The reversal of PXR or PPARα activation-induced hepatomegaly.

The activation of pregnane X receptor (PXR) or peroxisome proliferator-activated receptor α (PPARα) can induce liver enlargement. Recently, we reported that PXR or PPARα activation-induced hepatomegaly depends on yes-associated protein (YAP) signaling and is characterized by hepatocyte hypertrophy around the central vein area and hepatocyte proliferation around the portal vein area. However, it remains unclear whether PXR or PPARα activation-induced hepatomegaly can be reversed after the withdrawal of their agonists. In this study, we investigated the regression of enlarged liver to normal size following the withdrawal of PCN or WY-14643 (typical agonists of mouse PXR or PPARα) in C57BL/6 mice. The immunohistochemistry analysis of CTNNB1 and KI67 showed a reversal of hepatocyte size and a decrease in hepatocyte proliferation after the withdrawal of agonists. In details, the expression of PXR or PPARα downstream proteins (CYP3A11, CYP2B10, ACOX1, and CYP4A) and the expression of proliferation-related proteins (CCNA1, CCND1, and PCNA) returned to the normal levels. Furthermore, YAP and its downstream proteins (CTGF, CYR61, and ANKRD1) also restored to the normal states, which was consistent with the change in liver size. These findings demonstrate the reversibility of PXR or PPARα activation-induced hepatomegaly and provide new data for the safety of PXR and PPARα as drug targets.

A novel model combining genes associated with disulfidptosis and glycolysis to predict breast cancer prognosis, molecular subtypes, and treatment response.

Breast cancer (BC) is a heterogeneous malignancy with a dismal prognosis. Disulfidptosis is a novel type of regulated cell death that happens in the presence of glucose deficiency and is linked to the metabolic process of glycolysis. However, the mechanism of action of disulfidptosis and glycolysis-related genes (DGRG) in BC, as well as their prognostic value in BC patients, remain unknown. After identifying the differentially expressed DGRG in normal and BC tissues, a number of machine learning algorithms were utilized to select essential prognostic genes to develop a model, including SLC7A11, CACNA1H, SDC1, CHST1, and TFF3. The expression characteristics of these genes were then examined using single-cell RNA sequencing, and BC was classified into three clusters using "ConsensusClusterPlus" based on these genes. The DGRG model's median risk score can categorize BC patients into high-risk and low-risk groups. Furthermore, we investigated variations in clinical landscape, immunoinvasion analysis, tumor immune dysfunction and rejection (TIDE), and medication sensitivity in patients in the DGRG model's high- and low-risk groups. Patients in the low-risk group performed better on immunological and chemotherapeutic therapies and had lower TIDE scores. In conclusion, the DGRG model we developed has significant clinical application potential because it can accurately predict the prognosis of BC, TME, and pharmacological treatment responses.

CAR and PPARα do not perform liquid-liquid phase separation in cells.

Constitutive androstane receptor (CAR) and peroxisome proliferator-activated receptor α (PPARα) are members of the nuclear receptor superfamily, which regulates various physiological and pathological processes. Phase separation is a dynamic biophysical process that biomacromolecules form liquid-like condensates, which have been identified as a contributor to many cellular functions, such as signal transduction and transcription regulation. However, the possibility of phase separation for CAR and PPARα remains unknown. This study explored the potential phase separation of CAR and PPARα. The computational analysis utilizing algorithms tools examining the intrinsically disordered regions (IDRs) of CAR and PPARα suggested a limited likelihood of undergoing phase separation. Experimental assays under varying conditions of hyperosmotic stress and agonist treatments confirmed the absence of phase separation for these receptors. Additionally, the optoDroplets assay, which utilizes blue light stimulation to induce condensate formation, showed that there was no condensate formation of the fusion protein of Cry2 with CAR or PPARα. Furthermore, phase separation of CAR or PPARα did not occur despite reduced target expression under hyperosmotic stress. In conclusion, these findings revealed that neither the activation of CAR and PPARα nor hyperosmotic stress induces phase separation of CAR and PPARα in cells. Significance Statement CAR and PPARα are key regulators of various functions in the body. This study showed that CAR and PPARα do not exhibit phase separation under hyperosmotic stress or after agonist-induced activation. These findings provide new insights into the CAR and PPARα biology and physiology.

Multi-View Time-Series Hypergraph Neural Network for Action Recognition.

Recently, action recognition has attracted considerable attention in the field of computer vision. In dynamic circumstances and complicated backgrounds, there are some problems, such as object occlusion, insufficient light, and weak correlation of human body joints, resulting in skeleton-based human action recognition accuracy being very low. To address this issue, we propose a Multi-View Time-Series Hypergraph Neural Network (MV-TSHGNN) method. The framework is composed of two main parts: the construction of a multi-view time-series hypergraph structure and the learning process of multi-view time-series hypergraph convolutions. Specifically, given the multi-view video sequence frames, we first extract the joint features of actions from different views. Then, limb components and adjacent joints spatial hypergraphs based on the joints of different views at the same time are constructed respectively, temporal hypergraphs are constructed joints of the same view at continuous times, which are established high-order semantic relationships and cooperatively generate complementary action features. After that, we design a multi-view time-series hypergraph neural network to efficiently learn the features of spatial and temporal hypergraphs, and effectively improve the accuracy of skeleton-based action recognition. To evaluate the effectiveness and efficiency of MV-TSHGNN, we conduct experiments on NTU RGB+D, NTU RGB+D 120 and imitating traffic police gestures datasets. The experimental results indicate that our proposed method model achieves the new state-of-the-art performance.

Brain delivery of fibronectin through bioactive phosphorous dendrimers for Parkinson's disease treatment via cooperative modulation of microglia.

Effective treatment of Parkinson's disease (PD), a prevalent central neurodegenerative disorder particularly affecting the elderly population, still remains a huge challenge. We present here a novel nanomedicine formulation based on bioactive hydroxyl-terminated phosphorous dendrimers (termed as AK123) complexed with fibronectin (FN) with anti-inflammatory and antioxidative activities. The created optimized AK123/FN nanocomplexes (NCs) with a size of 223 nm display good colloidal stability in aqueous solution and can be specifically taken up by microglia through FN-mediated targeting. We show that the AK123/FN NCs are able to consume excessive reactive oxygen species, promote microglia M2 polarization and inhibit the nuclear factor-kappa B signaling pathway to downregulate inflammatory factors. With the abundant dendrimer surface hydroxyl terminal groups, the developed NCs are able to cross blood-brain barrier (BBB) to exert targeted therapy of a PD mouse model through the AK123-mediated anti-inflammation for M2 polarization of microglia and FN-mediated antioxidant and anti-inflammatory effects, thus reducing the aggregation of α-synuclein and restoring the contents of dopamine and tyrosine hydroxylase to normal levels in vivo. The developed dendrimer/FN NCs combine the advantages of BBB-crossing hydroxyl-terminated bioactive per se phosphorus dendrimers and FN, which is expected to be extended for the treatment of different neurodegenerative diseases.

Assessing patient information needs for new antidiabetic medications to inform shared decision-making: A best-worst scaling experiment in China.

BACKGROUND: Shared decision-making (SDM) is a patient-centred approach to improve the quality of care. An essential requirement for the SDM process is to be fully aware of patient information needs. OBJECTIVES: Our study aimed to assess patient information needs for new antidiabetic medications using the best-worst scaling (BWS) experiment. METHODS: BWS tasks were developed according to a literature review and the focus group discussion. We used a balanced incomplete block design and blocking techniques to generate choice sets. The final BWS contains 11 attributes, with 6-choice scenarios in each block. The one-to-one, face-to-face BWS survey was conducted among type 2 diabetic patients in Jiangsu Province. Results were analyzed using count-based analysis and modelling approaches. We also conducted a subgroup analysis to observe preference heterogeneity. RESULTS: Data from 539 patients were available for analysis. The most desired information domain was the comparative effectiveness of new antidiabetic medications. It consists of the incidence of macrovascular complications, the length of extended life years, changes in health-related quality of life, the incidence of microvascular complications, and the control of glycated haemoglobin. Of all the attributes, the incidence of macrovascular complications was the primary concern. Patients' glycemic control and whether they had diabetes complications exerted a significant influence on their information needs. CONCLUSIONS: Information on health benefits is of critical significance for diabetic patients. Patients have different information needs as their disease progresses. Personalized patient decision aids that integrate patient information needs and provide evidence of new antidiabetic medications are worthy of being established. PATIENT OR PUBLIC CONTRIBUTION: Before data collection, a pilot survey was carried out among diabetic patients to provide feedback on the acceptability and intelligibility of the attributes.

Procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 promotes collagen cross-linking and ECM stiffening to induce liver fibrosis.

Procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 (Plod2) is a key collagen lysyl hydroxylase mediating the formation of collagen fiber and stabilized collagen cross-links, and has been identified in several forms of fibrosis. However, the potential role and regulatory mechanism of Plod2 in liver fibrosis remain unclear yet. Mouse liver fibrosis models were induced by injecting carbon tetrachloride (CCl4) intraperitoneally. The morphology and alignment of collagen was observed under transmission and scanning electron microscopy, and extracellular matrix (ECM) stiffness was measured by atomic force microscopy. Large amounts of densely packed fibrillar collagen fibers produced by myofibroblasts (MFs) were deposited in fibrotic liver of mice reaching very large diameters in the cross section, accompanied with ECM stiffening, which was positively correlated with collagen-crosslinking. The expression of Plod2 was dynamically up-regulated in fibrotic liver of mouse and human. In MFs transfection of Plod2 siRNA made collagen fibers more orderly and linear aligned which can be easily degraded and protected from ECM stiffness. Administration of Plod2 siRNA preventatively or therapeutically in CCl4 mice reduced the average size of collagen bundles in transverse section, increased collagen solubility, decreases the levels of crosslinking products hydroxylysylpyridinoline and lysylpyridinoline, prevented ECM stiffening and alleviated liver fibrosis. Altogether, Plod2 mediates the formation of stabilized profibrotic collagen cross-links in MFs, leading to the alteration of collagen solubility and ECM stiffness, and eventually aggravates liver fibrosis, which provide potential target for the treatment of liver disease.

Highly Flexible and Superelastic Graphene Nanofibrous Aerogels for Intelligent Sign Language.

Highly flexible and superelastic aerogels at large deformation have become urgent mechanical demands in practical uses, but both properties are usually exclusive. Here a trans-scale porosity design is proposed in graphene nanofibrous aerogels (GNFAs) to break the trade-off between high flexibility and superelasticity. The resulting GNFAs can completely recover after 1000 fatigue cycles at 60% folding strain, and notably maintain excellent structural integrity after 10000 cycles at 90% compressive strain, outperforming most of the reported aerogels. The mechanical robustness is demonstrated to be derived from the trans-scale porous structure, which is composed of hyperbolic micropores and porous nanofibers to enable the large elastic deformation capability. It is further revealed that flexible and superelastic GNFAs exhibit high sensitivity and ultrastability as an electrical sensors to detect tension and flexion deformation. As proof, The GNFA sensor is implemented onto a human finger and achieves the intelligent recognition of sign language with high accuracy by multi-layer artificial neural network. This study proposes a highly flexible and elastic graphene aerogel for wearable human-machine interfaces in sensor technology.

New alkaloids from Stemona tuberosa and structural revision of tuberostemonols P and R.

Three Stemona alkaloids named stemotuberines A-C (1-3) with unique C17N frameworks, presumably formed by elimination of the C-11-C-15 lactone ring of the stichoneurine skeleton, were isolated from the roots of Stemona tuberosa. Their structures were elucidated by spectroscopic analysis, X-ray diffraction, and computational methods. Compounds 2 and 3 showed inhibition (IC50 values of 37.1 and 23.2 µM, respectively) against LPS-induced nitric oxide production in RAW 264.7 cells. In addition, concern was expressed about the reported plant origin (S. sessilifolia) of the recently described alkaloids tuberostemonols O-R (4-7), which should be S. tuberosa. NMR calculations indicated structural misassignment of these compounds except for 6. Isolation of tuberostemonol P (5) from our material of S. tuberosa allowed for a close examination of the spectroscopic data leading to the revised structure 5a. Tuberostemonol R (7) was found to have identical 1H and 13C NMR data to the well-known alkaloid croomine, and therefore its structure including relative stereochemistry must be revised as 7a.

Medicinal cannabis oil improves anxiety-like and depressive-like behaviors in CCS mice via the BDNF/TRPC6 signaling pathway.

BACKGROUND: Post-traumatic stress disorder (PTSD) refers to a chronic impairing psychiatric disorder occurring after exposure to the severe traumatic event. Studies have demonstrated that medicinal cannabis oil plays an important role in neuroprotection, but the mechanism by which it exerts anti-PTSD effects remains unclear. METHODS: The chronic complex stress (CCS) simulating the conditions of long voyage stress for 4 weeks was used to establish the PTSD mice model. After that, behavioral tests were used to evaluate PTSD-like behaviors in mice. Mouse brain tissue index was detected and hematoxylin-eosin staining was used to assess pathological changes in the hippocampus. The indicators of cell apoptosis and the BDNF/TRPC6 signaling activation in the mice hippocampus were detected by western blotting or real-time quantitative reverse transcription PCR experiments. RESULTS: We established the PTSD mice model induced by CCS, which exhibited significant PTSD-like phenotypes, including increased anxiety-like and depression-like behaviors. Medicinal cannabis oil treatment significantly ameliorated PTSD-like behaviors and improved brain histomorphological abnormalities in CCS mice. Mechanistically, medicinal cannabis oil reduced CCS-induced cell apoptosis and enhanced the activation of BDNF/TRPC6 signaling pathway. CONCLUSIONS: We constructed a PTSD model with CCS and medicinal cannabis oil that significantly improved anxiety-like and depressive-like behaviors in CCS mice, which may play an anti-PTSD role by stimulating the BDNF/TRPC6 signaling pathway.

Assessing right ventricular peak strain in myocardial infarction patients with mitral regurgitation by cardiac magnetic resonance feature tracking.

Background: Although it is known that mitral regurgitation (MR) in patients with myocardial infarction (MI) may increase the right ventricular (RV) afterload, leading to RV dysfunction, the exact detrimental effects on RV function and myocardial peak strain remain unresolved. In this study, we assessed the impact of MR on the impairment of RV myocardial deformation in patients with MI and explored the independent influential factors of RV peak strain. Methods: A total of 199 MI participants without or with MR were retrospectively assessed in this study. The cardiovascular magnetic resonance examination protocol included a late gadolinium-enhanced (LGE) imaging technique and a cine-balanced steady-state free precession sequence. Statistical tests, including two independent sample t-test or Mann-Whitney U-test, analysis of variance, Kruskal-Wallis test, and multiple linear regression analysis models were performed. Results: The MI (MR+) group exhibited significantly lower RV strain parameters in the radial, circumferential and longitudinal directions when compared to the control and the MI (MR-) groups (both P<0.05). The RV global longitudinal peak strain (GLPS) in the MI group significantly decreased when compared with that in the control group (P<0.05). As moderate-severe MR worsened in patients with MI, RV myocardial global peak strain and the peak systolic strain rate (PSSR) gradually decreased. Multiple linear regression analysis revealed that left ventricular (LV) GLPS, triglycerides, and age were independently correlated with RV GLPS (all P<0.05). RV end-systolic volume (RVESV) acted as an independent association factor for RV global peak strain. Conclusions: MR may exacerbate the impairment of RV peak strain and functions in patients with MI. LV GLPS was positively correlated with RV GLPS. However, RVESV, triglycerides, and age acted as independent risk factors associated with worsening RV GLPS.

Effects of As8 structure formation on the surface morphology and internal microstructure of GaAs thin films.

Gallium arsenide (GaAs) materials have the advantages of high electron mobility, electron saturation drift rate, and other irreplaceable semiconducting properties. They play an important role in the electronics, solar and other fields. However, during GaAs film sedimentary growth, As atoms can undergo segregation to form As8 clusters because of the influence of external factors, which affect the surface morphology and internal structure of these films. In this study, a series of investigations on the deposition and growth of GaAs crystal films were performed. Additionally, the deposition and growth of GaAs thin films were simulated using molecular dynamics. The influence of As8 clusters on the surface morphology and internal structure of GaAs films at different incidence angles, velocities and substrate temperatures was studied by using "defect analysis technology" and "diamond structure identification" in open source software, along with surface roughness and radial distribution function. Results show that with increasing incident angle, the number of As8 clusters decreases and film density increases. Increasing incident velocity increases the irregular movement of As8 clusters in air, and their deposition on the film surface affects the morphology of the film, the surface roughness increases first and then decreases. Additionally, we investigated the effect of different substrate temperatures on the film surface. Results show that at a substrate temperature of 1173 K, the number of As8 clusters in the film decreases or the As8 clusters disappear, heterogeneous nucleation occurs in the film, and the crystallization rate increases. Although the dislocation line associated with nucleation may affect the mechanical and optical properties of the film, it considerably reduces the annealing effort after the deposition and growth.

Untargeted metabolomics reveals intervention effects of wine-processed Schisandra chinensis polysaccharide on Alzheimer's disease mice.

Schisandra chinensis (Turcz.) Baill (SC) is a traditional sedative in China, with wide applications for treating various neurological disorders. Its polysaccharide component has been gaining increased attention for its potential in nerve protection. While raw SC is the primary focus of current research, its processed products are primarily utilized as clinical medicines. Notably, limited research exists on the mechanisms underlying the effects of wine-processed Schisandra chinensis polysaccharide (WSCP) in Alzheimer's Disease (AD). Therefore, this study seeks to assess the therapeutic impact of WSCP on AD mice and investigate the underlying mechanisms through biochemical and metabolomics analyses. The results demonstrate that WSCP exerts significant therapeutic effects on AD mice by enhancing learning and memory abilities, mitigating hippocampal neuronal damage, reducing abnormal amyloid-beta (Aß) deposition, and attenuating hyperphosphorylation of Tau. Biochemical analysis revealed that WSCP can increase SOD content and decrease MDA, IL-6, and TNF-α content in AD mice. Furthermore, serum metabolomic results showed that WSCP intervention can reverse metabolic disorders in AD mice. 43 endogenous metabolites were identified as potential biomarkers for WSCP treatment of AD, and the major metabolic pathways were Ala, Glu and Asp metabolism, TCA cycle. Overall, these findings will provide a basis for further development of WSCP.

TDDFT Study on the ESIPT Properties of 2-(2'-Hydroxyphenyl)-Benzothiazole and Sensing Mechanism of a Derived Fluorescent Probe for Fluoride Ion.

The level of fluoride ions (F-) in the human body is closely related to various pathological and physiological states, and the rapid detection of F- is important for studying physiological processes and the early diagnosis of diseases. In this study, the detailed sensing mechanism of a novel high-efficiency probe (PBT) based on 2-(2'-hydroxyphenyl)-benzothiazole derivatives towards F- has been fully investigated based on density functional theory (DFT) and time-dependent density functional theory (TDDFT) methods. F- attacks the O-P bond of PBT to cleavage the dimethylphosphinothionyl group, and the potential products were evaluated by Gibbs free energy and spectroscopic analyses, which ultimately identified the product as HBT-Enol1 with an intramolecular hydrogen bond. Bond parameters, infrared vibrational spectroscopy and charge analysis indicate that the hydrogen bond is enhanced at the excited state (S1), favoring excited state intramolecular proton transfer (ESIPT). The mild energy barrier further evidences the occurrence of ESIPT. Combined with frontier molecular orbital (FMO) analysis, the fluorescence quenching of PBT was attributed to the photoinduced electron transfer (PET) mechanism and the fluorescence turn-on mechanism of the product was attributed to the ESIPT process of HBT-Enol1.

The additive effect of metabolic syndrome on left ventricular impairment in patients with obstructive coronary artery disease assessed by 3.0 T cardiac magnetic resonance feature tracking.

BACKGROUND: Metabolic syndrome (MetS) can increase the risk of morbidity and mortality of cardiovascular disease and obstructive coronary artery disease (OCAD), which usually have a poor prognosis. This study aimed to explore the impact of MetS on left ventricular (LV) deformation and function in OCAD patients and investigate the independent factors of impaired LV function and deformation. MATERIALS AND METHODS: A total of 121 patients with OCAD and 52 sex- and age-matched controls who underwent cardiac magnetic resonance scanning were enrolled in the study. All OCAD patients were divided into two groups: OCAD with MetS [OCAD(MetS+), n = 83] and OCAD without MetS [OCAD(MetS-), n = 38]. LV functional and global strain parameters were measured and compared among the three groups. Multivariable linear regression analyses were constructed to investigate the independent factors of LV impairment in OCAD patients. Logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to test the prediction efficiency of MetS for LV impairment. RESULTS: From controls to the OCAD(MetS-) group to the OCAD(MetS+) group, LV mass (LVM) increased, and LV global function index (LVGFI) and LV global longitudinal peak strain (GLPS) decreased (all p < 0.05). Compared with the OCAD(MetS-) group, the LV GLPS declined significantly (p = 0.027), the LVM increased (p = 0.006), and the LVGFI decreased (p = 0.043) in the OCAD(MetS+) group. After adjustment for covariates in OCAD patients, MetS was an independent factor of decreased LV GLPS (ß = - 0.211, p = 0.002) and increased LVM (ß = 0.221, p = 0.003). The logistic multivariable regression analysis and ROC analysis showed that combined MetS improved the efficiency of predicting LV GLPS reduction (AUC = 0.88) and LVM (AUC = 0.89) increase. CONCLUSIONS: MetS aggravated the damage of LV deformation and function in OCAD patients and was independently associated with LV deformation and impaired LV strain. Additionally, MetS increased the prediction efficiency of increased LVM and decreased LV GLPS. Early detection and intervention of MetS in patients with OCAD is of great significance.

Iodine-induced synthetic method and pharmacokinetic study of cis- and trans-crocetin.

Objective: This experiment aimed to obtain the relatively rare cis-crocetin isomer from natural plants, which predominantly exist in the more stable all-trans configuration. This was achieved through iodine-induced isomerization, followed by purification and structural identification. The study also aimed to compare the pharmacokinetic differences between cis- and trans-crocetin in vivo. Methods: Trans-crocetin of high purity was extracted by hydrolysis from gardenia yellow pigment. Cis-crocetin was then synthesized through an optimized electrophilic addition reaction induced by elemental iodine, and subsequently separated and purified via silica gel column chromatography. Structural identification of cis-crocetin was determined using IR, UV, and NMR techniques. In vivo pharmacokinetic studies were conducted for both cis- and trans-crocetin. In addition to this, we have conducted a comparative study on the in vivo anti-hypoxic activity of trans- and cis-crocetin. Results: Under the selected reaction conditions using DMF as the solvent, with a concentration of 2.5 mg/mL for both trans-crocetin and the iodine solution, and adjusting the illumination time according to the amount of trans-crocetin, the rate of iodine-induced isomerization was the fastest. Cis-crocetin was successfully obtained and, after purification, its structure was identified and found to be consistent with reported data. Cis-crocetin exhibited a faster absorption rate and higher bioavailability, and despite its shorter half-life, it could partially convert to trans-crocetin in the body, thereby extending the duration of the drug's action within the body to some extent. Conclusion: This study accomplished the successful preparation and structural identification of cis-crocetin. Additionally, through pharmacokinetic studies, it uncovered notable variations in bioavailability between cis- and trans-crocetin. These findings serve as a solid scientific foundation for future functional research and practical applications in this field.

Determinative scrolling and folding of membranes through shrinking channels.

Flat membranes ubiquitously transform into mysterious complex shapes in nature and artificial worlds. Behind the complexity, clear determinative deformation modes have been continuously found to serve as basic application rules but remain unfulfilled. Here, we decipher two elemental deformation modes of thin membranes, spontaneous scrolling and folding as passing through shrinking channels. We validate that these two modes rule the deformation of membranes of a wide thickness range from micrometer to atomic scale. Their occurrence and the determinative fold number quantitatively correlate with the Föppl-von Kármán number and shrinkage ratio. The unveiled determinative deformation modes can guide fabricating foldable designer microrobots and delicate structures of two-dimensional sheets and provide another mechanical principle beyond genetic determinism in biological morphogens.

A widely conserved protein Rof inhibits transcription termination factor Rho and promotes Salmonella virulence program.

Transcription is crucial for the expression of genetic information and its efficient and accurate termination is required for all living organisms. Rho-dependent termination could rapidly terminate unwanted premature RNAs and play important roles in bacterial adaptation to changing environments. Although Rho has been discovered for about five decades, the regulation mechanisms of Rho-dependent termination are still not fully elucidated. Here we report that Rof is a conserved antiterminator and determine the cryogenic electron microscopy structure of Rho-Rof antitermination complex. Rof binds to the open-ring Rho hexamer and inhibits the initiation of Rho-dependent termination. Rof's N-terminal α-helix undergoes conformational changes upon binding with Rho, and is key in facilitating Rof-Rho interactions. Rof binds to Rho's primary binding site (PBS) and excludes Rho from binding with PBS ligand RNA at the initiation step. Further in vivo analyses in Salmonella Typhimurium show that Rof is required for virulence gene expression and host cell invasion, unveiling a physiological function of Rof and transcription termination in bacterial pathogenesis.

The responses of CO2 emission to nitrogen application and earthworm addition in the soybean cropland.

The effects of nitrogen application or earthworms on soil respiration in the Huang-Huai-Hai Plain of China have received increasing attention. However, the response of soil carbon dioxide (CO2) emission to nitrogen application and earthworm addition is still unclear. A field experiment with nitrogen application frequency and earthworm addition was conducted in the Huang-Huai-Hai Plain. Results showed nitrogen application frequency had a significant effect on soil respiration, but neither earthworms nor their interaction with nitrogen application frequency were significant. Low-frequency nitrogen application (NL) significantly increased soil respiration by 25%, while high-frequency nitrogen application (NH), earthworm addition (E), earthworm and high-frequency nitrogen application (E*NH), and earthworm and low-frequency nitrogen application (E*NL) also increased soil respiration by 21%, 21%, 12%, and 11%, respectively. The main reason for the rise in soil respiration was alterations in the bacterial richness and keystone taxa (Myxococcales). The NH resulted in higher soil nitrogen levels compared to NL, but NL had the highest bacterial richness. The abundance of Corynebacteriales and Gammaproteobacteria were positively connected with the CO2 emissions, while Myxococcales, Thermoleophilia, and Verrucomicrobia were negatively correlated. Our findings indicate the ecological importance of bacterial communities in regulating the carbon cycle in the Huang-Huai-Hai Plain.

Joint estimation model for FSO channel parameters and performance evaluation based on CNNs.

Free space optical (FSO) communication systems experience turbulence-induced fading. As a possible solution, adaptive transmission, which adjusts transmitter parameters based on instantaneous channel state information (CSI), can be used. Most of the existing channel estimation methods ignore the impact of detection noise at the receiver, which will lead to additional estimation errors. In this paper, a joint estimation model based on convolutional neural networks (CNNs) is proposed to estimate detection noise and turbulence fading parameters. We obtained turbulence channel simulation data sets considering the background of detection noise based on the edge probability distribution function of the receive signal. The training of the CNN estimator is carried out through maximum pooling, adaptive learning rate, and regularization, ultimately accurately estimating channel characteristics based on the optimal output results of the network. The simulation results show that the proposed CNN joint estimator performs better in high-detection-noise environments compared with traditional maximum likelihood estimators, and it has better generalization ability in different real atmospheric environments.