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Abstract Swin Transformer is an important work among all the attempts to reduce the computational complexity of Transformers while maintaining its excellent performance in computer vision. Window-based patch self-attention can use the local connectivity of the image features, and the shifted window-based patch self-attention enables the communication of information between different patches in the entire image scope. Through in-depth research on the effects of different sizes of shifted windows on the patch information communication efficiency, this article proposes a Dual-Scale Transformer with double-sized shifted window attention method. The proposed method surpasses CNN-based methods such as U-Net, AttenU-Net, ResU-Net, CE-Net by a considerable margin (Approximately 3% $$\sim$$ ∼ 6% increase), and outperforms the Transformer based models single-scale Swin Transformer(SwinT)(Approximately 1% increase), on the datasets of the Kvasir-SEG, ISIC2017, MICCAI EndoVisSub-Instrument and CadVesSet. The experimental results verify that the proposed dual scale shifted window attention benefits the communication of patch information and can enhance the segmentation results to state of the art. We also implement an ablation study on the effect of the shifted window size on the information flow efficiency and verify that the dual-scale shifted window attention is the optimized network design. Our study highlights the significant impact of network structure design on visual performance, providing valuable insights for the design of networks based on Transformer architectures.

Abstract Osteophytes are frequently observed in elderly people and most commonly appear at the anterior edge of the cervical and lumbar vertebrae body. The anterior osteophytes keep developing and will lead to neck/back pain over time. In clinical practice, the accurate measurement of the anterior osteophyte length and the understanding of the temporal progression of anterior osteophyte growth are of vital importance to clinicians for effective treatment planning. This study proposes a new measuring method using the osteophyte ratio index to quantify anterior osteophyte length based on lateral radiographs. Moreover, we develop a continuous stochastic degradation model with time-related functions to characterize the anterior osteophyte formation and growth process on cervical and lumbar vertebrae over time. Follow-up data of anterior osteophytes up to 9 years are obtained for measurement and model validation. The agreement test indicates excellent reproducibility for our measuring method. The proposed model accurately fits the osteophyte growth paths. The model predicts the mean time to onset of pain and obtained survival function of the degenerative vertebrae. This research opens the door to future quantification and mathematical modeling of the anterior osteophyte growth on human cervical and lumbar vertebrae. The measured follow-up data is shared for future studies.

Abstract Due to the antiquity and difficulty of excavation, the Terracotta Warriors have suffered varying degrees of damage. To restore the cultural relics to their original appearance, utilizing point clouds to repair damaged Terracotta Warriors has always been a hot topic in cultural relic protection. The output results of existing methods in point cloud completion often lack diversity. Probability-based models represented by Denoising Diffusion Probabilistic Models have recently achieved great success in the field of images and point clouds and can output a variety of results. However, one drawback of diffusion models is that too many samples result in slow generation speed. Toward this issue, we propose a new neural network for Terracotta Warriors fragments completion. During the reverse diffusion stage, we initially decrease the number of sampling steps to generate a coarse result. This preliminary outcome undergoes further refinement through a multi-scale refine network. Additionally, we introduce a novel approach called Partition Attention Sampling to enhance the representation capabilities of features. The effectiveness of the proposed model is validated in the experiments on the real Terracotta Warriors dataset and public dataset. The experimental results conclusively demonstrate that our model exhibits competitive performance in comparison to other existing models.

Abstract Utrophin (UTRN), known as a tumor suppressor, potentially regulates tumor development and the immune microenvironment. However, its impact on breast cancer’s development and treatment remains unstudied. We conducted a thorough examination of UTRN using both bioinformatic and in vitro experiments in this study. We discovered UTRN expression decreased in breast cancer compared to standard samples. High UTRN expression correlated with better prognosis. Drug sensitivity tests and RT-qPCR assays revealed UTRN’s pivotal role in tamoxifen resistance. Furthermore, the Kruskal–Wallis rank test indicated UTRN’s potential as a valuable diagnostic biomarker for breast cancer and its utility in detecting T stage of breast cancer. Additionally, our results demonstrated UTRN’s close association with immune cells, inhibitors, stimulators, receptors, and chemokines in breast cancer (BRCA). This research provides a novel perspective on UTRN’s role in breast cancer’s prognostic and therapeutic value. Low UTRN expression may contribute to tamoxifen resistance and a poor prognosis. Specifically, UTRN can improve clinical decision-making and raise the diagnosis accuracy of breast cancer.

Abstract The relationship between Needle Track Bleeding (NTB) and the occurrence of postoperative immediate pneumothorax remains unclear. In our cross-sectional study, we conducted a retrospective collected of data from 674 consecutive patients who underwent CT-guided percutaneous transthoracic lung biopsies between 2019 and 2022. A logistic regression model was employed to explore the association between NTB and postoperative immediate pneumothorax, and restricted cubic spline curves was used to investigate the link and its explicit curve shape. A sensitivity analysis was performed by transforming the continuous NTB into categorical variable and calculated an E-value. A total of 453 participants (47.90% male) were included in our analysis. The postoperative immediate pneumothorax rate was 41.05% (186/453). We found a negative correlation between NTB and postoperative immediate pneumothorax (OR = 0.91, 95%CI 0.88–0.95) after adjusting for confounding factors. This relationship was nonlinear, with a key inflection point at NTB of 8 mm. No significant link was noted for NTB > 8 mm (OR = 0.98, 95%CI 0.95–1.02), while a protective association was observed for NTB ≤ 8 mm (OR = 0.74, 95%CI 0.66–0.81). NTB showed a nonlinear, protective correlation with postoperative immediate pneumothorax. However, when NTB exceeded 8 mm, the protective association was not observed.

Abstract Injection-production operation parameters, the minimum injection gas pressure (IGP: operation pressure), IGP interval, minimum IGP residence time, and injection-production cycle of the underground salt rock gas storage under long-term operation, affect not only the capacity and working ability of a salt cavern but also be crucial to the safety and stability of the surrounding rock. A 3D geo-mechanical model of the salt cavern is established to study the stability of the storage in the operation period. The deformation, expansion safety factor, volume shrinkage, and plastic zone are comprehensively considered for predicting the feasibility and stability of the salt cavern. The stability of the surrounding rock of the cavern with different injection-production parameters and the impact of each parameter on the stability of the cavern during operating are systematically investigated. The results indicate that the displacement, the expansion coefficient of the surrounding rock, and the volume shrinkage rate of the salt cavern reduces significantly with the increment of IGP interval and minimum IGP, while they increases with raising the minimum IGP residence time and injection-production cycle. With the continuous operation of the cavity, the displacement and the volume shrinkage rate enhances significantly year by year with the augment of operation parameters, moreover, their value show a fluctuating upward trend with the alternation of the gas injection and the production. The volume of the plastic zone is enlarged with the increment of the IGP interval, minimum IGP, and injection-production cycle, while it reduces with the extension of the minimum IGP residence time. The variation becomes remarkably with the augment of parameters. The sensitivity coefficients of each injection-production operation parameter are ranked, from large to small, as follows: IGP interval, minimum IGP, minimum IGP residence time, injection-production cycle. The results can offer beneficial reference for effectively optimize the injection-production parameters, so as to provide technical guidance for ensuring the stability of the storage and meeting requirements for the storage capacity.

Abstract The aim of this study is to evaluate the factors affecting the objective response rate (ORR) after neoadjuvant therapy of taxol plus platinum (TP) regimen combined with programmed cell death protein-1 (PD-1) inhibitors for esophageal cancer, and establish a predictive model for forecasting ORR. According to the inclusion and exclusion criteria, consecutive esophageal cancer patients who were treated in the First Affiliated Hospital of Xi’an Jiaotong University from January 2020 to February 2022 were enrolled in this study as a training cohort, while patients who were treated in the Shaanxi Provincial Cancer Hospital Affiliated to Medical College of Xi’an Jiaotong University from January 2020 to December 2021 were enrolled as a validation cohort. All patients were treated with resectable locally advanced esophageal cancer and received neoadjuvant chemotherapy combined with immunotherapy. The ORR was defined as the sum of complete pathological response, major pathological response and partial pathological response. Logistic regression analysis was performed to determine the factors that might be related to the ORR of the patients after neoadjuvant therapy. The nomogram based on the result of regression analysis was established and verified to predict the ORR. In this study, 42 patients were included as training cohort and 53 patients were included as validation cohort. Chi-square analysis showed that neutrophil, platelet, platelet-to-lymphocytes ratio (PLR), systemic immune-inflammation index (SII), D-dimer and carcinoembryonic antigen (CEA) between ORR group and non-ORR group were significantly different. Logistic regression analysis showed that aspartate aminotransferase (AST), D-dimer and CEA were independent predictors of ORR after neoadjuvant immunotherapy. Finally, a nomogram was established based on AST, D-dimer and CEA. Internal validation and external validation revealed that the nomogram had a good ability to predict ORR after neoadjuvant immunotherapy. In conclusion, AST, D-dimer and CEA were the independent predictors of ORR after neoadjuvant immunotherapy. The nomogram based on these three indicators showed a good predictive ability.

Abstract To obtain a higher simplification rate while retaining geometric features, a simplification framework for the point cloud is proposed. Firstly, multi-angle images of the original point cloud are obtained with a virtual camera. Then, feature lines of each image are extracted by deep neural network. Furthermore, according to the proposed mapping relationship between the acquired 2D feature lines and original point cloud, feature points of the point cloud are extracted automatically. Finally, the simplified point cloud is obtained by fusing feature points and simplified non-feature points. The proposed simplification method is applied to four data sets and compared with the other six algorithms. The experimental results demonstrate that our proposed simplification method has the superiority in terms of both retaining geometric features and high simplification rate.

Abstract We constructed a mining soil restoration system combining plant, complex substrate and microbe. Sludge was added to reconstructed mine substrates (RMS) to accelerate the reclamation process. The effect of sludge on plant growth, microbial activity, soil aggregate stability, and aggregation-associated soil characteristics was monitored during 10 years of reclamation. Results show that the height and total biomass of ryegrass increases with reclamation time. Sludge amendment increases the aggregate binding agent content and soil aggregate stability. Soil organic carbon (SOC) and light-fraction SOC (LFOC) in the RMS increase by 151% and 247% compared with those of the control, respectively. A similar trend was observed for the glomalin-related soil protein (GRSP). Stable soil aggregate indexes increase until the seventh year. In short, the variables of RMS determined after 3–7 years insignificantly differ from those of the untreated sample in the tenth-year. Furthermore, significant positive correlations between the GRSP and SOC and GRSP and soil structure-related variables were observed in RMS. Biological stimulation of the SOC and GRSP accelerates the recovery of the soil structure and ecosystem function. Consequently, the plant–complex substrate–microbe ecological restoration system can be used as an effective tool in early mining soil reclamation.

Abstract Nitrogen is one of the most important nutrients needed for plants and algae to survive, and the photosynthetic ability of algae is related to nitrogen abundance. Red algae are unique photosynthetic eukaryotic organisms in the evolution of algae, as they contain phycobilisomes (PBSs) on their thylakoid membranes. In this report, the in vivo chlorophyll (Chl) a fluorescence kinetics of nitrogen-starved Porphyridium cruentum were analyzed to determine the effects of nitrogen deficiency on photosynthetic performance using a multi-color pulse amplitude modulation (PAM) chlorophyll fluorometer. Due to nitrogen starvation, the photochemical efficiency of PSII and the activity of PSII reaction centers (RCs) decreased, and photoinhibition of PSII occurred. The water-splitting system on the donor side of PSII was seriously impacted by nitrogen deficiency, leading to the inactivation of the oxygen-evolving complex (OEC) and decreased light energy conversion efficiency. In nitrogen-starved cells, a higher proportion of energy was used for photochemical reactions, and thermal dissipation was reduced, as shown by qP and qN. The ability of nitrogen-starved cells to tolerate and resist high photon flux densities was weakened. Our results showed that the photosynthetic performance of P. cruentum was severely impacted by nitrogen deficiency.

Abstract Almost half of dental restorations have failed in less than 10 years, and approximately 60% of practice time has been consumed to replace these dental restorations. As such, contemporary dentin adhesives should be modified to treat secondary caries and prevent the degradation of adhesive–dentin interfaces. To achieve this goal, we developed a versatile therapeutic adhesive in the present study by incorporating quercetin, which is a naturally derived plant extract, into a commercial adhesive at three concentrations (100, 500 and 1000 µg/mL). An unmodified adhesive served as a control. The antibacterial ability on Streptococcus mutans biofilm, conversion degree, microtensile bond strength, failure modes, in situ zymography, nanoleakage expression and cytotoxicity of quercetin-doped adhesive were comprehensively evaluated. Results showed that the quercetin-doped adhesive (500 µg/mL) preserved its bonding properties against collagenase ageing and inhibited the growth of S. mutans biofilm. Efficient bonding interface sealing ability, matrix metalloproteinase inhibition and acceptable biocompatibility were also achieved. Thus, a simple, safe and workable strategy was successfully developed to produce therapeutic adhesives for the extension of the service life of adhesive restorations.

Abstract This study aimed to investigate application of Onodera prognostic nutrition index (OPNI) and neutrophil-to-lymphocyte ratio (NLR) in evaluating risk of postoperative complications in Crohn’s disease (CD). Clinical data of 108 postoperative CD patients in 9 years were respectively reviewed. OPNI and NLR were within 1 week preoperatively. Average OPNI was 38.8 ± 8.2 and significantly lower in patients with: CD type B3; lymphopenia; decreased haemoglobin, prealbumin, and albumin; and daily enteral nutrition

Abstract Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P

Abstract Parkinson’s disease is the world’s fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson’s disease and automate diagnostics would greatly improve the treatment of patients with Parkinson’s disease. Current diagnostic methods are expensive and have limited availability. Considering the insidious and preclinical onset and progression of the disease, a desirable screening should be diagnostically accurate even before the onset of symptoms to allow medical interventions. We highlight retinal fundus imaging, often termed a window to the brain, as a diagnostic screening modality for Parkinson’s disease. We conducted a systematic evaluation of conventional machine learning and deep learning techniques to classify Parkinson’s disease from UK Biobank fundus imaging. Our results suggest Parkinson’s disease individuals can be differentiated from age and gender-matched healthy subjects with 68% accuracy. This accuracy is maintained when predicting either prevalent or incident Parkinson’s disease. Explainability and trustworthiness are enhanced by visual attribution maps of localized biomarkers and quantified metrics of model robustness to data perturbations.

Abstract Colorectal cancer is the third most common cancer worldwide and there has been a concerning increase in the incidence rate of colorectal cancer among individuals under the age of 50. This study compared the survival outcome between early-onset and late-onset metastatic colorectal cancer to find the differences and identify their prognostic factors. We obtained patient data from SEER database. Survival outcome was estimated using Kaplan–Meier survival curves and compared using the log-rank test. Univariate and multivariate analyses were conducted utilizing COX models to identify their independent prognostic factors. A total of 10,036 early-onset metastatic colorectal (EOCRC) cancer patients and 56,225 late-onset metastatic colorectal cancer (LOCRC) patients between 2010 and 2019 were included in this study. EOCRC has more survival benefits than LOCRC. Tumor primary location (p

Abstract During the production of metal material, various complex defects may come into being on the surface, together with large amount of background texture information, causing false or missing detection in the process of small defect detection. To resolve those problems, this paper introduces a new model which combines the advantages of CSPlayer module and Global Attention Enhancement Mechanism based on the YOLOv5s model. First of all, we replace C3 module with CSPlayer module to augment the neural network model, so as to improve its flexibility and adaptability. Then, we introduce the Global Attention Mechanism (GAM) and build the generalized additive model. In the meanwhile, the attention weights of all dimensions are weighted and averaged as output to promote the detection speed and accuracy. The results of the experiment in which the GC10-DET augmented dataset is involved, show that the improved algorithm model performs better than YOLOv5s in precision, mAP@0.5 and mAP@0.5: 0.95 by 5.3%, 1.4% and 1.7% respectively, and it also has a higher reasoning speed.

Abstract Magnetic anastomosis substantially shortens the duration of vascular anastomosis. We aimed to apply magnetic anastomosis technology (MAT) to donor liver implantations in pig orthotopic liver transplantation (OLT). Twenty healthy adult pigs were randomly divided into donors and recipients, and major vascular anastomosis was performed using MAT during OLT. Recipient liver and kidney function was measured pre-surgery and 12, 24 and 72 h post-surgery. Vascular anastomoses examinations were performed using ultrasound or angiography weekly post-surgery, and pathological examinations of vascular anastomoses were performed during autopsy after animal euthanasia. All recipients survived 24 h after surgery, which is considered as successful transplantation. Anhepatic duration was only 13 min, and no anastomotic obstruction or stenosis, magnetic displacement and anastomotic angulation, or distortion was found upon postoperative examinations of major liver vasculature. Aspartate aminotransferase, alanine aminotransferase, and total bilirubin serum levels increased considerably postoperatively. The follow-up period for this study was 1 year, and the median survival time of all recipients was 115 d (interquartile range = 11–180 d). The main causes of death were liver failure, immune rejection, infection, and arterial anastomotic bleeding. Moreover, vascular anastomoses healed well with a survival time of more than two weeks. We developed a novel magnetic device to create a fast and safe technique to perform major vascular anastomoses in pig liver transplantations. Additionally, the liver graft implantation using MAT considerably shortened the recipient warm ischemia time, which will reduce the extent of ischemia–reperfusion injury. We conclude that MAT is an effective method for donor liver fast implantation in OLT in pigs.

Abstract Liver resection (LR) is the only recommended effective curative treatment for patients with intrahepatic cholangiocarcinoma (ICC), but the prognosis of patients with ICC is still poor even after curative resection. Recently, many researchers focused on the therapeutic value of LT for patients with ICC. This study aimed to identify the role of liver transplantation in patients with ICC by internally comparing with LR in ICC and externally comparing with LT in HCC. We obtained patient data from SEER database. Propensity score methods were applied to control confounders. Survival outcome was estimated using Kaplan–Meier survival curves and compared using the log-rank test. A total of 2538 patients with ICC after surgery and 5048 patients with HCC after LT between 2000 and 2019 were included in this study. The prognosis of patients with ICC after LT were better than patients with ICC after LR in both unmatched (HR 0.65, P = 0.002) and matched cohorts (HR 0.62, P = 0.009). The 5-year OS rate after LT could be improved to 61.7% in patients with local advanced ICC after neoadjuvant chemotherapy. In conclusion, our study demonstrated that the prognosis of patients with ICC after LT was better than patients with ICC after LR, but was still worse than patients with HCC after LT. LT with neoadjuvant chemotherapy should be considered as a treatment option for patients with locally advanced ICC, but more prospective multicenter clinical trials are needed to further confirm these results.

Abstract To solve the problem of missed and false detection caused by the large number of tiny targets and complex background textures in a printed circuit board (PCB), we propose a global contextual attention augmented YOLO model with ConvMixer prediction heads (GCC-YOLO). In this study, we apply a high-resolution feature layer (P2) to gain more details and positional information of small targets. Moreover, in order to suppress the background noisy information and further enhance the feature extraction capability, a global contextual attention module (GC) is introduced in the backbone network and combined with a C3 module. Furthermore, in order to reduce the loss of shallow feature information due to the deepening of network layers, a bi-directional weighted feature pyramid (BiFPN) feature fusion structure is introduced. Finally, a ConvMixer module is introduced and combined with the C3 module to create a new prediction head, which improves the small target detection capability of the model while reducing the parameters. Test results on the PCB dataset show that GCC-YOLO improved the Precision, Recall, mAP@0.5, and mAP@0.5:0.95 by 0.2%, 1.8%, 0.5%, and 8.3%, respectively, compared to YOLOv5s; moreover, it has a smaller model volume and faster reasoning speed compared to other algorithms.

Abstract FAT atypical cadherin 1 (FAT1) is one of the most mutagenic genes in tumors, and several critical studies have revealed its role in tumors, although no pan-cancer studies are currently available. Therefore, we explored the potential oncogenic role of FAT1 in 33 tumors based on The Cancer Genome Atlas and Gene Expression Omibus datasets. We found that FAT1 was strongly expressed in most tumors and significantly correlated with their prognosis. Additionally, we analyzed the association of FAT1 with tumors from multiple perspectives, including single-cell sequencing, mutations, high tumor mutational burden, microsatellite instability, immune cell infiltration, and immune microenvironment. Our first pan-cancer study provided a relatively comprehensive understanding of the oncogenic role of FAT1 in tumors.

The aim of this study was to localize the anatomic distribution of upper motor neuron (UMN) loss through examining cortical thickness at the clinical onset of amyotrophic lateral sclerosis (ALS) and explore motor manifestation in functionally impaired body region attribute to impairment of lower motor neuron (LMN) or UMN or mixed LMN and UMN? The clinical features, cortical thickness of corresponding areas from different body regions in MRI and electromyography (EMG) data were collected from 108 classical ALS patients. The cortical thickness was thinner in ALS group than control group in bilateral head-face and upper-limb areas (p < 0.05). In head-face area, the cortical thickness of bulbar-onset group was significantly lower than that of control groups (p < 0.05). In upper-limb areas, the cortical thickness of cervical-onset group was significantly thinner than that of control group. Notably, the bulbar ALSFRS-R subscore was correlated with cortical thickness in bilateral head-face areas (p < 0.05). The bulbar ALSFRS-R subscore of the positive LMN damage group was lower compared to that of the negative LMN damage group (P < 0.001). The limb ALSFRS-R subscore correlated with compound muscle action potential (CMAP) amplitudes of median, ulnar, peroneal, and tibial nerves (P < 0.001), but was not related to cortical thickness. In conclusion, the UMN degeneration in ALS was derived from focal initiation, bulbar- and cervical-onset may date from head-face and upper-limb areas in motor homunculus cortex, respectively. The bulbar dysfunction was resulted from the mixed UMN and LMN impairment, while limb dysfunction derived mostly from LMN loss. [ABSTRACT FROM AUTHOR]