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Abstract The Hippo pathway is commonly altered in cancer initiation and progression; however, exactly how this pathway becomes dysregulated to promote human cancer development remains unclear. Here we analyze the Hippo somatic mutations in the human cancer genome and functionally annotate their roles in targeting the Hippo pathway. We identify a total of 85 loss-of-function (LOF) missense mutations for Hippo pathway genes and elucidate their underlying mechanisms. Interestingly, we reveal zinc-finger domain as an integral structure for MOB1 function, whose LOF mutations in head and neck cancer promote tumor growth. Moreover, the schwannoma/meningioma-derived NF2 LOF mutations not only inhibit its tumor suppressive function in the Hippo pathway, but also gain an oncogenic role for NF2 by activating the VANGL-JNK pathway. Collectively, our study not only offers a rich somatic mutation resource for investigating the Hippo pathway in human cancers, but also provides a molecular basis for Hippo-based cancer therapy.

Abstract Enriched environment (EE), characterized by multi‐sensory stimulation, represents a non‐invasive alternative for alleviating epileptic seizures. However, the mechanism by which EE exerts its therapeutic impact remains incompletely understood. Here, it is elucidated that EE mitigates seizure susceptibility through the augmentation of adult neurogenesis within the entorhinal cortex (EC) circuit. A substantial upregulation of adult hippocampal neurogenesis concomitant with a notable reduction in seizure susceptibility has been found following exposure to EE. EE‐enhanced adult‐born dentate granule cells (abDGCs) are functionally activated during seizure events. Importantly, the selective activation of abDGCs mimics the anti‐seizure effects observed with EE, while their inhibition negates these effects. Further, whole‐brain c‐Fos mapping demonstrates increased activity in DG‐projecting EC CaMKIIα+ neurons in response to EE. Crucially, EC CaMKIIα+ neurons exert bidirectional modulation over the proliferation and maturation of abDGCs that can activate local GABAergic interneurons; thus, they are essential components for the anti‐seizure effects mediated by EE. Collectively, this study provides compelling evidence regarding the circuit mechanisms underlying the effects of EE treatment on epileptic seizures, shedding light on the involvement of the EC‐DG circuit in augmenting the functionality of abDGCs. This may help for the translational application of EE for epilepsy management.

Abstract Background Spinal tuberculosis (STB) is a local manifestation of systemic infection caused by Mycobacterium tuberculosis, accounting for a significant proportion of joint tuberculosis cases. This study aimed to explore the diagnostic value of MRI combined with mannose-binding lectin (MBL) for STB. Methods 124 patients suspected of having STB were collected and divided into STB and non-STB groups according to their pathological diagnosis. Serum MBL levels were measured using ELISA and a Pearson analysis was constructed to determine the correlation between MBL and STB. ROC was plotted to analyze their diagnostic value for STB. All the subjects included in the study underwent an MRI. Results The sensitivity of MRI for the diagnosis of STB was 84.38% and specificity was 86.67%. The serum MBL levels of the patients in the STB group were significantly lower than the levels in the non-STB group. ROC analysis results indicated that serum MBL’s area under the curve (AUC) for diagnosis of STB was 0.836, with a sensitivity of 82.3% and a specificity was 77.4%. The sensitivity of MRI combined with MBL diagnosis was 96.61%, and the specificity was 92.31%, indicating that combining the two diagnostic methods was more effective than using either one alone. Conclusions Both MRI and MBL had certain diagnostic values for STB, but their combined use resulted in a diagnostic accuracy than either one alone.

Abstract As mechanized open-pit coal mining intensifies, assessing and predicting slope stability has become increasingly important. To address the limitations of traditional mechanical calculations, numerical simulations, and physical experiments, this paper identifies the key factors impacting slope stability in open-pit mines and develops a multi-parameter sample data set. The study employs hyperparameters optimized using a Bayesian algorithm, introduces additional convolutional layers, and combines the Adam optimizer with dropout techniques to enhance the feature extraction and performance of one-dimensional convolutional neural networks (1D-CNN). This leads to a Bayesian-optimized one-dimensional convolutional neural network (B-1D MCNN) model for predicting slope stability.The study evaluates the classification performance and accuracy of various models for slope stability, including BP neural networks, genetic algorithm-optimized convolutional neural networks, 1D-CNN, and B-1D MCNN, using accuracy, precision, and F1-score as metrics. The analysis also examines the influence of factor indicators and training set length on the model's output to assess its generalization capabilities.The research findings suggest that: (1) the B-1D MCNN model for evaluating slope stability demonstrates the capability to accurately depict the nonlinear correlation between influencing factors and slope stability. (2) Compared with other models, the B-1D MCNN model has shown enhancements of 10.96% to 27.85%, 10.26% to 28.55%, and 8.98% to 25.05% in terms of Accuracy, F1-Score, and Precision, respectively. (3) As the length of the training dataset increases, the performance of the model improves accordingly. (4) The B-1D MCNN model shows a generalization power of 87.5%.

Given a graph G and an integer [Formula: see text], a spanning subgraph H of G is called a [Formula: see text]-factor of G if every component of H is a path with at least k vertices. A graph G is [Formula: see text]-factor avoidable if for every edge [Formula: see text], G has a [Formula: see text]-factor excluding e. A graph G is said to be [Formula: see text]-factor critical avoidable if the graph [Formula: see text] is [Formula: see text]-factor avoidable for any [Formula: see text] with [Formula: see text]. Here we study the sharp bounds of toughness and isolated toughness conditions for the existence of [Formula: see text]-factor critical avoidable graphs. In view of graph theory approaches, this paper mainly contributes to verify that (i) An [Formula: see text]-connected graph is [Formula: see text]-factor critical avoidable if its toughness [Formula: see text]; (ii) An [Formula: see text]-connected graph is [Formula: see text]-factor critical avoidable if its isolated toughness [Formula: see text].

With the prevalence of sequentially-emerged sublineages including BA.1, BA.2 and BA.5, SARS-CoV-2 Omicron infection has transformed into a regional epidemic disease. As a sublineage of BA.5, the BA.5.2.48 outbroke and evolved into multi-subvariants in China without clearly established virological characteristics. Here, we evaluated the virological characteristics of two isolates of the prevalent BA.5.2.48 subvariant, DY.2 and DY.1.1 (a subvariant of DY.1). Compared to the normal BA.5 spike, the double-mutated DY.1.1 spike demonstrates efficient cleavage, reduced fusogenicity and higher hACE2 binding affinity. BA.5.2.48 demonstrated enhanced airborne transmission capacity than BA.2 in hamsters. The pathogenicity of BA.5.2.48 is greater than BA.2, as revealed in Omicron-lethal H11-K18-hACE2 rodents. In both naïve and convalescent hamsters, DY.1.1 shows stronger fitness than DY.2 in hamster turbinates. Thus regional outbreaking of BA.5.2.48 promotes the multidirectional evolution of its subvariants, gaining either enhanced pathogenicity or a fitness in upper airways which is associated with higher transmission.

Objective Tread defects are a primary manifestation of wheel failures in high-speed railway EMU (electrical multiple unites) trains, significantly impacting both EMU train operation safety and passenger ride comfort. Wheel tread defects are predominantly concentrated on front and rear cars, which may result from a combination of various factors, requiring predictive method that comprehensively integrate various influencing factors. Method Based on the wheel reprofiling maintenance data of EMU train operated by a railway bureau, the dataset sample consists of 10 features (including 4 nominal and 6 continuous features) and the data are preprocessed. By treating the imbalanced dataset through synthetic minority over-sampling technique (SMOTE), a standardized dataset is constructed. A DNN (deep neural network) model is established to combine the underlying features and form a high-level abstract representation of the features. The optimal learning performance of the model is achieved through network structure adjustment and hyperparameter optimization. The model is trained and tested to verify its prediction effect. Result & Conclusion The data-driven prediction method for wheel tread defects of front and rear cars demonstrates high-predictive accuracy and relatively excellent comprehensive performance, achieving a precision rate of 92.5%. Thus the probability of wheel tread damage of front and rear cars can be effectively predicted.

Abstract Background The safety and efficacy of two-stage revision for culture-negative PJI remain controversial. This study analyzed outcomes after two-stage revision in patients with culture-negative and culture-positive periprosthetic joint infection (PJI) during follow-up lasting at least two years. Methods Data were retrospectively analysed patients who underwent hip or knee revision arthroplasty from January 2008 to October 2020 at our medical center. The primary outcome was the re-revision rate, while secondary outcomes were the rates of reinfection, readmission, and mortality. Patients with culture-negative or culture-positive PJI were compared in terms of these outcomes, as well as survival time without reinfection or revision surgery, based on Kaplan‒Meier analysis. Results The final analysis included 87 patients who were followed up for a mean of 72.3 months (range, 24–123 months). The mean age was 58.1 years in the culture-negative group (n = 24) and 59.1 years in the culture-positive group (n = 63). The two groups (culture-negative versus culture-positive) did not differ significantly in rates of re-revision (0.0% vs. 3.2%, p > 0.05), reinfection (4.2% vs. 3.2%, p > 0.05), readmission (8.4% vs. 8.0%, p > 0.05), or mortality (8.3% vs. 7.9%, p > 0.05). They were also similar in survival rates without infection-related complications or revision surgery at 100 months (91.5% in the culture-negative group vs. 87.9% in the culture-positive group; Mantel‒Cox log-rank χ2 = 0.251, p = 0.616). Conclusion The two-stage revision proves to be a well-tolerated and effective procedure in both culture-negative and culture-positive PJI during mid to long-term follow-up.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a significant threat to human health globally. It is crucial to develop a vaccine to reduce the effect of the virus on public health, economy, and society and regulate the transmission of SARS-CoV-2. Influenza B virus (IBV) can be used as a vector that does not rely on the current circulating influenza A strains. In this study, we constructed an IBV-based vector vaccine by inserting a receptor-binding domain (RBD) into a non-structural protein 1 (NS1)-truncated gene (rIBV-NS110-RBD). Subsequently, we assessed its safety, immunogenicity, and protective efficacy against SARS-CoV-2 in mice, and observed that it was safe in a mouse model. Intranasal administration of a recombinant rIBV-NS110-RBD vaccine induced high levels of SARS-CoV-2-specific IgA and IgG antibodies and T cell-mediated immunity in mice. Administering two doses of the intranasal rIBV-NS110-RBD vaccine significantly reduced the viral load and lung damage in mice. This novel IBV-based vaccine offers a novel approach for controlling the SARS-CoV-2 pandemic.

To study the quality characteristics of different apple varieties and establish a comprehensive evaluation model of apple quality, taking five varieties of apples (Tianshui Huaniu, Aksu Tangxin, Marshal Huang, Cream Fuji, and Luochuan Red Fuji) as the research object, the four texture characteristics, including hardness, adhesion, chewability, cohesion, and four physical and chemical indicators, including water content, titratable acid (TA), soluble sugar (SS), and soluble solid content (SSC) were tested. Combining the low-field nuclear magnetic resonance detection technology, the correlation between the water distribution and the physicochemical and texture characteristics of apple was explored, and the main indicators for evaluating apple quality were established by principal component analysis. Based on the entropy weight method, each core index was given weight, and a grey correlation degree evaluation model was established. The results showed that there were significant differences in various indexes of different varieties of apples (P

In this article, a honeycomb vertical surrounding gate access transistor array scheme is proposed to further decrease the DRAM cell area with aggressively shrink bit line (BL) pitch and word line (WL) pitch adopting the ZigZag BL and WL air gap. To verify the process feasibility, process flow emulation is optimized by virtual fabrication with SEMulator3D®. Moreover, the ZigZag BL feasibility in lithography process is evaluated by optical proximity correction (OPC) simulation. In addition, the parasitic capacitance of BL and WL decrease 22.8% and 76.8%, respectively, as compared to reference paper. And the electrical properties of the proposed device are simulated by three-dimensional technology computer aided design (3D TCAD). The GIDL effect is prohibited through prolonging the drain extension and reducing its doping concentration. Finally, the surrounding gate transistor can achieve high on-state current ( $30~\mu \text{A}$ ) at $\text{V}_{\mathrm {g}}=1.5$ V and off-state current below 0.1 fA at $\text{V}_{\mathrm {d}}= -0.2$ V. These results are beneficial for the direction of pathfinding for increasing the density and decreasing the energy consumption of DRAM.

Automatic ship detection is a crucial task within the domain of maritime transportation management. With the progressive success of convolutional neural networks (CNNs), a number of advanced CNN models have been presented in order to detect ships. Although these detection models have achieved marked performance, several undesired results may occur under complex maritime conditions, such as missed detections, false positives, and low detection accuracy. Moreover, the existing detection models endure large number of parameters and heavy computation cost. To deal with these problems, we suggest a lightweight ship model of detection called DSSM–LightNet based upon the improved YOLOv8n. First, we introduce a lightweight Dual Convolutional (DualConv) into the model to lower both the number of parameters and the computational complexity. The principle is that DualConv combines two types of convolution kernels, 3x3 and 1x1, and utilizes group convolution techniques to effectively reduce computational costs while processing the same input feature map channels. Second, we propose a Slim-neck structure in the neck network, which introduces GSConv and VoVGSCSP modules to construct an efficient feature-fusion layer. This fusion strategy helps the model better capture the features of targets of different sizes. Meanwhile, a spatially enhanced attention module (SEAM) is leveraged to integrate with a Feature Pyramid Network (FPN) and the Slim-neck to achieve simple yet effective feature extraction, minimizing information loss during feature fusion. CIoU may not accurately reflect the relative positional relationship between bounding boxes in some complex scenarios. In contrast, MPDIoU can provide more accurate positional information in bounding-box regression by directly minimizing point distance and considering comprehensive loss. Therefore, we utilize the minimum point distance IoU (MPDIoU) rather than the Complete Intersection over Union (CIoU) Loss to further enhance the detection precision of the suggested model. Comprehensive tests carried out on the publicly accessible SeaShips dataset have demonstrated that our model greatly exceeds other algorithms in relation to their detection accuracy and efficiency, while reserving its lightweight nature.

Luteolin, a naturally occurring pharmaceutical compound with significant antitumor properties, faces challenges in clinical applications due to its low solubility in water and limited bioavailability. To address these issues, a one-step synthesis method was employed to encapsulate luteolin within ZIF-8. The successful preparation of luteolin@ ZIF-8 nanoparticles was confirmed through various analytical techniques, including fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), laser size distribution analysis, X-ray diffraction (XRD), and release curve assessment. Results indicate that the formulated luteolin@ ZIF-8 nanoparticles exhibited high drug loading (1360 mg/g) and demonstrated selective drug release in acidic microenvironments. Furthermore, the encapsulation of luteolin increased the size of ZIF-8 from 168.4 ± 0.2 nm to 384.7 ± 1.4 nm, but did not change its crystalline structure significantly. Notably, the results of in vitro anti-cervical and prostate cancers experiments revealed that luteolin@ ZIF-8 had better efficacy in inhibiting the proliferation and migration of HeLa and PC3 cells than free luteolin. The antitumor activity of luteolin@ ZIF-8 was sustained for 72 h, with a particularly pronounced inhibitory effect on HeLa cells as compared to PC3 cells. This study underscores the effective enhancement of luteolin's antitumor activity through encapsulation in ZIF-8, offering substantial implications for improving its clinical applications.

Summary: Autophagy supports cell survival under different stress conditions, where ATG8-family proteins are required for autophagosome biogenesis/maturation and selective autophagy. Here, we present a protocol for studying ATG8-family protein phosphorylation using Phos-tag gel, a modified SDS-PAGE system, when the related phosphorylation site information and/or specific phospho-antibody are unavailable. We describe steps for generating GST-ATG8 proteins in bacteria, purifying S protein-Flag-SBP protein (SFB)-tagged kinasefrom cells, preparing gel, and an in vitro kinase assay. We then detail procedures for western blotting and image processing.For complete details on the use and execution of this protocol, please refer to Seo et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Curculigoside (CCG) is a phenolic glycoside compound extracted from the root of a natural plant called Curculigo orchioides Gaertn. In this study, the neuroprotective effect of CCG through oxidative stress mediated mitochondrial dysfunction on L-glutamate (L-Glu)-damaged hippocampal neuron cell line (HT22) and APPswe/PSEN1dE9 transgenic (APP/PS1) mice were investigated. Observably, CCG in L-Glu-damaged HT22 cells suppressed apoptosis, reduced the accumulation of reactive oxygen species, balanced the mitochondrial membrane potential and prevented the over-influx of calcium. In APP/PS1 mice, 4-week CCG administration significantly improved their memory and behavioral impairments, enhanced the function of cholinergic system, reduced the deposition of Aβ and neurofibrillary fiber tangles caused by tau phosphorylation, and suppressed the development and progression of oxidative stress in brains of APP/PS1 mice. Based on the screening of proteomic analysis on hippocampus, CCG were confirmed that it could regulate the expression levels of proteins related to mitochondrial dysfunction, mainly through activating on AMPK/Nrf2 signaling, in APP/PS1 mice and L-Glu-exposed HT22 cells. CCG has a prominent neuroprotective effect on regulate the AMPK/Nrf2-mediated mitochondrial dysfunction in cells APP/PS1 mice support CCG is a potentially potent drug for AD treatment and merits further investigation.

Mechanoluminescent (ML) materials can exhibit visible-to-near-infrared mechanoluminescence when responding to the fracture or deformation of a solid under mechanical stimulation. Transforming mechanical energy into light demonstrates promising applications in terms of visual mechanical sensing. In this work, we synthesized the phosphor CaZnOS:Tb3+, Sm3+, which exhibited intense and tunable multicolor mechanoluminescence without pre-irradiation. Intense green ML materials were obtained by doping Tb3+ with different concentrations. Tunable multicolor mechanoluminescence (such as green, yellow-green, and orange-red) could be realized by combining green emission (about 542 nm), attributed to Tb3+, and red emission (about 600 nm) generated from the Sm3+ in the CaZnOS substrate. The tunable multicolor ML materials CaZnOS:Tb3+, Sm3+ exhibited intense luminance and recoverable mechanoluminescence when responding to mechanical stimulation. Benefiting from the excellent ML performance and multicolor tunability in CaZnOS:Tb3+, Sm3+, we mixed the phosphor with PDMS and a curing agent to explore its practical application. An application for visual mechanical sensing was designed for handwriting identification. By taking a time-lapsed shot while writing, we easily obtained images of the writer’s handwriting. The images of the ML intensity were acquired by using specific software to transform the shooting data. We could easily distinguish people’s handwriting through analyzing the different ML performances.

In the realm of medical image analysis, the cost associated with acquiring accurately labeled data is prohibitively high. To address the issue of label scarcity, semi-supervised learning methods are employed, utilizing unlabeled data alongside a limited set of labeled data. This paper presents a novel semi-supervised medical segmentation framework, DCCLNet (deep consistency collaborative learning UNet), grounded in deep consistent co-learning. The framework synergistically integrates consistency learning from feature and input perturbations, coupled with collaborative training between CNN (convolutional neural networks) and ViT (vision transformer), to capitalize on the learning advantages offered by these two distinct paradigms. Feature perturbation involves the application of auxiliary decoders with varied feature disturbances to the main CNN backbone, enhancing the robustness of the CNN backbone through consistency constraints generated by the auxiliary and main decoders. Input perturbation employs an MT (mean teacher) architecture wherein the main network serves as the student model guided by a teacher model subjected to input perturbations. Collaborative training aims to improve the accuracy of the main networks by encouraging mutual learning between the CNN and ViT. Experiments conducted on publicly available datasets for ACDC (automated cardiac diagnosis challenge) and Prostate datasets yielded Dice coefficients of 0.890 and 0.812, respectively. Additionally, comprehensive ablation studies were performed to demonstrate the effectiveness of each methodological contribution in this study.

Accurate ecological water regulation to achieve the optimal coupling between ecological water supply and vegetation water demand is the key challenge for ecological conservation in arid regions. Previous studies have mainly focused on the relationship between vegetation and specific water supply methods in arid regions. However, there has been limited attention to the maximum thresholds of Enhanced Vegetation Index (EVI) and area for vegetation protection and restoration under limited water conditions.Therefore, this study targets the mainstream of the Tarim River and conducts a systematic analysis of the maximum thresholds of EVI and area for vegetation protection and restoration under water constraints. Firstly, vegetation change patterns were discriminated using logistic and Gaussian functions. The results indicated that with enhanced watershed water resources management, both vegetation EVI and Evapotranspiration (ET) showed an increasing trend, which was projected to continue in the future. Based on the discrimination of vegetation change patterns, this study innovatively defined regions with linear, logarithmic, logical, and Gaussian patterns as area expansion zones requiring priority in ensuring ecological water supply, and regions with exponential patterns as quality improvement zones for improving vegetation restoration quality.By extracting vegetation EVI and ET indicators and constructing copula function in the two zones, the joint distribution function revealed that under water constraints, the range of natural vegetation expansion area-EVI threshold in the Tarim River was 17959.02 (EVI: 0.137) ∼ 18279.75 (EVI: 0.137) km2. The maximum threshold of vegetation EVI in the quality improvement zone was 0.223. Under current conditions, the average vegetation EVI in the area expansion zone was 0.137 (stable level), indicating a threshold for natural vegetation restoration of 0.137. During normal water years, besides increasing vegetation EVI to the threshold of natural vegetation restoration, the area could still expand by 665.06 ∼ 985.79 km2, corresponding to a vegetation area threshold of 17959.02 ∼ 18279.75 km2. In wet water years, the natural vegetation area could expand by 5172.53 ∼ 5493.26 km2, with a vegetation area threshold of 22466.49 ∼ 22787.22 km2.

Abstract The integration of metasurfaces and optical waveguides is gradually attracting the attention of researchers because it allows for more efficient manipulation and guidance of light. However, most of the existing studies focus on passive devices, which lack dynamic modulation. This work utilizes the meta‐waveguides with liquid crystal(LC) to modulate the on‐chip spectrum, which is the first experimentally verified, to the authors' knowledge. By applying a voltage, the refractive index of the liquid crystal surrounding the meta‐waveguides can be tuned, resulting in a blue shift of the spectrum. The simulation shows that the 18.4 dB switching ratio can be achieved at 1550 nm. The meta‐waveguides are prepared using electron beam lithography (EBL), and the improved transmittance of the spectrum in the short wavelength is experimentally verified, which is consistent with the simulation trend. At 1551.64 nm wavelength, the device achieves a switching ratio of ≈16 dB with an active area of 8 µm × 0.4 µm. Based on this device, an optoelectronic computing architecture for the Hadamard matrix product and a novel wavelength selection switch are proposed. This work offers a promising avenue for on‐chip dynamic modulation in integrated photonics, which has the advantage of a compact active area, fast response time, and low energy consumption compared to conventional thermal‐light modulation.

Abstract Iron metabolism dysregulation is tightly associated with cancer development. But the underlying mechanisms remain poorly understood. Increasing evidence has shown that long noncoding RNAs (lncRNAs) participate in various metabolic processes via integrating signaling pathway. In this study, we revealed one iron-triggered lncRNA, one target of YAP, LncRIM (LncRNA Related to Iron Metabolism, also named ZBED5-AS1 and Loc729013), which effectively links the Hippo pathway to iron metabolism and is largely independent on IRP2. Mechanically, LncRIM directly binds NF2 to inhibit NF2-LATS1 interaction, which causes YAP activation and increases intracellular iron level via DMT1 and TFR1. Additionally, LncRIM-NF2 axis mediates cellular iron metabolism dependent on the Hippo pathway. Clinically, high expression of LncRIM correlates with poor patient survival, suggesting its potential use as a biomarker and therapeutic target. Taken together, our study demonstrated a novel mechanism in which LncRIM-NF2 axis facilitates iron-mediated feedback loop to hyperactivate YAP and promote breast cancer development.

Abstract Background Patients with rheumatoid arthritis (RA) undergoing bilateral total hip arthroplasty (THA) and total knee arthroplasty (TKA) are an uncommon population, and their outcomes are also difficult to predict. The purpose of this study was to evaluate whether both bilateral cementless THA and cemented posterior-stabilized TKA (PS-TKA) can provide reliable outcomes for RA patients. Methods We retrospectively reviewed 30 RA patients (60 hips and 60 knees) who underwent both elective bilateral cementless THA and cemented PS-TKA, with a minimum follow-up of 2 years. Clinical, patient-reported, and radiographic data were retrospectively analyzed. Results The mean follow-up was 84 months (range, 24–156). By the last follow-up, the post-operative range of motion, Harris Hip Score, Knee Society Score (KSS) clinical, KSS functional, Western Ontario and McMaster Universities Index of Osteoarthritis (WOMAC) hip, and WOMAC knee scores were significantly improved compared to the preoperative values. All patients achieved the ability to walk. In addition, overall satisfaction scores on a 100-point scale were 92.5 after THA and 89.6 after TKA. Only one patient underwent revision surgery due to knee joint instability, and all replaced hips and knees were radiographically stable by the assessment of the radiolucent line. The proportion of implants that did not suffer loosening or require revision surgery was 99.2% during the 84-month follow-up, based on Kaplan-Meier analysis. Conclusions Our study suggests that bilateral cementless THA and cemented PS-TKA provides reliable mid-long-term clinical, patient-reported, and radiographic outcomes in RA patients, with high survivorship and patient satisfaction.

Accurate and fast detection of abnormal hydroponic lettuce leaves is primary technology for robotic sorting. Yellow and rotten leaves are main types of abnormal leaves in hydroponic lettuce. This study aims to demonstrate a feasibility of detecting yellow and rotten leaves of hydroponic lettuce by machine learning models, i.e. Multiple Linear Regression (MLR), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). One-way analysis of variance was applied to reduce RGB, HSV, and L*a*b* features number of hydroponic lettuce images. Image binarization, image mask, and image filling methods were employed to segment hydroponic lettuce from an image for models testing. Results showed that G, H, and a* were selected from RGB, HSV, and L*a*b* for training models. It took about 20.25 s to detect an image with 3 024 × 4 032 pixels by KNN, which was much longer than MLR (0.61 s) and SVM (1.98 s). MLR got detection accuracies of 89.48% and 99.29% for yellow and rotten leaves, respectively, while SVM reached 98.33% and 97.91%, respectively. SVM was more robust than MLR in detecting yellow and rotten leaves of hydroponic. Thus, it was possible for abnormal hydroponic lettuce leaves detection by machine learning methods.

Deep-learning-based on convolutional neural networks (CNN) has been widely applied in synthetic aperture radar (SAR) target recognition and made significant progress. However, due to the physical effects of the equipment used to collect images, various degrees of speckle noise will be introduced into SAR images. Traditional CNN-based SAR target recognition methods are premised on the same noise intensity in the training and testing set, which is contrary to the target recognition in practice. To alleviate this problem, we propose a novel speckle noise resistant framework for SAR target recognition, called dual-consistency-alignment-based self-supervised learning. First, original SAR images are randomly added to speckle noise with different thresholds through multiplicative noise, after which contrastive pretraining is performed on unlabeled data. During this period, we combine instance pseudolabel consistency alignment and feature consistency alignment to align multiple threshold speckle noise views with original views under the same targets. Finally, the pretrained model is migrated to the downstream SAR speckle noise target recognition task. In this article, speckle noise modeling is conducted based on moving and stationary target capture and recognition data testing set, and experiment results reveal that this method can adapt to different intensities of speckle noise, is robust to modeled SAR image recognition, and maintains a high recognition rate even in small-sample learning.

Abstract Immune checkpoint blockade therapies targeting the PD-L1/PD-1 axis have demonstrated clear clinical benefits. Improved understanding of the underlying regulatory mechanisms might contribute new insights into immunotherapy. Here, we identify transmembrane and ubiquitin-like domain-containing protein 1 (TMUB1) as a modulator of PD-L1 post-translational modifications in tumor cells. Mechanistically, TMUB1 competes with HECT, UBA and WWE domain-containing protein 1 (HUWE1), a E3 ubiquitin ligase, to interact with PD-L1 and inhibit its polyubiquitination at K281 in the endoplasmic reticulum. Moreover, TMUB1 enhances PD-L1 N-glycosylation and stability by recruiting STT3A, thereby promoting PD-L1 maturation and tumor immune evasion. TMUB1 protein levels correlate with PD-L1 expression in human tumor tissue, with high expression being associated with poor patient survival rates. A synthetic peptide engineered to compete with TMUB1 significantly promotes antitumor immunity and suppresses tumor growth in mice. These findings identify TMUB1 as a promising immunotherapeutic target.

Ammonia is toxic to aquatic animals and its chronic effects on the swimming crab Portunus trituberculatus is still not fully understood. Therefore, we conducted this study to detect the responses of energy metabolism of crabs to chronic high environmental ammonia (HEA) exposure by exposing them to HEA (5 and 15 mg·L−1) for 15 d and subsequently recovering in natural seawater for 7 d. Then we analyzed the glucose and lactate content, ATPases activities and the expression of the genes involved in energy homeostasis. Besides, glutamic pyruvic transaminase (GPT), glutamic oxaloacetic transaminase (GOT), alkaline phosphatase (AKP) activity and histological changes were assayed to determine the HEA-induced hepatopancreas damage. Results showed a HEA dose- and exposure time-dependent mortality and hepatopancreas damage. This was accompanied by a loss of energy homeostasis as indicated by the significant increase of AMP/ATP ratio and genes expression involved in AMPK pathway (P

Laser-based additive manufacturing has garnered significant attention in recent years as a promising 3D-printing method for fabricating metallic components. However, the surface roughness of additive manufactured components has been considered a challenge to achieving high performance. At present, the average surface roughness (Sa) of AM parts can reach high levels, greater than 50 μm, and a maximum distance between the high peaks and the low valleys of more than 300 μm, which requires post machining. Therefore, laser polishing is increasingly being utilized as a method of surface treatment for metal alloys, wherein the rapid remelting and resolidification during the process significantly alter both the surface quality and subsurface material properties. In this paper, the surface roughness, microstructures, microhardness, and wear resistance of the as-received, continuous wave laser polishing (CWLP), and pulsed laser polishing (PLP) processed samples were investigated systematically. The results revealed that the surface roughness (Sa) of the as-received sample was 6.29 μm, which was reduced to 0.94 μm and 0.84 μm by CWLP and PLP processing, respectively. It was also found that a hardened layer, about 200 μm, was produced on the Ti6Al4V alloy surface after laser polishing, which can improve the mechanical properties of the component. The microhardness of the laser-polished samples was increased to about 482 HV with an improvement of about 25.2% compared with the as-received Ti6Al4V alloy. Moreover, the coefficient of friction (COF) was slightly reduced by both CWLP and LPL processing, and the wear rate of the surface layer was improved to 0.790 mm3/(N∙m) and 0.714 mm3/(N∙m), respectively, under dry fraction conditions.

Background Preoperative imaging assessment of surgical risk is very important for the prognosis of these children. To develop and validate a radiomics-based machine learning model based on the analysis of radiomics features to predict surgical risk in children with abdominal neuroblastoma (NB).Methods A retrospective study was conducted from April 2019 to March 2021 among 74 children with abdominal NB. A total of 1874 radiomic features in MR images were extracted from each patient. Support vector machines (SVMs) were used to establish the model. Eighty percent of the data were used as the training set to optimize the model, and 20% of the data were used to validate its accuracy, sensitivity, specificity and area under the curve (AUC) to verify its effectiveness.Results Among the 74 children with abdominal NB, 55 (65%) had surgical risk and 19 (35%) had no surgical risk. A t test and Lasso identified that 28 radiomic features were associated with surgical risk. After developing an SVM-based model using these features, predictions were made about whether children with abdominal NB had surgical risk. The model achieved an AUC of 0.94 (a sensitivity of 0.83 and a specificity of 0.80) with 0.890 accuracy in the training set and an AUC of 0.81 (a sensitivity of 0.73 and a specificity of 0.82) with 0.838 accuracy in the test set.Conclusions Radiomics and machine learning can be used to predict the surgical risk in children with abdominal NB. The model based on 28 radiomic features established by SVM showed good diagnostic efficiency.

Magnolol (M), a hydroquinone containing an allyl side chain, is one of the major active components of Houpoea officinalis for antioxidation and anti-aging. To enhance the antioxidant activity of magnolol, the different sites of magnolol were structurally modified in this experiment, and a total of 12 magnolol derivatives were obtained. Based on the preliminary exploration of the anti-aging effect of magnolol derivatives in a Caenorhabditis elegans (C. elegans) model. Our results indicate that the active groups of magnolol exerting anti-aging effects were allyl groups and hydroxyl on the phenyl. Meanwhile, the anti-aging effect of the novel magnolol derivative M27 was found to be significantly superior to that of magnolol. To investigate the effect of M27 on senescence and the potential mechanism of action, we investigated the effect of M27 on senescence in C. elegans. In this study, we investigated the effect of M27 on C. elegans physiology by examining body length, body curvature and pharyngeal pumping frequency. The effect of M27 on stress resistance in C. elegans was explored by acute stress experiments. The mechanism of M27 anti-aging was investigated by measuring ROS content, DAF-16 nuclear translocation, sod-3 expression, and lifespan of transgenic nematodes. Our results indicate that M27 prolonged the lifespan of C. elegans. Meanwhile, M27 improved the healthy lifespan of C. elegans by improving pharyngeal pumping ability and reducing lipofuscin accumulation in C. elegans. M27 increased resistance to high temperature and oxidative stress in C. elegans by reducing ROS. M27 induced DAF-16 translocation from cytoplasm to nucleus in transgenic TJ356 nematodes and upregulated the expression of sod-3 (a gene downstream of DAF-16) in CF1553 nematodes. Furthermore, M27 did not extend the lifespan of daf-16, age-1, daf-2, and hsp-16.2 mutants. This work suggests that M27 may ameliorate aging and extend lifespan in C. elegans through the IIS pathway.

PurposeThis meta-analysis compared the long-term (12 months or 24 months) efficacy and safety of intravitreal aflibercept injection (IAI) for diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR).MethodsWe selected 16 randomized controlled trials (RCTs) performed after 2015 that had a minimum of 12 months and up to 24 months of treatment and conducted a meta-analysis with Review Manager version 5.3. Visual acuity (VA), central subfield thickness (CST) and adverse events were the outcomes selected for evaluation from the eligible studies.ResultsBased on 16 RCTs, we evaluated a total of 7125 patients. For PDR and severe DME with poor baseline vision, after a minimum of 12 months and up to 24 months of treatment, the aflibercept treatment group obtained better VA improvement than the focal/grid laser photocoagulation treatment group (MD=13.30; 95%CI: 13.01~13.58; P

Objective To evaluate the diagnostic values of preoperative plasma fibrinogen and platelet count for screening fixation‐related infection (FRI) in patients undergoing conversion total hip arthroplasty (cTHA) after failed internal fixation of hip fractures. Method This was a single‐center retrospective study. Data were retrospectively analyzed for 435 patients who underwent cTHA in our hospital from January 2008 to September 2020. They were divided into infected (n = 30) and non‐infected groups (n = 405) according to the 2013 International Consensus Meeting (ICM) criteria. The diagnostic sensitivity and specificity of plasma fibrinogen and platelet count were determined using receiver operating characteristic (ROC) curves. Optimal predictive cutoffs of these two markers were determined based on the Youden index. In addition, the diagnostic value of preoperative serum C‐reactive protein (CRP) and erythrocyte sedimentation rate (ESR) for screening FRI were also evaluated based on the cutoffs recommended by the 2013 ICM Criteria. Finally, the diagnostic ability of various combinations of the plasma fibrinogen and platelet count as well as serum CRP and ESR was re‐assessed. Results The numbers of patients with and without FRI were 30 (6.9%) and 405 (93.1%), respectively. Areas under the ROC curves were 0.770 for fibrinogen, 0.606 for platelet, 0.844 for CRP and 0.749 for ESR. The optimal predictive cutoff of fibrinogen was 3.73 g/L, which gave sensitivity of 60.0% and specificity of 90.5%. The optimal predictive cutoff for platelet was 241.5 × 109/L, which gave sensitivity of 46.7% and specificity of 83.7%. The CRP gave sensitivity of 66.7% and specificity of 92.5% with the predetermined cutoff of 10 mg/L, while the ESR gave sensitivity of 67.5% and specificity of 72.4% % with the predetermined cutoff of 30 mm/h. The combination of CRP and ESR showed high specificity of 93.2% but low sensitivity of 66.7%, while the corresponding values for CRP with fibrinogen were satisfied both for sensitivity of 80.0% and specificity of 78.7%. The combination of these four biomarkers gave sensitivity of 73.3% and specificity of 85.7%. Conclusion Preoperative serum CRP, ESR, plasma fibrinogen and platelet count have low sensitivity on their own for screening FRI in patients, but the combination of CRP with fibrinogen shows promise for that.

To address the current problem of the difficulty of extracting the phenotypic parameters of tomato plants in a non-destructive and accurate way, we proposed a method of stem and leaf segmentation and phenotypic extraction of tomato plants based on skeleton extraction and supervoxel clustering. To carry out growth and cultivation experiments on tomato plants in a solar greenhouse, we obtained multi-view image sequences of the tomato plants to construct three-dimensional models of the plant. We used Laplace’s skeleton extraction algorithm to extract the skeleton of the point cloud after removing the noise points using a multi-filtering algorithm, and, based on the plant skeleton, searched for the highest point path, height constraints, and radius constraints to separate the stem from the leaf. At the same time, a supervoxel segmentation method based on Euclidean distance was used to segment each leaf. We extracted a total of six phenotypic parameters of the plant: height, stem diameter, leaf angle, leaf length, leaf width and leaf area, using the segmented organs, which are important for the phenotype. The results showed that the average accuracy, average recall and average F1 scores of the stem and leaf segmentation were 0.88, 0.80 and 0.84, and the segmentation indexes were better than the other four segmentation algorithms; the coefficients of determination between the measurement values of the phenotypic parameters and the real values were 0.97, 0.84, 0.88, 0.94, 0.92 and 0.93; and the root-mean-square errors were 2.17 cm, 0.346 cm, 5.65°, 3.18 cm, 2.99 cm and 8.79 cm2. The measurement values of the proposed method had a strong correlation with the actual values, which could satisfy the requirements of daily production and provide technical support for the extraction of high-throughput phenotypic parameters of tomato plants in solar greenhouses.

Seahorses are valuable species for their use in traditional Chinese medicine, as well as for the aquarium trade as ornamentals and curiosities. To balance market demand and reduce pressure on wild populations, many countries have undertaken commercial seahorse cultivation. Skeletal development plays a crucial role in fish fry culture, affecting external morphology, feeding, and movement. This study investigated the ontogeny allometry, timing, and progression of skeletal development in H. abdominalis from DAB (day after birth) 1 to DAB 100 under mass-scale captive breeding conditions in north China. The results of this study revealed the growth rate was significantly increased between DAB 30 and DAB 54. Allometry analysis revealed that in the early stage, the head, trunk, and tail demonstrated almost isometric growth. However, in the later stage, the head and trunk exhibited negative isometric growth, whereas the tail displayed positive isometric growth. Skeletal staining results showed that newborn seahorses do not have ossified bones until DAB 11 (SL 28.14 ± 2.94 mm). Ossification was primarily observed in the jaw region and the tubular nasal structure of the cranium, which indicated the importance of the early development of feeding organs. The initial formation of ossified vertebral columns was observed at DAB 13 (SL 26.48 ± 0.63 mm), with the complete ossification of all vertebrae occurring by DAB 45 (SL 54.87 ± 4.70 mm). Furthermore, the cranium, rings, and plates were all fully ossified by DAB 30. Ossification of the fins began at DAB 23 (SL 31.27 ± 4.05 mm). However, neither of them were fully ossified by DAB 100. The pelvic fin and the complete structure of the caudal fin were not observed, possibly because of caudal fin ray structure degeneration within the pouch. In addition, no skeletal deformities were observed in all the tested samples. The results of this study provide valuable information on the developmental biology of H. abdominalis, enriching our understanding of their growth and offering insights for optimizing fish fry breeding technologies.

Ovoviviparity and male pregnancy represent distinctive reproductive strategies in seahorses. However, the detailed process of gonadal development in seahorses, particularly in the pot-bellied seahorse (Hippocampus abdominalis), remains largely unknown. In this study, we investigated the complete gonadal development process of the pot-bellied seahorse under captive breeding conditions (18 ± 1 °C). Immediately after birth, primordial germ cells (PGCs) were found within the genital ridge, enclosed by a single layer of somatic cells. Around 7–9 days after birth (DAB), the ovary begins to differentiate. By 30 DAB, two germinal ridges had formed along the edge of the follicular lamina in the ovary. The primary oocytes, resulting from this differentiation process, gradually migrated from the dorsal sides to the mid-ventral area of the ovary, eventually maturing into eggs. In the testis, the primary and secondary spermatocytes appeared at 15 and 30 DAB, respectively, preceding the formation of the testicular lumen (50 DAB). The testis was observed to consist of a single large germinal compartment. Under captive breeding conditions in Northern China, the pot-bellied seahorse demonstrated year-round breeding capability, with each male producing approximately 100–150 larvae. The findings from this study contribute valuable insights into seahorse aquaculture and enhance understanding of the unique reproductive strategy employed by seahorses.

Abstract Background Arbuscular mycorrhizal fungi (AMF) are a group of important symbiotic microorganisms found in ecosystems. Maize is the second most produced food crop globally. To investigate the mechanisms by which mycorrhizal symbiosis improves maize yields, the effects of mycorrhizal symbiosis on root vigor, nutrient accumulation in various tissues, and root exudates were investigated. We propose the following hypothesis: The secretion of organic acids in root exudates has antagonistic or synergistic effects, which are related to the rhizosphere environment. AMF symbiosis will enhance this effect. Result Rhizophagus aggreatus, Claroideoglomus etunicatum, and Funneliformis mosseae were used to inoculate maize plants separately; meanwhile, maize was inoculated with the above three fungi together for another processing. The plant tissues were sampled at five growth stages: V12 (twelve-leaf), VT (Tassel), R1 (Silking), R2 (Blister), and R4 (Dough stage). The root vigor, and nutrient content in different maize organs and organic acids in root exudates were determined in these stages. The results show that mycorrhizal symbiosis significantly improved the root vigor of maize, especially for plants inoculated with F. mosseae. AMF symbiosis significantly increased N, P, and K accumulation. Mixed inoculation with arbuscular mycorrhizal fungi significantly promoted the accumulation of N and K in maize. P accumulation was significantly promoted by C. etunicatum inoculation. Mycorrhizal symbiosis reduced the levels of protocatechuic, vanillic, citric, and ferulic acid in maize root exudates and increased the levels of p-hydroxybenzoic and caffeic acid. Except for syringic, chlorogenic and succinic acid, the levels of other organic acids in root exudates were higher in plants inoculated with F. mosseae than in other treatments. Conclusion This study demonstrates that mycorrhizal symbiosis improves root vigor and promotes nutrient accumulation at various sites; in addition, mycorrhizal symbiosis affects the content of organic acids in root exudates.

Histone acetylation is a pivotal epigenetic modification that controls chromatin structure and regulates gene expression. It plays an essential role in modulating zygotic transcription and cell lineage specification of developing embryos. While the outcomes of many inductive signals have been described to require enzymatic activities of histone acetyltransferases and deacetylases (HDACs), the mechanisms by which HDACs confine the utilization of the zygotic genome remain to be elucidated. Here, we show that histone deacetylase 1 (Hdac1) progressively binds to the zygotic genome from mid-blastula and onward. The recruitment of Hdac1 to the genome at blastula is instructed maternally. Cis-regulatory modules (CRMs) bound by Hdac1 possess epigenetic signatures underlying distinct functions. We highlight a dual function model of Hdac1 where Hdac1 not only represses gene expression by sustaining a histone hypoacetylation state on inactive chromatin, but also maintains gene expression through participating in dynamic histone acetylation–deacetylation cycles on active chromatin. As a result, Hdac1 maintains differential histone acetylation states of bound CRMs between different germ layers and reinforces the transcriptional program underlying cell lineage identities, both in time and space. Taken together, our study reveals a comprehensive role for Hdac1 during early vertebrate embryogenesis.

Summary: Background: Magnetic Resonance Imaging (MRI) is an indispensable tool for the diagnosis of temporal lobe epilepsy (TLE). However, about 30% of TLE patients show no lesion on structural MRI (sMRI-negative), posing a significant challenge for presurgical evaluation. This study aimed to investigate whether chemical exchange saturation transfer (CEST) MRI at 3 Tesla can lateralize the epileptic focus of TLE and study the metabolic contributors to the CEST signal measured. Methods: Forty TLE subjects (16 males and 24 females) were included in this study. An automated data analysis pipeline was established, including segmentation of the hippocampus and amygdala (HA), calculation of four CEST metrics and quantitative relaxation times (T1 and T2), and construction of prediction models by logistic regression. Furthermore, a modified two-stage Bloch–McConnell fitting method was developed to investigate the molecular imaging mechanism of 3 T CEST in identifying epileptic foci of TLE. Findings: The mean CEST ratio (CESTR) metric within 2.25–3.25 ppm in the HA was the most powerful index in predicting seizure laterality, with an area under the receiver-operating characteristic curve (AUC) of 0.84. And, the combination of T2 and CESTR further increased the AUC to 0.92. Amine and guanidinium moieties were the two leading contributors to the CEST contrast between the epileptogenic HA and the normal HA. Interpretation: CEST at 3 Tesla is a powerful modality that can predict seizure laterality with high accuracy. This study can potentially facilitate the clinical translation of CEST MRI in identifying the epileptic foci of TLE or other localization-related epilepsies. Funding: National Natural Science Foundation of China, Science Technology Department of Zhejiang Province, and Zhejiang University.

The fully automatic registration of 3D terrestrial laser scanning (TLS) point clouds, which is the first step in the usage of point clouds, is a highly challenging task in Light Detection and Ranging (LiDAR) remote sensing applications. Here, an automatic algorithm for pairwise coarse registration of TLS point clouds using 3D line features is proposed. First, the 3D line sets were extracted from the original pair of point clouds respectively, and two arbitrary lines from a point cloud were used to construct a 2-line base; Then, a pair of conjugate 2-line bases were identified from the source and target 3D line sets at a time, based on which a 3D rotation matrix together with its corresponding overlap between the pairwise 3D line sets was calculated; Third, a series of 3D rotation matrixes together with their overlaps were obtained using the traversing strategy to identify conjugate 2-line base pairs, and the 3D rotation matrix with the highest overlap was outputted as the final 3D rotation matrix, which was further used to compute the corresponding lines set from the pairwise 3D line sets; Next, based on the set of common perpendicular midpoints between the line correspondences, the 3D translation vector was computed; Finally, the 3D transformation matrix between pairwise point clouds was obtained by combining the 3D rotation matrix and the 3D translation vector. The proposed method was tested on three different TLS datasets, with experimental results demonstrating that the proposed algorithm could perform well on registering pairwise TLS point clouds. The rotation and translation errors of aligning the nine experimental pairwise point clouds were all less than 0.50° and 0.55m, respectively. This registration framework was also shown to be superior to state-of-the-art methods in terms of registration accuracy.

Emerging studies highlight the Hippo pathway as an important player in organ size control, tissue homeostasis, regeneration, development, and diseases, but our understanding of its roles and regulations remains incomplete. Our recent work reported a functional interplay between the Hippo pathway and heavy metals, providing new insights into this key signaling pathway.

Summary: Neurofibromatosis type 2 is an autosomal dominant multiple neoplasia syndrome and is usually caused by mutations in the neurofibromin 2 (NF2) gene, which encodes a tumor suppressor and initiates the Hippo pathway. However, the mechanism by which NF2 functions in the Hippo pathway isn’t fully understood. Here we identified a NF2 c.770-784del mutation from a neurofibromatosis type 2 family. MD simulations showed that this mutation significantly changed the structure of the F3 module of the NF2-FERM domain. Functional assays indicated that the NF2 c.770-784del variant formed LLPS in the cytoplasm with LATS to restrain LATS plasma membrane localization and inactivated the Hippo pathway. Besides, this deletion partly caused a skipping of exon 8 and reduced the protein level of NF2, collectively promoting proliferation and tumorigenesis of meningeal cells. We identified an unrecognized mechanism of LLPS and splicing skipping for the NF2-induced Hippo pathway, which provided new insight into the pathogenesis of neurofibromatosis type 2.

Laser polishing is an emerging efficient technique to remove surface asperity without polluting the environment. However, the insufficient understanding of the mechanism of laser polishing has limited its practical application in industry. In this study, a dual-beam laser polishing experiment was carried out to reduce the roughness of a primary Ti6Al4V sample, and the polishing mechanism was well studied using simulation analysis. The results showed that the surface roughness of the sample was efficiently reduced from an initial 10.96 μm to 1.421 μm using dual-beam laser processing. The simulation analysis regarding the evolution of material surface morphology and the flow behavior of the molten pool during laser the polishing process revealed that the capillary force attributed to surface tension was the main driving force for flattening the large curvature surface of the molten pool at the initial stage, whereas the thermocapillary force influenced from temperature gradient played the key role of eliminating the secondary roughness at the edge of the molten pool during the continuous wave laser polishing process. However, the effect of thermocapillary force can be ignored during the second processing stage in dual-beam laser polishing. The simulation result is well in agreement with the experimental result, indicating the accuracy of the mechanism for the dual-beam laser polishing process. In summary, this work reveals the effect of capillary force and thermocapillary force on molten pool flows during the dual-beam laser polishing processes. Moreover, it is also proved that the dual-beam laser polishing process can further reduce the surface roughness of a sample and obtain a smoother surface.

Summary: Identification of protein interactors is fundamental to understanding their functions. Here, we describe a modified protocol for tandem affinity purification coupled with mass spectrometry (TAP/MS), which includes two-step purification. We detail the S-, 2×FLAG-, and Streptavidin-Binding Peptide (SBP)- tandem tags (SFB-tag) system for protein purification. This protocol can be used to identify protein interactors and establish a high-confidence protein–protein interaction network based on computational models. This is particularly useful for identifying bona fide interacting proteins for subsequent functional studies.For complete details on the use and execution of this protocol, please refer to Bian et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Lakes are important guarantees of regional economic development and ecological security. Previous studies focused on trends of surface area and water level of lakes in Xinjiang, but paid less attention to nonlinear change and driving mechanisms of lake areas at annual and monthly scales. To address this issue, this study used a remote-sensing Big Data cloud platform and mathematical statistical methods to investigate the change in typical lakes and its attribution in Xinjiang during 1986–2020. The results showed that: 1) there was a significant linear trend in Xinjiang lakes: except for Jili Lake, the plains lakes showed an insignificant (p > 0.1) expansion trend, while the mountain lakes showed an significant expansion trend (p < 0.01). 2) There was a significant nonlinear trend in Xinjiang lakes: most of the plains lakes showed periodicity at 14 and 21 years, however most of the mountain lakes showed periodicity at 17 and 21 years. Most of the mutation trends of plains lakes were not significant, yet the mutation trends of mountain lakes showed significant expansion. 3) Human activities were the dominant factor leading to changes in the plains lakes: among the anthropogenic factors, farmland area, GDP, and population had significant effects on lake area (p < 0.1), and lake expansion was closely related to population and farmland area. Among climatic elements, precipitation mainly affected the changes in plains lakes. 4) Climate change was the dominant factor leading to changes in mountain lakes. The effects of temperature change on mountain lakes were all significantly positive (p < 0.05). In the future, it will be necessary to build lake protection schemes that adapt to climate change and human disturbances. This study can provide an important scientific basis for the rational development and utilization of lakes in Xinjiang.

Ecological water conveyance is an important way to promote the restoration of degraded ecosystems in arid watersheds. However, there are few previous research results on how to quantitatively evaluate the effect of ecological water conveyance on ecological restoration. In this regard, this paper selects the Tarim River Basin as a typical area, analyzing the changes of desert riparian vegetation and hydrological elements, constructing a watershed ecological environment quality evaluation system, and comprehensively evaluating the ecological water conveyance effect of the damaged desert forest ecosystem. The conclusion showed that the proportion of the pixel area with an upward trend of Fractional Vegetation Cover (FVC) from 2000 to 2021 is as high as 84.3%. The plant diversity index in the ecological water conveyance area showed the characteristics of first obvious increase and then stable. The main body of groundwater depth showed an upward trend, and the Temperature Vegetation Dryness Index (TVDI) showed a downward trend of pixel area accounting for 57.0%, which indicated that ecological water conveyance had played a positive role in groundwater recharge and ecological restoration along the Tarim River. The ecological environment quality of the river basin showed a trend of transition from low-grade to high-grade, and the area with excellent ecological quality had increased from 4,635.50 km2 in 2000 to 12,335.0 km2 in 2021. The above research provides important scientific reference for the protection and restoration of vegetation degradation in arid watersheds.

BackgroundPseudo-continuous arterial spin labeling (pCASL) is widely used to quantify cerebral blood flow (CBF) abnormalities in patients with Alzheimer’s disease (AD). T1-mapping techniques assess microstructural characteristics in various pathologic changes, but their application in AD remains in the exploratory stage. We hypothesized that combining quantitative CBF and T1 values would generate diagnostic results with higher accuracy than using either method alone in discriminating AD patients from cognitively normal control (NC) subjects.Materials and methodsA total of 45 patients diagnosed with AD and 33 NC subjects were enrolled, and cognitive assessment was performed for each participant according to the Chinese version of the Mini-Mental State Examination (MMSE). T1-weighted magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and pCASL sequence were scanned on a 3T MR scanner. A brain morphometric analysis was integrated into prototype sequence, providing tissue classification and morphometric segmentation results. Quantitative CBF and T1 values of each brain region were automatically generated inline after data acquisition. Independent samples t-test was used to compare regional CBF and T1 values controlled by false discovery rate correction (corrected p < 0.01). The model with combined CBF and T1 values was compared with the individual index by performing receiver operating characteristic curves analysis. The associations between the MMSE score and CBF and T1 values of the brain were investigated using partial correlations.ResultsCerebral blood flow of the right caudate nucleus (RCc) and left hippocampus (LHc) was significantly lower in the AD group compared with the NC group, while the T1 values of the right caudate nucleus (RCt) and left hippocampus (LHt) increased in the AD group. Prediction accuracies of 73.1, 77.2, 75.9, and 81.3% were achieved for each of the above parameters, respectively. In distinguishing patients from controls using the corresponding optimized cut-off values, most combinations of parameters were elevated (area under curve = 0.775–0.894). The highest area under curve value was 0.944, by combining RCc, LHc, RCt, and LHt.ConclusionIn this preliminary study, the combined model based on pCASL and T1-mapping improved the diagnostic performance of discriminating AD and NC groups. T1-mapping may become a competitive technique for quantitatively measuring pathologic changes in the brain.

Objectives: Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder with heterogeneous manifestations and complex etiology. We used quantitative proteomics analysis based on mass spectrometry to identify the differences in proteomics profiles for follicular fluid obtained from patients with or without PCOS and explore possible mechanisms underlying PCOS.Methods: Follicular fluid samples were collected from infertile patients with (n = 9) or without (n = 9) PCOS. Total protein was extracted, quantitatively labeled with a tandem mass tag (TMT), and analyzed using liquid chromatography-mass spectrometry (LC‐MS). TMT-based proteomics and bioinformatics analysis were used to determine the differentially expressed proteins (DEPs) and understand the protein networks. The analysis included protein annotation, unsupervised hierarchical clustering, functional classification, functional enrichment and clustering, and protein-protein interaction analysis. Selected DEPs were confirmed by ELISA, and correlation analysis was performed between these DEPs and the clinical characteristics.Results: In this study, we have identified 1,216 proteins, including 70 DEPs (32 upregulated proteins, 38 downregulated proteins). Bioinformatics analysis revealed that the inflammatory response, complement and coagulation cascades, activation of the immune response, lipid transport, and regulation of protein metabolic processes were co-enriched in patients with PCOS. Based on ELISA results, insulin-like growth factor binding protein 1 (IGFBP1) and apolipoprotein C2 (APOC2) were differentially expressed between patients with and without PCOS. Follicular IGFBP1 showed a positive correlation with the serum levels of high-density lipoprotein cholesterol (HDL-C) (r = 0.3046, p = 0.0419), but negatively correlated with the serum levels of anti-Müllerian hormone (AMH) (r = –0.2924, p = 0.0354) and triglycerides (r = –0.3177, p = 0.0246). Follicular APOC2 was negatively correlated with the serum apolipoprotein A1 (APOA1) levels (r = 0.4509, p = 0.0002).Conclusion: Our study identified DEPs in the follicular fluid of patients with PCOS. Inflammatory response, complement and coagulation cascades, activation of the immune response, lipid transport, and regulation of protein metabolic process were deregulated in PCOS, which may play essential roles in the pathogenesis of PCOS.

In this paper, we consider a variant of dominating set problem, i.e., the total dominating set problem. Given an undirected graph G=(V,E), a subset of vertices T⊆V is called a total dominating set if every vertex in V is adjacent to at least one vertex in T. Based on LP relaxation techniques, this paper gives a distributed approximation algorithm for the total dominating set problem in general graphs. The presented algorithm obtains a fractional total dominating set that is, at most, k(1+Δ1k)Δ1k times the size of the optimal solution to this problem, where k is a positive integer and Δ is the maximum degree of G. The running time of this algorithm is constant communication rounds under the assumption of a synchronous communication model.

Abstract CD9 is a glycoprotein of the transmembrane 4 superfamily that is involved in various cellular processes. Studies related to the immune functions and activities of CD9 in teleost fish are limited. In this study, we characterized two CD9 homologs, PoCD9.1 and PoCD9.3, from Japanese flounder (Paralichthys olivaceus). Sequence analysis showed that PoCD9.1 and PoCD9.3 possess characteristic transmembrane 4 superfamily (TM4SF) structures. PoCD9.1 shares 70.61% sequence identity with PoCD9.3. The expression of PoCD9.1 and PoCD9.3 in the three main immune tissues was significantly induced in a time-dependent manner by extracellular and intracellular pathogen infection, which indicates that the two CD9 homologs play an important role in the response to pathogenic infection. Following infection with the extracellular pathogen Vibrio anguillarum, the expression profiles of both PoCD9.1 and PoCD9.3 were similar. After infection with the intracellular pathogen Edwardsiella piscicida, the expression levels of PoCD9.1 and PoCD9.3 were different at different stages of infection, especially in the spleen. The spleen was the most important tissue for the PoCD9.1 and PoCD9.3 responses to pathogen infection among the three examined immune tissues. Knockdown of PoCD9.1 and PoCD9.3 attenuated the ability of host cells to eliminate pathogenic bacteria, and PoCD9.1 knockdown was more lethal than PoCD9.3 knockdown for host cells with E. piscicida infection. Overexpression of PoCD9.1 and PoCD9.3 promoted host or host cell defence against E. piscicida infection. These findings suggest that PoCD9.1 and PoCD9.3 serve as immune-related factors, play an important role in the immune defence system of Japanese flounder, and display different functions in response to different pathogens at different stages of infection.