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Boron (B), an essential micronutrient for fruit development, also plays a crucial role in maintaining the shelf life of strawberries (Fragaria ananassa Duch.) by affecting cell wall structure and components. We investigated the distribution pattern of B within cells and cell walls in strawberry fruits under different B levels and revealed the relationship between the B distribution in cell walls and fruit firmness after harvesting. Foliar spraying of 0.1% H3BO3 promoted the growth of strawberry seedlings and improved fruit yield and flesh firmness by 45.7% and 25.6%. During the fruit softening and decay process, the content of bound B and cell wall-B decreased while more B was allocated to the protoplast and apoplast. The changes in B distribution in cells were attributed to cell damage during fruit decay, and B extended the freshness period of the fruits by alleviating the decrease of B distribution in cell walls. After leaving the fruits at room temperature for 10 h, the B content in different cell wall components significantly decreased, while foliar spraying of B alleviated the reduction of B content in covalently bound pectin (CBP), cellulose, and hemicellulose. Meanwhile, B spraying on fruit decreased the activity of cell wall degradation enzymes, including polygalacturonase (PG) and pectin lyase (PL), by 20.2% and 38.1%, while enhancing the demethylation of pectin by increasing pectin methylesterase (PME) activity from 21.6 U/g to 25.7 U/g. Thus, foliar spraying of 0.1% H3BO3 enhances the cross-linking of B with cell wall components and maintains cell wall structure, thereby prolonging the shelf life of strawberry fruits. [ABSTRACT FROM AUTHOR]

Machine learning potential (MLP) has been a popular topic in recent years for its capability to replace expensive first-principles calculations in some large systems. Meanwhile, message passing networks have gained significant attention due to their remarkable accuracy, and a wave of message passing networks based on Cartesian coordinates has emerged. However, the information of the node in these models is usually limited to scalars, and vectors. In this work, we propose High-order Tensor message Passing interatomic Potential (HotPP), an E(n) equivariant message passing neural network that extends the node embedding and message to an arbitrary order tensor. By performing some basic equivariant operations, high order tensors can be coupled very simply and thus the model can make direct predictions of high-order tensors such as dipole moments and polarizabilities without any modifications. The tests in several datasets show that HotPP not only achieves high accuracy in predicting target properties, but also successfully performs tasks such as calculating phonon spectra, infrared spectra, and Raman spectra, demonstrating its potential as a tool for future research.Machine learning potential has gained interest for replacing calculations in large systems. Here, authors propose an E(n) equivariant message passing neural network that uses high-order Cartesian tensors to predict properties with high accuracy [ABSTRACT FROM AUTHOR]

Wavefront distortions pose a significant limitation in various optical applications, hindering further advancements in optical system performance. In this study, a novel generic calibration model based on Zernike‐fitting neural network (ZFNN) is proposed, which enables insitu wavefront correction with just a single‐shot measurement. The experimental setup follows a standard or equivalent focal‐field imaging optical path, allowing calibration without the need to remove any components from the optical system. The ZFNN, a physics‐informed neural network, offers the advantage of not requiring prior training, eliminating the need for extensive labeled data. With a fully connected network architecture and a modest number of neurons (469), the ZFNN achieves exceptionally fast optimization speed and meets the basic requirements for real‐time calibration. Consequently, this approach holds great potential for applications such as rapid calibration of optical systems, high‐precision light field modulation, and various advanced imaging techniques. [ABSTRACT FROM AUTHOR]

Background: This study aimed to construct a clinical prediction model and nomogram to differentiate invasive from non-invasive pulmonary adenocarcinoma in solitary pulmonary nodules (SPNs). Method: We analyzed computed tomography and clinical features as well as preoperative biomarkers in 1,106 patients with SPN who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University between January 2020 and December 2021. Clinical parameters and imaging characteristics were analyzed using univariate and multivariate logistic regression analyses. Predictive models and nomograms were developed and their recognition abilities were evaluated using receiver operating characteristic (ROC) curves. The clinical utility of the nomogram was evaluated using decision curve analysis (DCA). Result: The final regression analysis selected age, carcinoembryonic antigen, bronchus sign, lobulation, pleural adhesion, maximum diameter, and the consolidation-to-tumor ratio as associated factors. The areas under the ROC curves were 0.844 (95% confidence interval [CI], 0.817-0.871) and 0.812 (95% CI, 0.766-0.857) for patients in the training and validation cohorts, respectively. The predictive model calibration curve revealed good calibration for both cohorts. The DCA results confirmed that the clinical prediction model was useful in clinical practice. Bias-corrected C-indices for the training and validation cohorts were 0.844 and 0.814, respectively. Conclusion: Our predictive model and nomogram might be useful for guiding clinical decisions regarding personalized surgical intervention and treatment options. [ABSTRACT FROM AUTHOR]

Tight glutenite reservoir structure is complex, mineral types are multi-seepage, and most of them are non-Darcy's law flows Based on the finite element COMSOL simulation of seepage flow in glutenite water flooding, this chapter mainly explores the influence of several related factors on displacement recovery. With the increase of wetting angle, the wettability makes the porous state of solids and fluids in glutenite stable, so that water can easily push oil out, which leads to the increase of water flooding recovery The higher the injection rate, the higher the water cut in a short time, which makes the oil-water two-phase displacement accelerate and the higher the displacement recovery With the increase of gravel diameter, the oil saturation decreases less and more crude oil is bound by the pore structure surrounded by large particles, which is not conducive to displacement Small gravel particles have little influence on the front of water drive, and there is no obvious dominant channel, which leads to the recovery effect. [ABSTRACT FROM AUTHOR]

Objective: Investigate the impact of combined computerized cognitive training and occupational therapy on individuals with mild cognitive impairment (MCI). Methods: We randomly assigned 118 MCI patients into two groups: a combined intervention group (n = 37) and a control group (n = 81), the latter receiving standard nursing care. The intervention group additionally underwent 12 weeks of computerized cognitive training and occupational therapy. Blind assessors evaluated cognitive performance, anxiety, depression, and daily living activities before the intervention, post-intervention, and at a 3-month follow-up. Results: Repeated-measures analysis of variance showed that the sMoCA scores, HAMA scores, and ADL scores of the experimental group at T2 (post-intervention) and T3 (3-month follow-up) were higher than those of the control group, and the difference was statistically significant (p < 0.001, p < 0.001, p = 0.026). Conclusion: Computerized cognitive training combined with occupational therapy can improve patients' cognitive status, enhance their compliance with continuing care, and maintain their anxiety and self-care ability at a stable level. [ABSTRACT FROM AUTHOR]

The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery. Traditional chemical solutions with large molecular size cannot effectively flow through the nanopores of the reservoir. In this study, the feasibility of Nanofluids has been investigated using a high pressure high temperature core-holder and nuclear magnetic resonance (NMR). The results of the experiments indicate that the specified Nanofluids can enhance the tight oil recovery significantly. The water and oil relative permeability curve shifts to the high water saturation side after Nanofluid flooding, thereby demonstrating an increase in the water wettability of the core. In the Nanofluid flooding process the oil recovery was enhanced by 15.1%, compared to waterflooding stage. The T2 spectra using the NMR show that after Nanofluid flooding, a 7.18% increment in oil recovery factor was gained in the small pores, a 4.9% increase in the middle pores, and a 0.29% increase in the large pores. These results confirm that the Nanofluids can improve the flow state in micro-sized pores inside the core and increase the ultimate oil recovery factor. [ABSTRACT FROM AUTHOR]

Background: As an important mathematical model, the finite state machine (FSM) has been used in many fields, such as manufacturing system, health care, and so on. This paper analyzes the current development status of FSMs. It is pointed out that the traditional methods are often inconvenient for analysis and design, or encounter high computational complexity problems when studying FSMs. Method: The deep Q-network (DQN) technique, which is a model-free optimization method, is introduced to solve the stabilization problem of probabilistic finite state machines (PFSMs). In order to better understand the technique, some preliminaries, including Markov decision process, o-greedy strategy, DQN, and so on, are recalled. Results: First, a necessary and suffcient stabilizability condition for PFSMs is derived. Next, the feedback stabilization problem of PFSMs is transformed into an optimization problem. Finally, by using the stabilizability condition and deep Q-network, an algorithm for solving the optimization problem (equivalently, computing a state feedback stabilizer) is provided. Discussion: Compared with the traditional Q learning, DQN avoids the limited capacity problem. So our method can deal with high-dimensional complex systems efficiently. The effectiveness of our method is further demonstrated through an illustrative example. [ABSTRACT FROM AUTHOR]

Recognized in the 1990s, vortex beams' ability to carry orbital angular momentum (OAM) has significantly contributed to applications in optical manipulation and high-dimensional classical and quantum information communication. However, inherent diffraction in free space results in the inevitable expansion of beam size and divergence contingent upon the OAM, limiting vortex beams' applicability in areas such as spatial mode multiplexing communication, fiber-optic data transmission, and particle manipulation. These domains necessitate vortex beams with OAM-independent propagation characteristics. We introduce iso-propagation vortices (IPVs), vortex beams characterized by OAM-independent propagation behavior, achieved through precise radial index configuration of Laguerre-Gaussian beams. IPVs display notable transmission dynamics, including a reduced quality factor, resilience post-damage, and decreased and uniform modal scattering under atmospheric turbulence. Their distinctive attributes render IPVs valuable for potential applications in imaging, microscopy, optical communication, metrology, quantum information processing, and light-matter interactions. Notably, within optical communication, the case study suggests that the IPV basis, due to its OAM-independent propagation behavior, provides access to a more extensive spectrum of data channels compared with conventional spatial multiplexing techniques, consequently augmenting information capacity. [ABSTRACT FROM AUTHOR]

A good intelligent learning model is the key to complete recognition of scene information and accurate recognition of specific targets in intelligent unmanned system. This study proposes a new associative memory model based on the semi-tensor product (STP) of matrices, to address the problems of information storage capacity and association. First, some preliminaries are introduced to facilitate modeling, and the problem of information storage capacity in the application of discrete Hopfield neural network (DHNN) to associative memory is pointed out. Second, learning modes are equivalently converted into their algebraic forms by using STP. A memory matrix is constructed to accurately remember these learning modes. Furthermore, an algorithm for updating the memory matrix is developed to improve the association ability of the model. And another algorithm is provided to show how our model learns and associates. Finally, some examples are given to demonstrate the effectiveness and advantages of our results. Compared with mainstream DHNNs, our model can remember learning modes more accurately with fewer nodes. [ABSTRACT FROM AUTHOR]

By concurrently manipulating the degrees of freedom associated with polarization and orbital angular momentum (OAM), a variety of vector fields can be generated, which exhibit unique characteristics and have found extensive application in both classical and quantum optics. However, the OAM dimensions in these fields have been predominantly confined to two. Different from high-order OAM with a large topological charge, broadening the OAM dimensions beyond this limit and generating OAM spectra with multiple OAM modes can significantly enhance the scope of research. In this study, we explore vector fields with OAM dimensions exceeding ten, achieving polarization-controlled spectra in higher-dimensional OAM. Our findings not only offer a method for controlling high-dimensional OAM through polarization but also pave the way for potential applications in both classical and quantum realms utilizing high-dimensional vector states. [ABSTRACT FROM AUTHOR]

Data from national meteorological stations in 90 counties of Jiangxi province during 2012-2021 and 8 microclimate stations in rice fields during 2017-2021 were used to analyze the differences in temperature between rice fields and stations, and the statistical results based on H1 (NS)(daily max temperature of national stations ≥35 °C), H1 (RS)(daily max temperature of rice fields ≥35 °C), H2 (NS)(daily max temperature of national stations ≥37°C) and H2 (RS) (daily max temperature of rice fields ≥ 37 °C ) were compared. Furthermore, proposing high-temperature damage indicators more suitable for early rice in Jiangxi, which would promoting capabilities of high-temperature monitoring and defense. The results showed that: (1) compared with the national stations, the rice fields had a cooling effect, and the Tmax(daily maximum temperature), T(daily average temperature), and Tmin(daily minimum temperature) were 0.6 °C, 0.4 °C, and 0.3 °C lower than national stations. What's more, the cooling effect increased with the growth of early rice, which showed as heading-maturity period>transplanting-booting period>sowing-transplanting period. (2) The cooling effect was higher in sunny days than in cloudy and rainy days during the high temperature period, and T, Tmax and Tmin of early rice field were 0.7 °C, 0.8 °C and 0.6 °C lower than that of the national stations. On cloudy and rainy days, the decrease in temperature of rice fields was similar. (3) There were significant differences in daily and hourly air temperature between 6 rice fields and the corresponding national stations during H1 (NS) heat damage occurred, and the cooling intensity of the rice field was greater at night than in the daytime. The Tmax, T and Tmin of the 6 fields were generally about 1.2 °C lower, which was strongest in Jinxi filed with T, Tmax and Tmin was 1.5 °C, 1.1 °C and 2.6 °C lower. (4) H1 (NS) was the largest and H2 (RS) was the smallest in terms of the number of counties affected by heat damage, the average duration, the average yield reduction simulation value of affected counties and the simulation value of the whole in recent 10 years based on different heat damage index. There was no significant difference in the result of average duration, the simulated average yield reduction rate of affected counties, and the simulated yield reduction rate of the whole based on H2 (NS) and H1 (RS), while they were all different with the result based on H1 (NS) or H2 (RS). And the simulated value of the reduction rate of the whole calculated by H2 (NS) was closer to the actual value. Therefore, national stations Tmax ≥37°C was more suitable as an index of heat damage for early rice in Jiangxi. [ABSTRACT FROM AUTHOR]

Background: Esophagectomy is the gold standard treatment for resectable esophageal cancer; however, there is insufficient evidence to indicate potential advantages over standard minimally invasive esophagectomy (MIE) in treating thoracic esophageal cancer. Robot-assisted minimally invasive esophagectomy (RAMIE) bridges the gap between open and minimally invasive surgery. In this single-center retrospective review, we compare the clinical outcomes of EC patients treated with MIE and RAMIE. Method: We retrospectively reviewed the clinical data of patients with esophageal cancer who underwent surgery at Qilu Hospital between August 2020 and August 2022, including 159 patients who underwent MIE and 35 patients who received RAMIE. The intraoperative, postoperative, and preoperative patient characteristics in both groups were evaluated. Results: Except for height, the MIE and RAMIE groups showed no significant differences in preoperative features (P>0.05). Further, there were no significant differences in intraoperative indices, including TNM stage of the resected tumor, tumor tissue type, or ASA score, between the two groups. However, statistically significant differences were found in some factors; the RAMIE group had a shorter operative time, less intraoperative bleeding, and more lymph nodes removed compared to the MIE group. Patients in the RAMIE group reported less discomfort and greater chest drainage on the first postoperative day than patients in the MIE group; however, there were no differences in other features between the two datasets. Conclusion: By comparing the clinical characteristics and outcomes of RAMIE with MIE, this study verified the feasibility and safety of RAMIE for esophageal cancer. Overall, RAMIE resulted in more complete lymph node clearance, shorter operating time, reduced surgical hemorrhage, reduced postoperative discomfort, and chest drainage alleviation in patients. To investigate the function of RAMIE in esophageal cancer, we propose undertaking a future clinical trial with long-term follow-up to analyze tumor clearance, recurrence, and survival after RAMIE. [ABSTRACT FROM AUTHOR]

The regulation of spermatogonial proliferation and apoptosis is of great significance for maintaining spermatogenesis. The single-cell RNA sequencing (scRNA-seq) analysis of the testis was performed to identify genes upregulated in spermatogonia. Using scRNAseq analysis, we identified the spermatogonia upregulated gene origin recognition complex subunit 6 (Orc6), which is involved in DNA replication and cell cycle regulation; its protein expression in the human and mouse testis was detected by western blot and immunofluorescence. To explore the potential function of Orc6 in spermatogonia, the C18-4 cell line was transfected with control or Orc6 siRNA. Subsequently, 5-ethynyl-2-deoxyuridine (EdU) and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays, flow cytometry, and western blot were used to evaluate its effects on proliferation and apoptosis. It was revealed that ORC6 could promote proliferation and inhibit apoptosis of C18-4 cells. Bulk RNA sequencing and bioinformatics analysis indicated that Orc6 was involved in the activation of wingless/integrated (Wnt)/β-catenin signaling. Western blot revealed that the expression of β-catenin protein and its phosphorylation (Ser675) were significantly decreased when silencing the expression of ORC6. Our findings indicated that Orc6 was upregulated in spermatogonia, whereby it regulated proliferation and apoptosis by activating Wnt/β-catenin signaling. [ABSTRACT FROM AUTHOR]

Background: DARS2 expression is upregulated in lung adenocarcinoma (LUAD) which correlates with tumor patient stage and prognosis. The mechanism of DARS2 involvement in LUAD still needs to be further explored. Methods: In this study, we found that DARS2 expression in LUAD tissue was significantly higher than that in normal tissue. At the same time, the Kaplan-Meier curve showed that the survival prognosis of LUAD patients with high expression of DARS2 was significantly worse than low expression of DARS2. The expression of DARS2 was detected in LUAD and adjacent normal tissues by IHC staining, histochemical scoring and a survival curve was generated. In addition, we demonstrated that the knockdown and overexpression of DARS2 significantly affected the proliferation, invasion, and migration of LUAD cells in vitro and in vivo. Finally, western blot and rescue assay were performed on LUAD cells to further explore and verify the signaling pathway. Results: DARS2 expression was significantly upregulated in LUAD tissues and cell lines. What is more, the increased expression of DARS2 was closely related to proliferation, invasion and metastasis. The tumorigenic assay in nude mice further showed that the tumorigenic ability of nude mice was significantly improved with the increase in DARS2 expression. Finally, we determined that DARS2 plays its role in LUAD by targeting the ERK/c-Myc signaling pathway. Conclusion: Our data revealed the oncogenic role of DARS2 in LUAD, indicating that DARS2 may be a predictive biomarker and novel therapeutic target for LUAD. [ABSTRACT FROM AUTHOR]

The tightly focused structured light field displays a non‐negligible component of the electric field in the direction of propagation, i.e., the longitudinal light field. The longitudinal light field results in various novel optical phenomena, such as transverse spin angular momentum and 3D topological light fields. However, it remains a challenge to generate customized longitudinal light fields. Here, based on inverse design theory, the longitudinal light field can be customized on demand under the tightly focusing condition, which allows to generate the longitudinal light field with controllable structured distribution for propagating waves or manipulate the complex structures for all the three components of the electric field. In experiment, an experimental system is built integrating the generation, customization, and detection of structured longitudinal light field, and the customization of the longitudinal light fields with various patterns is experimentally realized. The customized longitudinal light field structures may find applications such as information encoding, long‐distance light manipulation, and novel light–matter interactions. As an example, information encoding is realized by the structured longitudinal light fields. [ABSTRACT FROM AUTHOR]

In Phi29-α–hemolysin (α-HL) nanopore sequencing systems, a strong electrochemical signal is dependent on a high concentration of salt. However, high salt concentrations adversely affect polymerase activity. Sequencing by synthesis (SBS) requires the use of phi29 polymerase without exonuclease activity to prevent the degradation of modified nucleotide tags; however, the lack of exonuclease activity also affects polymerase processivity. This study aimed to optimize phi29 polymerase for improved salt tolerance and processivity while maintaining its lack of exonuclease activity to meet the requirements of nanopore sequencing. Using salt tolerance compartmentalized self-replication (stCSR) and a microfluidic platform, we obtained 11 mutant sites with enhanced salt tolerance attributes. Sequencing and biochemical analyses revealed that the substitution of conserved amino acids such as G197D, Y369E, T372N, and I378R plays a critical role in maintaining the processivity of exonuclease-deficient phi29 polymerase under high salt conditions. Furthermore, Y369E and T372N have been identified as important determinants of DNA polymerase binding affinity. This study provides insights into optimizing polymerase processability under high-salt conditions for real-time polymerase nanopore sequencing, paving the way for improved performance and applications in nanopore sequencing technologies. [ABSTRACT FROM AUTHOR]

Cementing carbonate reservoirs is generally a difficult task. The so-called thixotropic cement slurry has gained considerable attention in this regard as it can help to fix some notable problems. More precisely, it can easily fill the leakage layer; moreover, its gelling strength can grow rapidly when pumping stops, thereby increasing the resistance to gas channeling, effectively preventing this undesired phenomenon in many cases. High-temperature thixotropic cement slurry systems, however, are still in an early stage of development and additional research is needed to make them a viable option. In the present study, using a self-developed composite high-temperature thixotropic additive as a basis, it is shown that the compressive strength can be adjusted by tuning the proportion of silica sand, the high-temperature retarder, fluid loss additive and dispersant (compatible with the thixotropic additive). According to the tests, the developed high-temperature thixotropic cement slurry system has a 14 d compressive strength of 29.73 MPa at 150°C, and a thickening time of 330 min when the dosage of retarder is 2%. At the same time, the rheological property, water loss, permeability, water separation rate, and settlement stability of the cement slurry system meet the requirements of cementing construction. [ABSTRACT FROM AUTHOR]

Background: At present, how to identify the benign or malignant nature of small (≤ 2 cm) solitary pulmonary nodules (SPN) are an urgent clinical challenge. This retrospective study aimed to develop a clinical prediction model combining clinical and radiological characteristics for assessing the probability of malignancy in SPNs measuring ≤ 2 cm. Method: In this study, we included patients with SPNs measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to December 2021. Clinical features, preoperative biomarker results, and computed tomography characteristics were collected. The enrolled patients were randomized at a ratio of 7:3 into a training cohort of 775 and a validation cohort of 331. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. The receiver operating characteristic (ROC) curve was used to evaluate the identification ability of the model. The calibration power was evaluated using the Hosmer-- Lemeshow test and calibration curve. The clinical utility of the nomogram was also assessed by decision curve analysis (DCA). Result: A total of 1,106 patients were included in this study. Among them, the malignancy rate of SPNs was 85.08% (941/1,106). We finally identified the following six independent risk factors by logistic regression: age, carcinoembryonic antigen, nodule shape, calcification, maximum diameter, and consolidation-to-tumor ratio. The area under the ROC curve (AUC) for the training cohort was 0.764 (95% confidence interval [CI]: 0.714--0.814), and the AUC for the validation cohort was 0.729 (95% CI: 0.647--0.811), indicating that the prediction accuracy of nomogram was relatively good. The calibration curve of the predictive model also demonstrated a good calibration in both cohorts. DCA proved that the clinical prediction model was useful in clinical practice. Conclusion: We developed and validated a predictive model and nomogram for estimating the probability of malignancy in SPNs measuring ≤ 2 cm. With the application of predictive models, thoracic surgeons can make more rational clinical decisions while avoiding overtreatment and wasting medical resources. [ABSTRACT FROM AUTHOR]

The seismic response of buildings is crucial for structural performance analysis. For structures with complete design data, the seismic response can be predicted using finite element analysis. However, for structures lacking necessary information, building finite element models and predicting their seismic response can be challenging. Compared to finite element analysis, convolutional neural networks (CNNs) can establish a neural network mapping relationship between the structure and the seismic response to predict the structural response without design data. In this paper, a structural response prediction model based on CNNs is established, aiming to analyze the effect of natural frequency reduction on the structural response after the Tohoku earthquake. The successful prediction of the structural acceleration and displacement response provides a new analytical method for predicting the seismic response of buildings lacking design data. [ABSTRACT FROM AUTHOR]

Stepwise mini-incision microdissection testicular sperm extraction (mTESE) is a procedure that attempts to minimize testicular damage. However, the mini-incision approach may vary in patients with different etiologies. Here, we performed a retrospective analysis of 665 men with nonobstructive azoospermia (NOA) who underwent stepwise mini-incision mTESE (Group 1) and 365 men who underwent standard mTESE (Group 2). The results showed that the operation time (mean ± standard deviation) for patients with successful sperm retrieval in Group 1 (64.0 ± 26.6 min) was significantly shorter than that in Group 2 (80.2 ± 31.3 min), with P<0.001. The total sperm retrieval rate (SRR) was 23.1% in our study, and there was no significant difference between Group 1 and Group 2 (P>0.05), even when the etiologies of NOA were taken into consideration. The results of consecutive multivariate logistic regression analysis (odds ratio [OR]: 0.57; 95% confidence interval [CI]: 0.38-0.87; P=0.009) and receiver operating characteristic (ROC) analysis (area under the ROC curve [AUC]=0.628) showed that preoperative anti-Müllerian hormone (AMH) level in idiopathic NOA patients was a potential predictor for surgical outcomes after initial three small incisions made in the equatorial region without sperm examined under an operating microscope (Steps 2-4). In conclusion, stepwise mini-incision mTESE is a useful technique for NOA patients, with comparable SRR, less surgical invasiveness, and shorter operation time compared with the standard approach. Low AMH levels may predict successful sperm retrieval in idiopathic patients even after a failed initial mini-incision procedure. [ABSTRACT FROM AUTHOR]

Infrared imaging is widely used due to its penetration capability to operate under many weather or lighting condition. However, due to the far distance of aerial view, feature blur, and the scarcity of aerial infrared data, the detection of small infrared targets on the water surface remains a challenging problem. In response to the problem of unclear features, we propose the spatial feature weighting method based on 2D Gaussian distribution. This method increases the weight of the target area by adaptively adjusting the feature activation. Secondly, for the problem of rare aerial perspective infrared data, we propose the cross‐spectral data migration method. By introducing the domain difference loss function to optimize the pseudo‐label selection process, the range of target domain distribution is expanded, and the adaptability of the detector is improved. Finally, in response to the problem of underfitting caused by category imbalance in transfer learning, we propose the class balancing method that effectively reduces the false detection. Extensive experiments were conducted on both benchmark datasets and the self‐built dataset to evaluate the effectiveness and robustness of our method. The proposed method was evaluated with different models and various scenarios, and the results demonstrated the effectiveness. [ABSTRACT FROM AUTHOR]

In frequency domain, power spectrum density with evenly spaced discrete lines forms a frequency comb, which has become a fundamental physical concept for wave. Especially, in optical electromagnetic wavebands, an optical frequency comb plays a crucial role for a variety of precision measurement technologies and has become one of the representative breakthroughs in modern physics. To extend the study of frequency comb to other wave region would be an interesting and important task. One significant challenge is to develop a general method suitable to different waves. Here, by manipulation one of the essence natures of wave, orbital angular momentum (OAM), we demonstrate an general approach to produce a frequency comb based on a rotational Doppler effect with the OAM comb. We experimentally generate and verify frequency comb with teeth up to 10. Our results not only provide a general way for the frequency comb generation suitable to various waves but also may open up possibilities for application of frequency comb in more types of wave. [ABSTRACT FROM AUTHOR]

Deep learning-based algorithms for single object tracking (SOT) have shown impressive performance but remain susceptible to adversarial patch attacks. However, existing adversarial patch generation methods primarily focus on generating patches within the search region, neglecting the incorporation of template information, which limits their effectiveness in carrying out successful attacks. There is also a lack of evaluation metrics to assess the patch's adversarial abilities. In this study, we propose a bilateral adversarial patch-generating network to address these limitations and advance the field of adversarial patch generation for SOT networks. Our network leverages a Focus structure that effectively integrates both template and search region information, generating separate adversarial patches for each branch. We also introduce the DeFocus structure to solve the size discrepancy between the template and search region of the tracking network. To effectively mislead the tracking network, we have designed adversarial object loss and adversarial regression loss functions tailored to the network's output. Moreover, we propose a comprehensive evaluation metric that measures the patch's adversarial ability by establishing a relationship between the relative patch size and attack performance. As UAV view data often constitute small objects requiring smaller patches, we evaluate our approach on the UAV123 and UAVDT datasets. Our evaluation encompasses not only the overall attack performance but also the effectiveness of our strategy and the transferability of the attacks. Experimental results demonstrate that our algorithm generates patches with higher attack efficiency compared to existing methods. [ABSTRACT FROM AUTHOR]

Crystal structure predictions based on first-principles calculations have gained great success in materials science and solid state physics. However, the remaining challenges still limit their applications in systems with a large number of atoms, especially the complexity of conformational space and the cost of local optimizations for big systems. Here, we introduce a crystal structure prediction method, MAGUS, based on the evolutionary algorithm, which addresses the above challenges with machine learning and graph theory. Techniques used in the program are summarized in detail and benchmark tests are provided. With intensive tests, we demonstrate that on-the-fly machine-learning potentials can be used to significantly reduce the number of expensive first-principles calculations, and the crystal decomposition based on graph theory can efficiently decrease the required configurations in order to find the target structures. We also summarized the representative applications of this method on several research topics, including unexpected compounds in the interior of planets and their exotic states at high pressure and high temperature (superionic, plastic, partially diffusive state, etc.); new functional materials (superhard, high-energy-density, superconducting, photoelectric materials), etc. These successful applications demonstrated that MAGUS code can help to accelerate the discovery of interesting materials and phenomena, as well as the significant value of crystal structure predictions in general. [ABSTRACT FROM AUTHOR]

Background: With the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging. Methods: A retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors. Results: A total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful. Conclusion: The nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery. [ABSTRACT FROM AUTHOR]

Background: Clinical competency is the ability to integrate knowledge, skills, attitudes and values into a clinical situation and it is very important in nursing education, clinical settings, nursing management, and crises. This study aimed to investigate nurses' professional competence and its correlates before and during the COVID-19 pandemic. Methods: We conducted this cross-sectional study before and during the COVID-19 outbreak and recruited all nurses working in hospitals affiliated to Rafsanjan University of Medical Sciences, southern Iran, so we included 260 and 246 nurses in the study before and during the COVID-19 epidemic, respectively. Competency Inventory for Registered Nurses (CIRN) was used to collect data. After inputting the data into SPSS24, we analysed them using descriptive statistics, chi-square and multivariate logistic tests. A significant level of 0.05 was considered. Results: The mean clinical competency scores of nurses were 156.97 ± 31.40 and 161.97 ± 31.36 before and during the COVID-19 epidemic, respectively. The total clinical competency score before the COVID-19 epidemic was not significantly different from that during the COVID-19 epidemic. Interpersonal relationships (p = 0.03) and desire for research/critical thinking (p = 0.01) were significantly lower before the COVID-19 outbreak than during the COVID-19 outbreak. Only shift type had an association with clinical competency before the COVID-19 outbreak, while work experience had an association with clinical competency during the COVID-19 epidemic. Conclusion: The clinical competency among nurses was moderate before and during the COVID-19 epidemic. Paying attention to the clinical competence of nurses can improve the care conditions of patients, and nursing managers should improve the clinical competence of nurses in different situations and crises. Therefore, we suggest further studies identifying factors improving the professional competency among nurses. [ABSTRACT FROM AUTHOR]

As a recently named rare renal tumor of epithelial origin, papillary renal neoplasm with reverse polarity (PRNRP) has unique histomorphological features and immunophenotypes, often associated with KRAS mutations and showing indolent biological behavior. In this study, we report a case of PRNRP. In this report, nearly all tumor cells were positive for GATA-3, KRT7, EMA, E-Cadherin, Ksp-Cadherin, 34bE12, and AMACR in varying intensities, focally positive for CD10 and Vimentin, while negative for CD117, TFE3, RCC, and CAIX. KRAS mutations (exon 2) were detected by amplification refractory mutation system polymerase chain reaction (ARMS-PCR), while no NRAS (exon 2-4) and BRAF V600 mutations (exon 15) were detected. A transperitoneal Robot-Assisted Laparoscopic Partial Nephrectomy was performed on the reported patient. No recurrence or metastasis was found during the 18 months of follow-up. [ABSTRACT FROM AUTHOR]

With the ongoing development of image technology, the deployment of various intelligent applications on embedded devices has attracted increased attention in the industry. One such application is automatic image captioning for infrared images, which involves converting images into text. This practical task is widely used in night security, as well as for understanding night scenes and other scenarios. However, due to the differences in image features and the complexity of semantic information, generating captions for infrared images remains a challenging task. From the perspective of deployment and application, to improve the correlation between descriptions and objects, we introduced the YOLOv6 and LSTM as encoder-decoder structure and proposed infrared image caption based on object-oriented attention. Firstly, to improve the domain adaptability of the detector, we optimized the pseudo-label learning process. Secondly, we proposed the object-oriented attention method to address the alignment problem between complex semantic information and embedded words. This method helps select the most crucial features of the object region and guides the caption model in generating words that are more relevant to the object. Our methods have shown good performance on the infrared image and can produce words explicitly associated with the object regions located by the detector. The robustness and effectiveness of the proposed methods were demonstrated through evaluation on various datasets, along with other state-of-the-art methods. Our approach achieved BLUE-4 scores of 31.6 and 41.2 on KAIST and Infrared City and Town datasets, respectively. Our approach provides a feasible solution for the deployment of embedded devices in industrial applications. [ABSTRACT FROM AUTHOR]

Template matching is the fundamental task in remote sensing image processing of air- and space-based platforms. Due to the heterogeneous image sources, different scales and different viewpoints, the realization of a general end-to-end matching model is still a challenging task. Considering the abovementioned problems, we propose a cross-view remote sensing image matching method. Firstly, a spatial attention map was proposed to solve the problem of the domain gap. It is produced by two-dimensional Gaussian distribution and eliminates the distance between the distributed heterogeneous features. Secondly, in order to perform matching at different flight altitudes, a multi-scale matching method was proposed to perform matching on three down-sampling scales in turn and confirm the optimal result. Thirdly, to improve the adaptability of the viewpoint changes, a pixel-wise consensus method based on a correlation layer was applied. Finally, we trained the proposed model based on weakly supervised learning, which does not require extensive annotation but only labels one pair of feature points of the template image and search image. The robustness and effectiveness of the proposed methods were demonstrated by evaluation on various datasets. Our method accommodates three types of template matching with different viewpoints, including SAR to RGB, infrared to RGB, and RGB to RGB. [ABSTRACT FROM AUTHOR]

The "low, slow, and small" target (LSST) poses a significant threat to the military ground unit. It is hard to defend against due to its invisibility to numerous detecting devices. With the onboard deep learning-based object detection methods, the intelligent LSST (ILSST) can find and detect the ground unit autonomously in a denied environment. This paper proposes an adversarial patch-based defending method to blind the ILSST by attacking its onboard object detection network. First, an adversarial influence score was established to indicate the influence of the adversarial noise on the objects. Then, based on this score, we used the least squares algorithm and Bisectional search methods to search the patch's optimal coordinates and size. Using the optimal coordinates and size, an adaptive patch-generating network was constructed to automatically generate patches on ground units and hide the ground units from the deep learning-based object detection network. To evaluate the efficiency of our algorithm, a new LSST view dataset was collected, and extensive attacking experiments are carried out on this dataset. The results demonstrate that our algorithm can effectively attack the object detection networks, is better than state-of-the-art adversarial patch-generating algorithms in hiding the ground units from the object detection networks, and has high transferability among the object detection networks. [ABSTRACT FROM AUTHOR]

Renal fibrosis (RF) is the common pathological manifestation of virtually all chronic kidney diseases (CKD) and one of the major causes of end-stage renal disease (ESRD), but the pathogenesis of which is still unclear. Renal tubulointerstitial lesions have been identified as a key pathological hallmark of RF pathology. Renal tubular epithelial cells are the resident cells of the tubulointerstitium and play an important role in kidney recovery versus renal fibrosis following injury. Studies in recent years have shown that senescence of renal tubular epithelial cells can accelerate the progression of renal fibrosis. Oxidative stress(OS), telomere attrition and DNA damage are the major causes of renal tubular epithelial cell senescence. Current interventions and therapeutic strategies for cellular senescence include calorie restriction and routine exercise, Klotho, senolytics, senostatics, and other related drugs. This paper provides an overview of the mechanisms and the key signaling pathways including Wnt/bcatenin/ RAS, Nrf2/ARE and STAT-3/NF-kB pathway involved in renal tubular epithelial cell senescence in RF and therapies targeting renal tubular epithelial cell senescence future therapeutic potential for RF patients. These findings may offer promise for the further treatment of RF and CKD. [ABSTRACT FROM AUTHOR]

Background: There is no definitive and detailed treatment guideline for advanced thymic tumors, thus when lymph node and other organ metastasis are present, clinical guidelines recommend chemotherapy-based multidisciplinary treatment. A consensus has been reached that surgery has beneficial effects on partial patients with stage IVA whose metastatic lesions were isolated and resectable, but because of few cases of advanced thymic tumor s and the scarcity of reports, the role of surgery in stage IVB is still unknown. The current study aimed to systematically analyze the role of surgery in advanced thymic tumors based on the Surveillance, Epidemiology, and End Results (SEER) database, with a sufficient number of cases. A secondary aim was to clarify the prognostic value of surgery in advanced thymic tumors. Method: Data derived from a total of 979 patients with advanced thymoma or advanced thymic carcinoma were collected from the SEER database. Propensity score matching was performed to eliminate confounding factors, and Cox regression analyses were conducted to assess prognoses. Results: Patients were assigned to four groups based on pathology and whether surgery was performed; thymoma (surgery), thymoma (no surgery), thymic carcinom a (surgery), and thymic carcinoma (no surgery). Diseasespecific survival differed significantly in the thymoma (surgery) and thymoma (no surgery) groups, both before and after propensity score matching (both p < 0.001). Similarly, disease-specific survival differed significantly in the thymic carcinoma (surgery) and the thymic carcinoma (no surgery) groups (p < 0.001 before and p = 0.003 after). No total resection, distant metastasis, and thymic carcinoma were all unfavorable prognostic factors. Conclusions: In the present study surgery had positive effects on advanced thymoma and advanced thymic carcinoma patients who could undergo surgical resection, significantly improving survival times. Total resection of the primary site was the most advantageous form of surgery. The study provides a reference for the clinical treatment of advanced thymic tumors. [ABSTRACT FROM AUTHOR]

In this paper, we consider the existence of positive solutions for a semipositone thirdorder nonlinear ordinary differential equation on time scales. In suitable growth conditions, by considering the properties on time scales and establishing a special cone, some new results on the existence of positive solutions are established when the nonlinearity is semipositone. [ABSTRACT FROM AUTHOR]

Both biotic and abiotic factors continually affect the phyllospheric ecology of plants. A better understanding of the drivers of phyllospheric community structure and multitrophic interactions is vital for developing plant protection strategies. In this study, 16S rRNA high-throughput sequencing was applied to study how summer climatic factors and bacterial wildfire disease have affected the composition and assembly of the bacterial community of tobacco (Nicotiana tabacum L.) phyllosphere. Our results indicated that three time series groups (T1, T2 and T3) formed significantly distinct clusters. The neutral community model (NCM) and beta nearest taxon index (betaNTI) demonstrated that the overall bacterial community assembly was predominantly driven by stochastic processes. Variance partitioning analysis (VPA) further showed that the complete set of the morbidity and climatic variables together could explain 35.7% of the variation of bacterial communities. The node numbers of the molecular ecological networks (MENs) showed an overall uptrend from T1 to T3. Besides, Pseudomonas is the keystone taxa in the MENs from T1 to T3. PICRUSt2 predictions revealed significantly more abundant genes of osmoprotectant biosynthesis/transport in T2, and more genes for pathogenicity and metabolizing organic substrate in T3. Together, this study provides insights into spatiotemporal patterns, processes and response mechanisms underlying the phyllospheric bacterial community. [ABSTRACT FROM AUTHOR]

Background: An increasing number of patients are being diagnosed with synchronous multiple primary lung cancer (SMPLC) with the popularization of lung cancer screening programs. However, a strategy for accurate location and suitable surgery therapy is still lacking. The present study aimed to explore the accuracy and feasibility of elec- tromagnetic navigation bronchoscopy (ENB)-guided thoracoscopic sublobectomy for stage IA SMPLC. Methods: Patients with SMPLC who underwent ENB-guided sublobectomy from January 2020 to June 2022 were enrolled in this study. The analysis of localization accuracy of ENB and surgical outcome was conducted. Results: Overall, 138 patients with 353 malignant nodules were enrolled. The tumor size was 0.7 cm (range from 0.5 to 1.1 cm). ENB localization was performed on 162 nodules, and a customized scoring system was developed to evaluate localization accuracy. The success rate of localization was 98.3% (178/181). Notably, localization accuracy was positively correlated with bronchial signs (p < 0.01) and negatively correlated with the distance from the nodule to the pleura (p = 0.02). All nodules were completely resected. Operation time, drainage volume on the third postoperative day, and catheter time were significantly correlated with the resected lesion numbers (p = 0.009, p = 0.004, and p = 0.01, respectively). Conclusions: ENB-guided uniportal video-assisted thoracoscopic sublobectomy provides accurate preoperative localization and avoids unnecessary lung resection of patients with stage IA SMPLC. However, complete resection of multilocation nodules (more than four lesions) increases the risk of postoperative complications. A new combined treatment strategy for SMPLC should be explored. [ABSTRACT FROM AUTHOR]

Mulberry tree (Morus alba) has a wide ecological distribution attributed to its strong adaptability and is also an important perennial economic tree species. However, the molecular mechanisms responsible for its adaptability remain unknown. Ascorbate peroxidase (APX) is a key antioxidant enzyme that defends against oxidative damage in plants under various stresses. In this study, the abundance of mulberry APX (MaAPX) in leaves was upregulated under drought stress. MaAPX, located in the cytoplasmic membrane and nucleus, is a transmembrane hydrophilic protein that is not a secretory signaling protein and can be phosphorylated. The full-length of its coding gene, MaAPX, is 750 bp. The expression of MaAPX changed with natural light and seasons under field condition and varied among mulberry cultivars and was not related to genome duplication. MaAPX expression in leaves and roots was influenced by many abiotic stress and exogenous hormones treatments. Under heat and NaCl stress, it was downregulated in leaves but upregulated in roots. Under drought stress, MaAPX expression was upregulated in both leaves and roots. Under ethylene and ABA treatment, MaAPX expression decreased in leaves but increased in roots. Under salicylic acid treatment, it slightly decreased in both leaves and roots. Our work provides a comprehensive analysis of the expression on MaAPX, which lays a foundation for further MaAPX function exploration and genetic application research in mulberry. [ABSTRACT FROM AUTHOR]

Background: N-Alpha-Acetyltransferase 50 (NAA50) has acetyltransferase activity and is important for chromosome segregation. However, the function and mechanism of NAA50 expression in cancer development was still unclear. Here, we systematically researched the function and mechanism of NAA50 in pan-cancer, and further verified the results of NAA50 in lung adenocarcinoma (LUAD). Methods: In this study, using the online databases TIMER2.0, SangerBox3.0, HPA, UCSC, GEPIA, cBioPortal, UALCAN, TISIDB, CancerSEA and LinkedOmics, we focused on the relevance between NAA50 and oncogenesis, progression, methylation, immune infiltration, function and prognosis. In addition, the proliferation of cells was detected by CCK-8 and Edu assay. Finally, we analyzed the relationship between the expression of NAA50 and cell cycle related proteins. Results: Pan-cancer analysis indicated that NAA50 was overexpressed in most cancers. And there was a significant correlation between NAA50 expression and the prognosis of cancer patients. In the meantime, NAA50 gene changes occur in a variety of tumors. Compared with normal tissues, the methylation level of NAA50 promoter increased in most cancer tissues. In addition, the results exhibited that in most cancers, NAA50 was significantly positively correlated with bone myeloid-derived suppressor cell (MDSC) infiltration and negatively correlated with T cell NK infiltration. Moreover, functional enrichment indicated that NAA50 regulates cell cycle and proliferation in LUAD. In vitro experiments testified that knockout of NAA50 could significantly inhibit the proliferation of LUAD. Conclusion: NAA50 may be a potential biomarker and oncogene of pancancer, especially LUAD, which may promote the occurrence and development of tumors through different mechanisms. Furthermore, NAA50 was bound up with to immune cell infiltration in pan-cancer, meaning NAA50 may be an important therapeutic target for human cancers. [ABSTRACT FROM AUTHOR]

With the current popularity of Electric Vehicles (EV), especially in some critical EV applications such as hospital EV fleets, the demand for continuous and reliable power supply is increasing. However, most of the charging stations are powered in a centralized way, which causes transistors and other components to be subjected to high voltage and current stresses that reduce reliability, and a single point of failure can cause the entire system to fail. Therefore, a significant effort is made in this paper to improve the reliability of the charging system. In terms of charging system structure design, a distributed charging structure with fault tolerance is designed and a mathematical model to evaluate the reliability of the structure is proposed. In terms of control, a current sharing control algorithm is designed that can achieve fault tolerance. To further improve the reliability of the system, a thermal sharing control method based on current sharing technology is also designed. This method can improve the reliability of the charging system by distributing the load more rationally according to the differences in component performance and operating environment; FPGA-based control techniques are provided, and innovative ideas of pipeline control and details of mathematical reasoning for key IP cores are presented. Experiments show that N + 1 redundancy fault tolerance can be achieved in both current sharing and thermal sharing modes. In the current sharing experiment, when module 3 failed, the total current only fluctuated 800 mA within 500 ms, which is satisfactory. In the thermal sharing experiment, after module 3 failed, modules 1, 2, and 4 adjusted the current reasonably under the correction of the thermal sharing loop, and the total current remained stable throughout the process. The experimental results prove that the charging system structure design and control method proposed in this paper are feasible and excellent. [ABSTRACT FROM AUTHOR]

Mitochondrial plasticity including mitochondrial dynamics, metabolic flexibility, and mitochondrial quality control, impact tumor cells' progression and determine immune cells' fate. Complement C1q binding protein (C1QBP) plays an indispensable role through regulating mitochondrial morphology, metabolism, and autophagy. C1QBP promotes mitochondrial plasticity to impact tumor metastasis and their therapeutic response. At the same time, C1QBP is involved in regulating immune cells' maturation, differentiation, and effector function through the enhancement of mitochondrial function. In this regard, manipulation of C1QBP has been shown to adjust the competitive balance between tumor cells and immune cells. In the course of evolution, mitochondrial plasticity has endowed numerous advantages against the relentless microenvironment of tumors. In this current review, we summarize the current knowledge of the mechanism of C1QBP regulation of cancer and immunity. We explain this process in vision of potentially new anticancer therapies. [ABSTRACT FROM AUTHOR]

The Internet of Vehicles (IoV), with the help of cloud computing, can provide rich and powerful application services for vehicles and drivers by sharing and analysing various IoV data. However, how to ensure the integrity of IoV data with multiple sources and diversity outsourced in the cloud is still an open challenge. To address this concern, this paper first presents an identity-based public auditing scheme for cloud storage of IoV data, which can fully achieve the essential function and security requirements, such as classified auditing, multi-source auditing and privacy protection. Particularly, we design a new authenticated data structure, called data mapping table, to track the distribution of each type of IoV data to ensure fine and rapid audits. Moreover, our scheme can reduce the overheads for both the key management and the generation of block tags. We formally prove the security of the presented scheme and evaluate its performance by comprehensive comparisons with the state-of-the-art schemes designed for traditional scenarios. The theoretical analyses and experimental results demonstrate that our scheme can securely and efficiently realize public auditing for IoV data, and outperforms the previous ones in both the computation and communication overheads in most cases. [ABSTRACT FROM AUTHOR]

Background and Objective: Understanding the tumor microenvironment (TME) and immune cell infiltration (ICI) may help guide immunotherapy efforts for colon cancer (COAD). However, whether ARID1B is truly regulated by hypermethylation or linked to immune infiltration remains unknown. The current work focused on the ARID1B gene expression and methylation in COAD, as well as its relation with ICI. Methods and Results: Multiple tools based on TCGA were used to analyze the differences in the expression of the ARID1B gene, DNA methylation, and its association with various clinicopathological features, somatic mutations, copy number variation, and the prognosis of patients with COAD. According to the analysis results, patients with high mRNA, low methylation levels showed better overall survival than patients with low mRNA, high methylation levels. The correlation analysis of immune cell infiltration and immune checkpoint gene expression showed that the infiltration rates of the main ICI subtypes, cancerassociated fibroblast, and myeloid cells were significantly enriched and correlated with ARID1B in COAD. An association between ARID1B expression and immune infiltration in COAD was found by correlating ICI indicators with ARID1B expression in the immune cell composition of the COAD microenvironment. Notably, M2 chemokines were related to ARID1B expression, while M1 chemokines were not. Conclusion: This study provided evidence that ARID1B may have a role in the pathogenesis of COAD. The specific underlying mechanisms that could be responsible for ARID1B’s downregulation in COAD will need to be investigated in the future. [ABSTRACT FROM AUTHOR]