based on unsupervised clustering is proposed. This algorithm uses the correlation between features to select the best subset. Then, a hybrid partitioning strategy is introduced in the negative selection algorithm (NSA), which divides the feature space into a grid based on the sample distribution density and generates specific candidate detectors in the boundary grid to effectively mitigate the holes caused by boundary diversity. Finally, the NSA is improved by self-set clustering and a novel gray wolf optimizer to achieve adaptive adjustment of the detector radius and position. The results show that the proposed NSA algorithm based on mixed hierarchical division and gray wolf optimization (MDGWO-NSA) achieves a higher detection rate, lower false alarm rate, and better generation quality than other network anomaly detection algorithms.