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Abstract Background Posterolateral decompression and fusion with internal fixation is a commonly used surgical approach for treating degenerative lumbar spinal stenosis (DLSS). This study aims to evaluate the impact of preserving a portion of the unilateral facet joint during decompression on surgical outcomes and long-term recovery in patients. Methods This study analyzed 73 patients with DLSS accompanied by bilateral lower limb neurological symptoms who underwent single-level L4/5 posterolateral decompression and fusion surgery from January 2022 to March 2023. Patients were categorized into two groups based on the type of surgery received: Group A comprised 31 patients who underwent neural decompression without facet joint preservation, while Group B consisted of 42 patients who underwent neural decompression with preservation of partial facet joints on one side. Regular follow-up evaluations were conducted, including clinical and radiological assessments immediately postoperatively, and at 3 and 12 months thereafter. Key patient information was documented through retrospective chart reviews. Results Most patients in both groups experienced favorable surgical outcomes. However, four cases encountered complications. Notably, during follow-up, Group B demonstrated superior 1-year postoperative interbody fusion outcomes (P

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignant neoplasm, and up to now, the role of long non-coding RNA (lncRNA) AP001885.4 in cancer, including ESCC, is absolutely unclear. The GEPIA database was applied to identify differentially expressed and prognosis-associated genes in esophageal cancer (ESCA). CCK-8, colony formation, Western blot, and qRT-PCR methods were harnessed to investigate the role and mechanism of AP001885.4 in esophageal carcinogenesis. By analyzing TCGA data in the GEPIA database, two lncRNAs were selected. AP001885.4 was overexpressed and positively associated with the unfavorable outcome of ESCC patients, and LINC001786 was under-expressed and negatively linked with the poor prognosis. Knockdown of AP001885.4 suppressed the proliferation and colony formation of ESCC cells. Importantly, the silence of AP001885.4 downregulated c-myc. Mechanically, the knockdown of AP001885.4 reduced METTL3 expression and m6A modification in c-myc mRNA, and METTL3 positively regulated c-myc. Furthermore, the knockdown of AP001885.4 diminished histone lactylation and NF-κB (p65) expression, and the protein lactylation inhibitors (2-DG, 2-deoxy-D-glucose and oxamate) and the NF-κB inhibitor (JSH-23) also lessened c-myc expression. Consequently, our findings suggested that AP001885.4 promoted the proliferation of esophageal squamous cell carcinoma cells by histone lactylation- and NF-κB (p65)-dependent transcription activation and METTL3-mediated mRNA stability of c-myc.

This study investigated the effects of four subtitle modes on the listening comprehension of TED (Technology, Entertainment, Design) talks and academic vocabulary learning of intermediate (non-English major) and advanced (English major) English as foreign language (EFL) learners. A total of 272 Chinese college sophomore students were randomly assigned to one of the four experimental groups: Dual subtitles, English subtitles, Chinese subtitles, and no subtitles. The participants viewed four TED talks videos over a period of two weeks and were pretested (vocabulary) and posttested (vocabulary, listening comprehension). The results demonstrated that there were no statistically significant differences among the four subtitle modes for intermediate learners. However, the findings showed significant differences among the four subtitle modes for advanced learners. Specifically, the no subtitle and dual subtitle groups performed significantly better than the English subtitle group on vocabulary learning. The Chinese subtitle group significantly outperformed the no subtitle group on listening comprehension. Taken together, the results for advanced English students indicated that the redundancy effect may exist in vocabulary learning and that adding dual subtitles may not impose high cognitive load. Accordingly, this study offered important implications for learning English through watching videos using different subtitle modes for Chinese students.

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.

Welding robot is widely used in many kinds and working conditions of welding production in the current machinery manufacturing industry. It plays an essential role in the machinery manufacturing industry. At the moment, in most industries, welding robots still work by teaching and payback. When the welding object or conditions change, the robot cannot make corresponding adjustments in time, which makes the welding gun deviate from the weld center, resulting in the decline of welding quality. The realization of automatic and intelligent welding is the inevitable development trend in the future. The application of machine vision in the welding field will promote the transformation of welding technology from rigid welding automation to flexible welding intelligence. Welding automation and intelligence are intended to improve the working conditions and environment, reduce labor costs, and improve product quality. Robotic welding technology is known for its great efficiency and consistent quality. A four-step welding seam tracking system is suggested based on segmented scanning, filtering, feature points extraction, and path planning. Through the laser sensor installed at the end of the welding robot, the welding seam data is continuously collected in multiple segments in a segmented scanning manner. To improve the tracking accuracy, a combined filtering method is used to correct the data to reduce the effects of burrs, data distortion, and noise on the surface of the weldment. Then the feature points are collected, and the coordinate system is calibrated in order to identify the welding points. Finally, the spatial welding path is obtained by path planning. Two-dimensional type S and three-dimensional complex welding experimental investigations are carried out. The results show that the proposed method can form a complete welding path. The average errors of the two weldments are about 0.296 mm and 0.292 mm, respectively, which are close enough to fulfill the required accuracy of 0.5 mm. It shows that the proposed tracking method is effective and can provide a reference for the research of high-precision tracking and automatic welding.

Mounting evidence has demonstrated that fatty acid binding protein 5 (FABP5) is commonly upregulated in many human malignancies. However, the mechanisms explaining the involvement of FABP5 in hepatocellular carcinoma (HCC) remain unclear. In this study, we demonstrated the involvement of FABP5 and its downstream signaling molecules in HCC progression. We first confirmed that FABP5 expression was upregulated in HCC. Additionally, FABP5 promoted HCC cells proliferation, migration, and invasion. Mechanistic investigation showed that FABP5 could improve cAMP-response element binding protein (CREB) phosphorylation. Meanwhile, CREB, as a transcription factor, upregulated the miR-889-5p expression by binding to the miR-889-5p promoter region. Consequently, miR-889-5p led to downregulation of Krüppel-like factor 9 (KLF9) by binding to the 3ʹ-UTR of the KLF9 mRNA, potentiating the PI3K/AKT signaling pathway and promoting the proliferation, migration, and invasion of HCC cells. Our findings have identified a FABP5/CREB/miR-889-5p/KLF9 axis for HCC progression, and we postulate that blocking this key signaling pathway may represent a promising strategy for HCC treatment.

Green innovation is currently recognized as a critical aspect for organizations to create economic value while contributing to ecological sustainability. Using the rationale of upper echelons theory, the present study introduces CEO narcissism, an important but underexplored psychological trait, and dynamic capability to probe the mechanisms driving green innovation. The regression findings show that enterprises with narcissistic CEOs do better in terms of green innovation. According to the mediation study findings, dynamic capability mediates between the CEO narcissism and corporate green innovation. In addition, the examination of mediated moderation reveals that top management risk aversion could negatively moderate this mediation effect. Such observations not only show that the CEO's personality has the potential to enhance corporate green achievements, but also discover the underlying mechanism which would provide guidance to help firms to be green.

Esophageal squamous cell carcinoma (ESCC) is one of the most frequent malignant tumors, and the mechanisms underlying the anti-ferroptosis of esophageal cancer cells are still largely unclear. This study aims to explore the roles of amplified protein kinase C iota (PKCiota) in the ferroptosis of ESCC cells. Cell viability, colony formation, MDA assay, Western blotting, co-IP, PLA, and RNA-seq technologies are used to reveal the roles and mechanisms underlying the PKCiota-induced resistance of ESCC cells to ferroptosis. We showed here that PKCiota was amplified and overexpressed in ESCC and decreased during RSL3-induced ferroptosis of ESCC cells. PKCiota interacted with GPX4 and the deubiquitinase USP14 and improved the protein stability of GPX4 by suppressing the USP14-mediated autophagy–lysosomal degradation pathway. PKCiota was negatively regulated by miR-145-5p, which decreased in esophageal cancer, and also regulated by USP14 and GPX4 by a positive feedback loop. PKCiota silencing and miR-145-5p overexpression suppressed tumor growth of ESCC cells in vivo, respectively; even a combination of silencing PKCiota and RSL3 treatment showed more vital suppressive roles on tumor growth than silencing PKCiota alone. Both PKCiota silencing and miR-145-5p overexpression sensitized ESCC cells to RSL3-induced ferroptosis. These results unveiled that amplified and overexpressed PKCiota induced the resistance of ESCC cells to ferroptosis by suppressing the USP14-mediated autophagic degradation of GPX4. Patients with PKCiota/USP14/GPX4 pathway activation might be sensitive to GPX4-targeted ferroptosis-based therapy.

ObjectiveIn order to solve the problem of time cooperative path planning for unmanned marine system (UMS) in complex environments, we propose a cooperative path planning method based on a differential evolution (DE) algorithm. MethodsFirst, natural environment and enemy threat models in the air, sea and underwater are established. The objective function of path planning with multiple constraints is constructed and a strategy proposed to solve the time coordination problem under the constraints of heterogeneous platforms starting at different times and places, but arriving at the same time and place. Next, a DE algorithm is used to optimize the solution, and the influence of the number of waypoints on the success rate of the planning is studied. ResultsBased on the reasonable selection of the number of waypoints, the DE algorithm can respectively plan the path that satisfies the time cooperative constraint for the UMS and find the shortest time to reaching the target in complex environments with multiple threats and obstacles. The results also show that either excessive or inadequate numbers of waypoints will result in success rate reduction of the path planning. ConclusionsThe results of this study show that the model and constraint conditions are reasonable, and the proposed algorithm can solve the problem of time coordination in the path planning of UMS, which has great practical application value.

This meta-analysis reviewed research between 2012 and 2018 focused on technology-assisted second language (L2) vocabulary learning for English as a foreign language (EFL) learner. A total of 45 studies of 2,374 preschool-to-college EFL students contributed effect sizes to this meta-analysis. Compared with traditional instructional methods, the overall effect of technology-assisted L2 vocabulary learning was large (g = 0.845), suggesting that technology-assisted L2 vocabulary learning was more beneficial than non-technology-assisted instruction. Importantly, within-study comparison results indicated that technology could enhance learners' long-term vocabulary retention. Moderator analysis results highlight several variables--namely, device type, game condition, setting, test format, and reported reliability--affecting the effectiveness of vocabulary learning. Specifically, advantages were found for mobile devices and on-the-move learning, suggesting that L2 vocabulary learning may be most efficient when students use mobile phones and are not restricted by classroom settings. These variables should be considered when planning instruction in technology-assisted L2 vocabulary learning.

Background: As an important downstream effector of various signaling pathways, mTOR plays critical roles in regulating many physiological processes including erythropoiesis. It is composed of two distinct complexes, mTORC1 and mTORC2, which differ in their components and downstream signaling effects. Our previous study revealed that the inhibition of mTORC1 by rapamycin significantly repressed the erythroid progenitor expansion in the early stage but promoted enucleation and mitochondria clearance in the late stage of erythroid differentiation. However, the particular roles and differences of mTORC1 and mTORC2 in the regulation of erythropoiesis still remain largely unknown. In the present study, we investigated the comparative effects of dual mTORC1/mTORC2 mTOR kinase inhibitor AZD8055 and mTORC1 inhibitor rapamycin on erythroid differentiation in K562 cells induced by hemin and erythropoiesis in β‐thalassemia mouse model. Materials and Methods: In vitro erythroid differentiation model of hemin‐induced K562 cells and β‐thalassemia mouse model were treated with AZD8055 and rapamycin. Cell Counting Kit‐8 was used to detect cell viability. The cell proliferation, cell cycle, erythroid surface marker expression, mitochondrial content, and membrane potential were determined and analyzed by flow cytometry and laser scanning confocal microscopy. Globin gene expression during erythroid differentiation was measured by RT‐qPCR. The mTORC2/mTORC1 and autophagy pathway was evaluated using western blotting. Results: Both AZD8055 and rapamycin treatments increased the expression levels of the erythroid differentiation‐specific markers, CD235a, α‐globin, γ‐globin, and ε‐globin. Notably, AZD8055 suppressed the cell proliferation and promoted the mitochondrial clearance of hemin‐induced K562 cells more effectively than rapamycin. In a mouse model of β‐thalassemia, both rapamycin and AZD8055 remarkably improve erythroid cell maturation and anemia. Moreover, AZD8055 and rapamycin treatment inhibited the mTORC1 pathway and enhanced autophagy, whereas AZD8055 enhanced autophagy more effectively than rapamycin. Indeed, AZD8055 treatment inhibited both mTORC2 and mTORC1 pathway in hemin‐induced K562 cells. Conclusion: AZD8055 is more effective than rapamycin in inhibiting proliferation and promoting mitochondrial clearance in erythroid differentiation, which might provide us one more therapeutic option other than rapamycin for ineffective erythropoiesis treatment in the future. These findings also provide some preliminary information indicating the roles of mTORC1 and mTORC2 in erythropoiesis, and further studies are necessary to dissect the underlying mechanisms. [ABSTRACT FROM AUTHOR]

To investigate the effect of structural parameters of bridges with unequal spans on the bridge alignment, the finite element model simulating the full-scale bridge was developed, considering the construction process. For ease of finite element modeling and investigation, the section of composite beam with corrugated steel web was first converted into the section composed of the same material. For this purpose, an equivalent method of replacing corrugated steel webs with concrete webs was proposed based on theoretical derivation. After equivalent replacement, the influences of material bulk density, internal prestress, pipe friction coefficient, and pipe deviation coefficient on the main beam at the maximum cantilever stage were analyzed, and the influences of external prestress on the main beam after bridge construction were analyzed. The results show that the most sensitive parameter to structural response is bulk density, subsequently the external prestress, internal prestress, pipe friction coefficient, and pipe deviation coefficient. Among them, the bulk density, internal prestress, and external prestress are all sensitive parameters, while pipe friction coefficient and pipe deviation coefficient are non-sensitive parameters.

In the scenarios of traffic diagnostic analysis and prediction in optical network based on deep learning, the work of traffic data collection and storage for optical link is limited due to security and other reasons. Aiming at the problem that the amount of traffic data is too small to support deep learning training, this paper proposes an optical network traffic data synthesis algorithm based on topology link recognition. The core idea is to combine the conditional generation model based on optical network topology and the data synthesis model based on optical network traffic in the framework of generative adversarial networks. The traffic data of the given optical link is synthesized in a self-supervised way. The simulation results show that the auto-correlation coefficients of the traffic data synthesized by the proposed algorithm is close to the real data, and the accuracy of the traffic prediction model based on fully connected neural network is more than 95%.

In the scenarios of traffic diagnostic analysis and prediction in optical network based on deep learning, the work of traffic data collection and storage for optical link is limited due to security and other reasons. Aiming at the problem that the amount of traffic data is too small to support deep learning training, this paper proposes an optical network traffic data synthesis algorithm based on topology link recognition. The core idea is to combine the conditional generation model based on optical network topology and the data synthesis model based on optical network traffic in the framework of generative adversarial networks. The traffic data of the given optical link is synthesized in a self-supervised way. The simulation results show that the auto-correlation coefficients of the traffic data synthesized by the proposed algorithm is close to the real data, and the accuracy of the traffic prediction model based on fully connected neural network is more than 95%.

ObjectivesIn order to realize the formation control of swarms of unmanned marine vehicle (UMV) with directed interaction topology, the formation tracking control of unmanned surface vehicle (USV) and unmanned aerial vehicle (UAV) swarms is studied.Methods An inner/outer loop layered control structure of formation is adopted to model the system, and the discrete-time system is used to describe the formation control problem of UMV swarms, improving the compatibility and practicability of the method for heterogeneous swarms. Based on the idea of a virtual leader, a distributed formation control protocol based on neighbor position and velocity error feedback is adopted, and the necessary and sufficient conditions for UMV swarms to realize the desired configuration and path tracking are given.ResultsThe simulation results show that UMV swarms can achieve stable formation control when there is a directed spanning tree in the interaction topology, and the parameters of the control protocol and discrete time period meet the given constraints.ConclusionsThis method has application value in the formation control of UMV swarms with directed interaction topology.

The Micro-Electromechanical System (MEMS) optical switches in power systems may be affected by optical control signals during fiber switching, which may cause damage to Optical Time-Domain Reflectometer (OTDR). In order to solve this problem, this paper proposes a method to optimize the switching path of MEMS optical switches in power systems. After the optical switch performing a complete scan, the accurate optical signal channel power contour map is obtained, and then the switching path is optimized and controlled. Therefore, the MEMS optical switch can achieve the highest relative channel isolation of incident light along the premise of balancing the control channel switching time. The best path for switching control can also be used to minimize the impact of the MEMS optical switch on other channels when switching under the premise of ensuring the switching time, and it will not be affected even in a very complicated channel environment.

Hyperspectral images (HSIs) with abundant spectra and high spatial resolution can satisfy the demand for the classification of adjacent homogeneous regions and accurately determine their specific land-cover classes. Due to the potentially large variance within the same class in hyperspectral images, classifying HSIs with limited training samples (i.e., few-shot HSI classification) has become especially difficult. To solve this issue without adding training costs, we propose an ensemble of meta-optimizers that were generated one by one through utilizing periodic annealing on the learning rate during the meta-training process. Such a combination of meta-learning and ensemble learning demonstrates a powerful ability to optimize the deep network on few-shot HSI training. In order to further improve the classification performance, we introduced a novel update integration process to determine the most appropriate update for network parameters during the model training process. Compared with popular human-designed optimizers (Adam, AdaGrad, RMSprop, SGD, etc.), our proposed model performed better in convergence speed, final loss value, overall accuracy, average accuracy, and Kappa coefficient on five HSI benchmarks in a few-shot learning setting. [ABSTRACT FROM AUTHOR]