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Abstract Background To identify independent factors of cognitive frailty (CF) and construct a nomogram to predict cognitive frailty risk in patients with lung cancer receiving drug therapy. Methods In this cross‐sectional study, patients with lung cancer undergoing drug therapy from October 2022 to July 2023 were enrolled. The data collected includes general demographic characteristics, clinical data characteristics and assessment of tools for cognitive frailty and other factors. Logistic regression was harnessed to determine the influencing factors, R software was used to establish a nomogram model to predict the risk of cognitive frailty. The enhanced bootstrap method was employed for internal verification of the model. The performance of the nomogram was evaluated by using calibration curves, the area under the receiver operating characteristic curve, and decision curve analysis. Results A total of 372 patients were recruited, with a cognitive frailty prevalence of 56.2%. Age, education background, diabetes mellitus, insomnia, sarcopenia, and nutrition status were identified as independent factors. Then, a nomogram model was constructed and patients were classified into high‐ and low‐risk groups with a cutoff value of 0.552. The internal validation results revealed good concordance, calibration and discrimination. The decision curve analysis presented prominent clinical utility. Conclusions The prevalence of cognitive frailty was higher in lung cancer patients receiving drug therapy. The nomogram could identify the risk of cognitive frailty intuitively and simply in patients with lung cancer, so as to provide references for early screening and intervention for cognitive frailty at the early phases of drug treatment.

Abstract As a signaling molecule, nitric oxide (NO) regulates the development and stress response in different organisms. The major biological activity of NO is protein S‐nitrosylation, whose function in fungi remains largely unclear. Here, it is found in the rice blast fungus Magnaporthe oryzae, de‐nitrosylation process is essential for functional appressorium formation during infection. Nitrosative stress caused by excessive accumulation of NO is harmful for fungal infection. While the S‐nitrosoglutathione reductase GSNOR‐mediated de‐nitrosylation removes excess NO toxicity during appressorium formation to promote infection. Through an indoTMT switch labeling proteomics technique, 741 S‐nitrosylation sites in 483 proteins are identified. Key appressorial proteins, such as Mgb1, MagB, Sps1, Cdc42, and septins, are activated by GSNOR through de‐nitrosylation. Removing S‐nitrosylation sites of above proteins is essential for proper protein structure and appressorial function. Therefore, GSNOR‐mediated de‐nitrosylation is an essential regulator for appressorium formation. It is also shown that breaking NO homeostasis by NO donors, NO scavengers, as well as chemical inhibitor of GSNOR, shall be effective methods for fungal disease control.

Since the model parameters of the shaking table exist in a non-linear form, this leads to distortion of the reproduced waveforms and can even lead to bias in the ground vibration test results. Therefore, the selection of the controller is particularly critical. Multi-variable (MVC) controllers are often used in shaking table control, to improve the control effect of MVC controllers. In this paper, a multi-parametric (BP-MVC) controller based on BP neural network is proposed. The BP neural network is applied to the multi-parameter (MVC) controller to identify the shaking table model, adjust the parameters in real-time, accelerate the convergence speed, and reduce the system error. The simulation results show that the correlation coefficient (CC) of the BP-MVC controller is greater than 0.985, and the root-mean-square error (RMSE) and mean absolute error (MAE) are less than 0.04 and 0.25, respectively, in a nonlinear, time-varying hydraulic system. This suggests that the BP-MVC controller has a better control performance and parameter adaptivity, which can provide a reference for the subsequent ground vibration tests.

Monitoring the annual variation of antibiotic resistance genes (ARGs) in livestock wastewater is important for determining the high-risk period of transfer and spread of animal-derived antibiotic resistance into the environment. However, the knowledge regarding the variation patterns of ARGs, especially intracellular ARGs (iARGs) and extracellular ARGs (eARGs), over time in livestock wastewater is still unclear. Herein, we conducted a year-round study to trace the profiles of ARGs at a Chinese-intensive dairy farm, focusing on the shifts observed in different months. The results showed significant differences in the composition and variation between iARGs and eARGs. Tetracycline, sulfonamide, and macrolide resistance genes were the major types of iARGs, while cfr was the major type of eARG. The environmental adaptations of the host bacteria determine whether ARGs appear as intracellular or extracellular forms. The total abundance of ARGs was higher from April to September, which can be attributed to the favorable climatic conditions for bacterial colonization and increased antibiotic administration during this period. Integron was found to be highly correlated with most iARGs, potentially playing a role in the presence of these genes within cells and their similar transmission patterns in wastewater. The intracellular and extracellular bacterial communities were significantly different, primarily because of variations in bacterial adaptability to the high salt and anaerobic environment. The intracellular co-occurrence network indicated that some dominant genera in wastewater, such as Turicibacter, Clostridium IV, Cloacibacillus, Subdivision5_genera_incertae_sedis, Saccharibacteria_genera_incertae_sedis and Halomonas, were potential hosts for many ARGs. To the best of our knowledge, this study demonstrates, for the first time, the annual variation of ARGs at critical points in the reuse of dairy farm wastewater. It also offers valuable insights into the prevention and control of ARGs derived from animals.

Multiphoton microscopy (MPM) is a powerful imaging technology for brain research. The imaging depth in MPM is partly determined by emission wavelength of fluorescent labels. It has been demonstrated that a longer emission wavelength is favorable for signal detection as imaging depth increases. However, there has been no comparison with near-infrared (NIR) emission. In order to quantitatively analyze the effect of emission wavelength on 3-photon imaging of mouse brains in vivo, we utilize the same excitation wavelength to excite a single fluorescent dye and simultaneously collect NIR and orange-red emission fluorescence at 828[Formula: see text]nm and 620[Formula: see text]nm, respectively. Both experimental and simulation results show that as the imaging depth increases, NIR emission decays less than orange-red fluorescent emission. These results show that it is preferable to shift the emission wavelength to NIR to enable more efficient signal collection deep in the brain.

Abstract Due to the rise of 5G, IoT, AI, and high-performance computing applications, datacenter traffic has grown at a compound annual growth rate of nearly 30%. Furthermore, nearly three-fourths of the datacenter traffic resides within datacenters. The conventional pluggable optics increases at a much slower rate than that of datacenter traffic. The gap between application requirements and the capability of conventional pluggable optics keeps increasing, a trend that is unsustainable. Co-packaged optics (CPO) is a disruptive approach to increasing the interconnecting bandwidth density and energy efficiency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and photonics. CPO is widely regarded as a promising solution for future datacenter interconnections, and silicon platform is the most promising platform for large-scale integration. Leading international companies (e.g., Intel, Broadcom and IBM) have heavily investigated in CPO technology, an inter-disciplinary research field that involves photonic devices, integrated circuits design, packaging, photonic device modeling, electronic-photonic co-simulation, applications, and standardization. This review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform, identify the key challenges, and point out the potential solutions, hoping to encourage collaboration between different research fields to accelerate the development of CPO technology. Graphical Abstract

The calcium/calcineurin signaling pathway plays a key role in the development and virulence of plant pathogenic fungi, but the regulation of this signaling pathway is still not clear. In this study, we identified a calcineurin regulator MoRCN1 in the plant pathogenic fungus Magnaporthe oryzae and found it is important for virulence by regulating the calcineurin pathway. MoRCN1 deletion mutants were severely decreased in colony growth and conidia formation. More importantly, the deletion of MoRCN1 led to a significant reduction in virulence due to defects in appressorium formation and invasive growth. The ΔMorcn1 mutants were more sensitive to different stresses and induced host ROS accumulation, suggesting a role of MoRCN1 in stress adaptation. We found that MoRCN1 directly interacted with the calcineurin catalytic subunit MoCNA and affected its protein stability, which was therefore important for regulating the calcineurin pathway. Transcriptome analysis showed that MoRCN1 significantly activated 491 genes and suppressed 337 genes in response to calcium ion, partially overlapped with the MoCRZ1-bound genes. Gene Ontology and KEGG pathway analyses indicated that MoRCN1-regulated genes were enriched in stress adaptation, lipid metabolism, and secondary metabolite biosynthesis, reflecting a function of MoRCN1 in host cell adaptation. Altogether, these results suggest MoRCN1 functions as a regulator of the calcium/calcineurin signaling pathway for fungal development and infection of host cells.

It is difficult to accurately establish a model of the real mesa system. Furthermore, a model of a seismic simulation vibration table array system is critical to increasing the accuracy of seismic testing in laboratory settings. Herein a model of the nine subarray shaking table system is identified by recursive extension of the least square method, which is used to accurately identify the structure parameters by simulation of the structure assuming a single degree-of-freedom. Then, through the displacement of the empty shaking table and the application of the recursive least squares algorithm, the model of the seismic simulation vibration table array is established. Through this study, the vibration table model of different construction forms can be obtained, and the parameters that are difficult to measure for some complex structures can effectively be determined.

Because of the continuous stream of touchscreen apps that are claimed to be educational and the increasing use of touchscreen devices in early childhood, considerable attention is being paid to the effect of touchscreens on young children's learning. However, the existing empirical findings in young child samples are not consistent. In this meta-analysis we tested the overall effect of touchscreen devices on young children's (0- to 5-year-olds) learning performance, as well as moderators of this effect, based on 36 empirical articles (79 effect sizes) involving 4,206 participants. The overall analysis showed a significant touchscreen learning effect (d = 0.46), indicating that young children indeed benefited from touchscreen learning. Interestingly, age, learning material domain, comparison group, and experimental environment significantly moderated the effect of touchscreen devices on young children's learning outcome. These findings shed light on the role of touchscreen-related physical experience in early childhood education.

Aeromonas veronii. a ubiquitous of zoonotic disease pathogen, depends on adhesion as the crucial way to colonize the gastrointestinal tract of humans and animals, which further causes severe gastrointestinal diseases and parenteral infections. However, the adherence mechanism of A. veronii has not been fully characterized. Therefore, we investigate the effect of autoinducer-2 (AI-2) on adherence of A. veronii through facilitating the expression of mannose-sensitive hemagglutinin (MSHA) type IV pili genes mediated by cyclic diguanosine monophosphate (c-di-GMP). The deficiency of AI-2 significantly lowered the adherence of A. veronii to erythrocytes and intestinal mucus, and the complement of AI-2 could increase its adherence ability. The deficiency of AI-2 only limited the formation of pili, instead of outer-membrane proteins and lipopolysaccharide, through reducing the expression levels of MSHA type IV pili genes due to the decline of c-di-GMP. The addition of guanosine triphosphate (GTP) could increase the content of c-di-GMP and the expression of MSHA type IV pili genes, and further promote adherence of A. veronii. Therefore, this study reveals, for the first time, adherence mediated by c-di-GMP with MshE as the c-di-GMP receptor is positively regulated by AI-2 in A. veronii, which increases the understanding of colonization strategy of pathogen and may facilitate control of A. veronii infection to host. IMPORTANCE Aeromonas veronii can adhere to host cells through different adherence factors including outer-membrane proteins (OMPs), lipopolysaccharide (LPS), and pili, but its adherence mechanisms are still unclear. Here, we evaluated the effect of autoinducer-2 (AI-2) on adherence of A. veronii and its regulation mechanism. After determination of the promotion effect of AI-2 on adherence, we investigated which adherence factor was regulated by AI-2, and the results show that AI-2 only limits the formation of pili. Among the four distinct pili systems, only the mannose-sensitive hemagglutinin (MSHA) type IV pili genes were significantly downregulated after deficiency of AI-2. MshE, an ATPase belonged to MSHA type IV pilin, was confirmed as c-di-GMP receptor, that can bind with c-di-GMP which is positively regulated by AI-2, and the increase of c-di-GMP can promote the expression of MSHA type IV pili genes and adherence of A. veronii. Therefore, this study confirms that c-di-GMP positively regulated by AI-2 binds with MshE, then increases the expression of MSHA pili genes, finally promoting adherence of A. veronii, suggesting a multilevel positive regulatory adhesion mechanism that is responsible for A. veronii adherence. [ABSTRACT FROM AUTHOR]