Specific emitter identification based on multiple sequence feature learning.

The specific emitter identification is widely used in electronic countermeasures, spectrum control, wireless network security and other civil and military fields. In response to the problems that the traditional specific emitter identification algorithm relies on a priori knowledge and has poor generalizability, and the existing specific emitter identification algorithm based on deep learning has poor feature selection and the adopted feature extraction network is not targeted, etc., the specific emitter identification algorithm based on multi-sequence feature learning is proposed. Firstly, multiple sequence features of the emitted signal of the communication radiation source are extracted, and these features are combined into multiple sequence features. Secondly, the multiple sequence fusion convolutional network is constructed to fuse and deeply extract the multiple sequence features and complete the classification of individual communication radiation sources through the classifier of neural network. The selected sequence features of this algorithm contain more and more essential RFF information, while the targeted design of the multi-sequence feature fusion learning network can effectively extract the essential RFF information. The results show that the algorithm can significantly improve the performance of SEI compared with the benchmark algorithm, with a recognition rate gain of about 17%.

Platelet-derived major histocompatibility complex class I coating on Treponema pallidum attenuates natural killer cell lethality.

The evasive tactics of Treponema pallidum pose a major challenge in combating and eradicating syphilis. Natural killer (NK) cells mediate important effector functions in the control of pathogenic infection, preferentially eliminating targets with low or no expression of major histocompatibility complex (MHC) class I. To clarify T. pallidum's mechanisms in evading NK-mediated immunosurveillance, experiments were performed to explore the cross-talk relations among T. pallidum, NK cells, and platelets. T. pallidum adhered to, activated, and promoted particle secretion of platelets. After preincubation with T. pallidum, platelets expressed and secreted high levels of MHC class I, subsequently transferring them to the surface of T. pallidum, potentially inducing an immune phenotype characterized by the "pseudo-expression" of MHC class I on the surface of T. pallidum (hereafter referred to a "pseudo-expression" of MHC class I). The polA mRNA assay showed that platelet-preincubated T. pallidum group exhibited a significantly higher copy number of polA transcript than the T. pallidum group. The survival rate of T. pallidum mirrored that of polA mRNA, indicating that preincubation of T. pallidum with platelets attenuated NK cell lethality. Platelets pseudo-expressed the MHC class I ligand on the T. pallidum surface, facilitating binding to killer cell immunoglobulin-like receptors with two immunoglobulin domains and long cytoplasmic tail 3 (KIR2DL3) on NK cells and initiating dephosphorylation of Vav1 and phosphorylation of Crk, ultimately attenuating NK cell lethality. Our findings elucidate the mechanism by which platelets transfer MHC class I to the T. pallidum surface to evade NK cell immune clearance.

Albumin levels and cerebral collateral circulation in patients with acute ischemic stroke due to intracranial arteriosclerotic: A propensity score-matched analysis.

Cerebral collateral circulation (CC) is associated with the recurrence and severity of acute ischemic stroke (AIS), and early identification of poor CC is helpful for the prevention of AIS. In this study we evaluated the association between serum albumin levels and CC in AIS using logistic regression. Propensity score (PS) matching was used to eliminate the effect of confounders, and restricted cubic splines (RCS) were employed to explore potential nonlinear associations between albumin and CC. In unadjusted logistic regression analysis, lower albumin (OR = 0.85, 95% CI = 0.79-0.92) was associated with poor CC, and after adjusting for covariates, the odds of lower albumin for poor CC compared to good CC were 0.86 (95% CI = 0.79-0.94). In the PS cohort, the association of albumin with CC was consistent with those of the original cohort. RCS results showed a linear relationship between albumin and CC (P values of .006 and .08 for overall and nonlinear associations, respectively). The results of this study suggest that lower serum albumin is independently associated with an increased risk of poor CC, which may serve as an effective predictive indicator for poor CC in patients with severe intracranial atherosclerotic stenosis.

Effect of cytokines on advanced hepatocellular carcinoma prognosis receiving radiotherapy and tislelizumab plus anlotinib: a single-center phase II clinical trial.

The purpose of this study was to investigate the relationship between circulating cytokines and liver function and prognosis of patients with advanced hepatocellular carcinoma (HCC) treated with radiotherapy combined with tislelizumab and anlotinib. The liver function indexes and pre-treatment levels of cytokines in 47 patients were measured by chemical method and flow cytometry. The median follow-up was 23.1 months. The objective response and the disease control rates were 46.8% and 68.1%, while overall survival (OS) and progression-free survival (PFS) were 12.6 and 11.4 months, respectively. Adverse events (2.1%) were grade 3-4. In addition to stage, intrahepatic metastasis and Child-Pugh score, pre-treatment interleukin-6 (IL-6) was the main cytokine affecting OS and PFS (p < 0.05). The OS (14.63 pg/mL as cutoff value) and PFS (9.85 pg/mL as cutoff value) of patients with low IL-6 levels exceeded those with high levels (21.0 and 6.9, 15.8 and 10.0 months, respectively). The risks of death and disease progression were reduced by 63.0% (HR = 0.37, 95% CI: 0.19-0.72) and 43.0% (HR = 0.57, 95% CI: 0.22-1.47), respectively. Pre-treatment IL-6 levels may be a simple and effective prognostic indicator for patients with advanced HCC treated with radiotherapy combined with immunotargeted therapy.

Pyridostigmine attenuates hypertension by inhibiting activation of the renin-angiotensin system in the hypothalamic paraventricular nucleus.

Activation of the renin-angiotensin system (RAS) triggers oxidative stress and an inflammatory response in the hypothalamic paraventricular nucleus (PVN), in turn increasing the sympathetic hyperactivity that is a major cause of hypertension. Pyridostigmine has cardioprotective effects by suppressing the RAS of myocardial tissue. However, whether pyridostigmine attenuates hypertension by inhibiting the RAS of the PVN remains unclear. We thus investigated the effect and mechanism of pyridostigmine on two-kidney one-clip (2K1C)-induced hypertension. 2K1C rats received pyridostigmine, or not, for 8 weeks. Cardiovascular function, hemodynamic parameters, and autonomic activity were measured. The PVN levels of pro-/anti-inflammatory cytokines, oxidative stress, and RAS signaling molecules were evaluated. Our results showed that hypertension was accompanied by cardiovascular dysfunction and an autonomic imbalance characterized by enhanced sympathetic but diminished vagal activity. The PVN levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), reactive oxygen species (ROS), NOX-2, and malondialdehyde (MDA) increased; those of IL-10 and superoxide dismutase (SOD) decreased. Moreover, the RAS signaling pathway was activated, as evidenced by increased levels of the angiotensin-converting enzyme (ACE), angiotensin II (Ang II), and the Ang II type 1 receptor (AT1R) and a decreased AT2R level. Pyridostigmine lowered blood pressure and improved cardiovascular function, associated with restoration of the autonomic balance. Meanwhile, pyridostigmine decreased PVN IL-6, TNF-α, ROS, NOX-2, and MDA levels and increased IL-10 and SOD levels. Additionally, pyridostigmine suppressed PVN ACE, Ang II, and AT1R levels and increased AT2R expression. Pyridostigmine attenuated hypertension by inhibiting PVN oxidative stress and inflammation induced by the RAS.

Anti-inflammatory effect of Trichospira verticillata via suppression of the NLRP3 inflammasome in neutrophilic asthma.

Trichospira verticillata is an annual herb that belongs to the family Asteraceae. Trichospira verticillata extract (TVE) elicits anti-plasmodial activity; however, there has been no detailed report about its anti-inflammatory effects and molecular mechanisms. In addition, herbal plants exhibit anti-inflammatory effects by suppressing the NLRP3 inflammasome. Therefore, the primary goal of this study was to examine the effects of TVE on NLRP3 inflammasome activation by measuring interleukin-1ß (IL-1ß) secretion. We treated lipopolysaccharides (LPS)-primed J774A.1 and THP-1 cells with TVE, which attenuated NLRP3 inflammasome activation. Notably, TVE did not affect nuclear factor-kappa B (NF-κB) signalling or intracellular reactive oxygen species (ROS) production and potassium efflux, suggesting that it inactivates the NLRP3 inflammasome via other mechanisms. Moreover, TVE suppressed the formation of apoptosis-associated speck-like protein (ASC) speck and oligomerization. Immunoprecipitation data revealed that TVE reduced the binding of NLRP3 to NIMA-related kinase 7 (NEK7), resulting in reduced ASC oligomerization and speck formation. Moreover, TVE alleviated neutrophilic asthma (NA) symptoms in mice. This study demonstrates that TVE modulates the binding of NLPR3 to NEK7, thereby reporting novel insights into the mechanism by which TVE inhibits NLRP3 inflammasome. These findings suggest TVE as a potential therapeutic of NLRP3 inflammasome-mediated diseases, particularly NA.

Construction of ß-Oximino Phosphorodithioates via (2,2,6,6-Tetramethylpiperidin-1-yl)oxyl-Promoted Difunctionalization of Alkenes with tert-Butyl Nitrite, P4S10, and Alcohols.

A (2,2,6,6-tetramethylpiperidin-1-yl)oxyl-mediated difunctionalization of alkenes with tert-butyl nitrite, P4S10, and alcohols has been developed for the synthesis of ß-oximino phosphorodithioates. The reaction goes through a radical pathway with the successive installation of phosphorodithioate and an oxime group. This four-component protocol offers a practical approach to constructing a variety of ß-oximino phosphorodithioates in moderate to good yields with favorable functional group tolerance.

Orthogonality of non-coaxial Laguerre-Gaussian beams.

The conventional orthogonality of Laguerre-Gaussian (LG) beams is widely recognized and serves as the fundamental basis for mode division multiplexing utilizing LG beams as channels. However, this conventional orthogonality holds true only when two LG beams share the same axis. Whether non-coaxial LG beams, with parallel axes separated by a distance, are orthogonal to each other remains an open question. To address this issue and reveal the orthogonality of non-coaxial LG beams, we analytically derive the projection of one LG beam onto another. This projection exhibits a helical phase and a rotationally symmetric amplitude with dark rings present. These dark rings indicate that two non-coaxial LG beams are indeed orthogonal to each other when their axes are appropriately separated. Furthermore, any pair of non-coaxial LG beams within a set also exhibit orthogonality when their axes are fixed at a certain separation distance. This novel form of orthogonality predicts an innovative compound multiplexing technique that simultaneously combines mode and space, enabling more efficient packing of multiple LG beams within a single transmission aperture while maintaining parallel and closely spaced beam axes.

Recent Advances in Synergistic Effect of Nanoparticles and Its Biomedical Application.

The synergistic impact of nanomaterials is critical for novel intracellular and/or subcellular drug delivery systems of minimal toxicity. This synergism results in a fundamental bio/nano interface interaction, which is discussed in terms of nanoparticle translocation, outer wrapping, embedding, and interior cellular attachment. The morphology, size, surface area, ligand chemistry and charge of nanoparticles all play a role in translocation. In this review, we suggest a generalized mechanism to characterize the bio/nano interface, as we discuss the synergistic interaction between nanoparticles and cells, tissues, and other biological systems. Novel perceptions are reviewed regarding the ability of nanoparticles to improve hybrid nanocarriers with homogeneous structures to enhance multifunctional biomedical applications, such as bioimaging, tissue engineering, immunotherapy, and phototherapy.

The value of audiovisual sexual stimulation with virtual reality in diagnosing erectile dysfunction.

Background: The traditional audiovisual sexual stimulation (AVSS) test may experience limitations including low erectile response rate and lack of unified diagnostic criteria. Aim: We aimed to explore the clinical value of AVSS with virtual reality (VR-AVSS) test in assessing erectile function and diagnosing erectile dysfunction (ED). Methods: Participants 18 to 60 years of age were screened for analysis in 3 clinical centers from June 2020 to March 2022. Demographic data, 5-item International Index of Erectile Function (IIEF-5), erectile hardness score (EHS), and self-reported symptom questions were collected. The ED patients and control patients were confirmed according to the IIEF-5 and EHS. All subjects watched a 60-minute erotic video by VR device during RigiScan recording. The parameters including tip average rigidity, tip effective erectile duration (duration of rigidity ≥60%, tip effective erectile duration), base average rigidity, and base effective erectile duration were evaluated. Outcomes: The main outcome of interest was the application of VR immersion technology to improve the traditional AVSS test. Results: A total of 301 ED cases and 100 eligible control patients were included for final analysis. Compared with control patients, ED cases had significantly lower IIEF-5 scores, EHS, positive response rate, and erectile rigidity and duration. The positive response rate of ED and control patients were 75.5% and 90.9%, respectively. The cutoff points of tip average rigidity, tip effective erectile duration, base average rigidity, and base effective erectile duration were 40.5% (sensitivity: 77.6%, specificity: 70.2%; P < .001), 4.75 minutes (sensitivity: 75.9%, specificity: 75.4%; P < .001), 48.5% (sensitivity: 77.6%, specificity: 75.1%; P < .001), and 7.75 minutes (sensitivity: 79.3%, specificity: 75.7%; P < .001). Clinical Implications: The technological superiority of VR will enable the VR-AVSS immersion test to be a more accurate detection than traditional AVSS modes. Strengths and Limitations: Our study applied VR immersion technology to establish the standard operation procedure for the AVSS test, which could effectively reduce the interference of adverse factors and minimize the detecting errors. However, the test data only included positive response subjects, so the true erectile status of men with a negative response to the AVSS test cannot be obtained. Conclusions: The VR-AVSS test can effectively improve the diagnostic accuracy of ED. The average rigidity and effective erectile duration were the optimal diagnostic parameters for excluding ED.

Visible-Light-Promoted Cascade Coupling of 2-Isocyanonaphthalenes with Elemental Sulfur and Amines to Construct Naphtho[2,1-d]thiazol-2-Amines.

A visible-light-induced strategy has been explored for the synthesis of naphtho[2,1-d]thiazol-2-amines through ortho-C-H sulfuration of 2-isocyanonaphthalenes with elemental sulfur and amines under external photocatalyst-free conditions. This three-component reaction, which utilizes elemental sulfur as the odorless sulfur source, molecular oxygen as the clean oxidant, and visible light as the clean energy source, provides a mild and efficient approach to construct a series of naphtho[2,1-d]thiazol-2-amines. Preliminary mechanistic studies indicated that visible-light-promoted photoexcitation of reaction intermediates consisting of thioureas and DBU might be involved in this transformation.

[Effects of Land Use Types on Water Quality at Different Buffer Scales: Tianjin Section of the Haihe River Basin as an Example].

It is important to explore the relationship between land use types and water quality to improve the surface water environment. Based on monthly water quality monitoring data from 16 nationally controlled surface water quality monitoring stations in Tianjin and land use data in 2021, GIS spatial analysis and mathematical and statistical methods were used to study the influence of land use types on surface water quality in buffer zones at different scales. The results showed that:① the land use types in the study area were mainly construction land, farmland, and water areas, which had significant effects on river water quality. Except for water temperature (WT) and pH, the farmland, construction land, and water areas were negatively correlated with each water quality indicator; forest land and grassland were positively correlated with dissolved oxygen (DO) and total nitrogen (TN) and negatively correlated with other water quality indicators. ② The water quality indicators showed obvious spatial differences in different seasons. The pH, DO and TN concentrations were higher in the dry season, whereas the permanganate index, ammonia nitrogen (NH4+-N), and total phosphorus (TP) concentrations were higher in the rainy season. ③ The results of the RDA analysis showed that the 800 m buffer zone land use had the greatest explanatory power for water quality changes in the dry season (50.4%), whereas the 3 000 m buffer zone land use could explain the water quality changes in the rainy season to the greatest extent (49.6%); from the average explanation rate of the dry and rainy seasons, the 3 000 m buffer zone was the best impact scale (50.0%) on water quality indicators in Tianjin. ④ The partial least squares regression (PLSR) analysis showed that the most important variables affecting surface water quality changes were construction land, farmland, and water areas. The predictive ability of the PLSR model of most water quality indicators was stronger in the dry season than that in the rainy season. In the dry season, all water quality indicators, except WT and pH, were most influenced by farmland. In the rainy season, construction land had the greatest influence on WT and NH4+-N concentrations, and the most important influencing factor for the remaining water quality indicators was still farmland. This study showed that the rational planning of land use types within 3 000 m of rivers or lakes was beneficial to improving the water quality of surface water.

Aiouea padiformis extract exhibits anti-inflammatory effects by inhibiting the ATPase activity of NLRP3.

Inflammation is implicated as a cause in many diseases. Most of the anti-inflammatory agents in use are synthetic and there is an unmet need for natural substance-derived anti-inflammatory agents with minimal side effects. Aiouea padiformis belongs to the Lauraceae family and is primarily found in tropical regions. While some members of the Aiouea genus are known to possess anti-inflammatory properties, the anti-inflammatory properties of Aiouea padiformis extract (AP) have not been investigated. In this study, we aimed to examine the anti-inflammatory function of AP through the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome and elucidate the underlying mechanisms. Treatment with AP inhibited the secretion of interleukin-1 beta (IL-1ß) mediated by NLRP3 inflammasome in J774A.1 and THP-1 cells without affecting the viability. In addition, AP treatment did not influence NF-κB signaling, potassium efflux, or intracellular reactive oxygen species (ROS) production-all of which are associated with NLRP3 inflammasome activation. However, intriguingly, AP treatment significantly reduced the ATPase activity of NLRP3, leading to the inhibition of ASC oligomerization and speck formation. Consistent with cellular experiments, the anti-inflammatory property of AP in vivo was also evaluated using an LPS-induced inflammation model in zebrafish, demonstrating that AP hinders NLRP3 inflammasome activation.

Choroid plexus and its relations with age-related diseases.

The choroid plexus is composed of epithelial cells situated on the basal layer. The tight junctions between adjacent choroid plexus epithelial cells establish the blood-cerebrospinal fluid barrier. This barrier, in conjunction with the blood-brain barrier, is crucial for the homeostasis of the brain microenvironment. The choroid plexus epithelium secretes cerebrospinal fluid, growth factors, neuropeptides, and lipids into the ventricles and also serves as a gateway for immune cells to enter the brain. The pathophysiology of aging and neurodegenerative diseases remains largely enigmatic, with an increasing body of research linking the choroid plexus to the etiology of these age-related disorders. In this review, we summarize the known relationship between the choroid plexus epithelium and age-related diseases, aiming to provide new therapeutic clues for these disorders.

Systematic Analysis of the MIO-forming Residues of Aromatic Ammonia Lyases.

Aromatic ammonia lyases (AALs) and tyrosine/phenylalanine ammonia mutases (TAM/PAM) are 3,5-dihydro-5-methylidene-4H-imidazol-4-one (MIO)-dependent enzymes. Usually, the MIO moiety is autocatalytically formed from the tripeptide Ala-Ser-Gly (ASG) and acts as an electrophile during the enzymatic reaction. However, the MIO-forming residues (ASG) have some diversity in this enzyme class. In this work, a systematic investigation on the variety of MIO-forming residues was carried out using in-depth sequence analyses. Several protein clusters of AAL-like enzymes with unusual MIO-forming residues such as ACG, TSG, SSG, and CSG were identified, including two novel histidine ammonia lyases and one PAM with CSG and TSG residues, respectively, as well as three novel ergothioneine trimethylammonia lyases without MIO motif. The mutagenesis of common MIO-groups confirmed the function of these MIO variants, which provides good starting points for future functional prediction and mutagenesis research of AALs.

Single image super-resolution with denoising diffusion GANS.

Single image super-resolution (SISR) refers to the reconstruction from the corresponding low-resolution (LR) image input to a high-resolution (HR) image. However, since a single low-resolution image corresponds to multiple high-resolution images, this is an ill-posed problem. In recent years, generative model-based SISR methods have outperformed conventional SISR methods in performance. However, the SISR methods based on GAN, VAE, and Flow have the problems of unstable training, low sampling quality, and expensive computational cost. These models also struggle to achieve the trifecta of diverse, high-quality, and fast sampling. In particular, denoising diffusion probabilistic models have shown impressive variety and high quality of samples, but their expensive sampling cost prevents them from being well applied in the real world. In this paper, we investigate the fundamental reason for the slow sampling speed of the SISR method based on the diffusion model lies in the Gaussian assumption used in the previous diffusion model, which is only applicable for small step sizes. We propose a new Single Image Super-Resolution with Denoising Diffusion GANS (SRDDGAN) to achieve large-step denoising, sample diversity, and training stability. Our approach combines denoising diffusion models with GANs to generate images conditionally, using a multimodal conditional GAN to model each denoising step. SRDDGAN outperforms existing diffusion model-based methods regarding PSNR and perceptual quality metrics, while the added latent variable Z solution explores the diversity of likely HR spatial domain. Notably, the SRDDGAN model infers nearly 11 times faster than diffusion-based SR3, making it a more practical solution for real-world applications.

Combating antimicrobial resistance: the silent war.

Once hailed as miraculous solutions, antibiotics no longer hold that status. The excessive use of antibiotics across human healthcare, agriculture, and animal husbandry has given rise to a broad array of multidrug-resistant (MDR) pathogens, posing formidable treatment challenges. Antimicrobial resistance (AMR) has evolved into a pressing global health crisis, linked to elevated mortality rates in the modern medical era. Additionally, the absence of effective antibiotics introduces substantial risks to medical and surgical procedures. The dwindling interest of pharmaceutical industries in developing new antibiotics against MDR pathogens has aggravated the scarcity issue, resulting in an exceedingly limited pipeline of new antibiotics. Given these circumstances, the imperative to devise novel strategies to combat perilous MDR pathogens has become paramount. Contemporary research has unveiled several promising avenues for addressing this challenge. The article provides a comprehensive overview of these innovative therapeutic approaches, highlighting their mechanisms of action, benefits, and drawbacks.

Deep evolutionary fusion neural network: a new prediction standard for infectious disease incidence rates.

BACKGROUND: Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research. RESULTS: The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575. CONCLUSIONS: We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases.

Identification of associated risk factors for serological distribution of hepatitis B virus via machine learning models.

BACKGROUND: The provincial-level sero-survey was launched to learn the updated seroprevalence of hepatitis B virus (HBV) infection in the general population aged 1-69 years in Chongqing and to assess the risk factors for HBV infection to effectively screen persons with chronic hepatitis B (CHB). METHODS: A total of 1828 individuals aged 1-69 years were investigated, and hepatitis B surface antigen (HBsAg), antibody to HBsAg (HBsAb), and antibody to B core antigen (HBcAb) were detected. Logistic regression and three machine learning (ML) algorithms, including random forest (RF), support vector machine (SVM), and stochastic gradient boosting (SGB), were developed for analysis. RESULTS: The HBsAg prevalence of the total population was 3.83%, and among persons aged 1-14 years and 15-69 years, it was 0.24% and 4.89%, respectively. A large figure of 95.18% (770/809) of adults was unaware of their occult HBV infection. Age, region, and immunization history were found to be statistically associated with HBcAb prevalence with a logistic regression model. The prediction accuracies were 0.717, 0.727, and 0.725 for the proposed RF, SVM, and SGB models, respectively. CONCLUSIONS: The logistic regression integrated with ML models could helpfully screen the risk factors for HBV infection and identify high-risk populations with CHB.