Error-compensation network for ringing artifact reduction in holographic displays.

Recent advances in learning-based computer-generated holography (CGH) have unlocked novel possibilities for crafting phase-only holograms. However, existing approaches primarily focus on the learning ability of network modules, often neglecting the impact of diffraction propagation models. The resulting ringing artifacts, emanating from the Gibbs phenomenon in the propagation model, can degrade the quality of reconstructed holographic images. To this end, we explore a diffraction propagation error-compensation network that can be easily integrated into existing CGH methods. This network is designed to correct propagation errors by predicting residual values, thereby aligning the diffraction process closely with an ideal state and easing the learning burden of the network. Simulations and optical experiments demonstrate that our method, when applied to state-of-the-art HoloNet and CCNN, achieves PSNRs of up to 32.47 dB and 29.53 dB, respectively, surpassing baseline methods by 3.89 dB and 0.62 dB. Additionally, real-world experiments have confirmed a significant reduction in ringing artifacts. We envision this approach being applied to a variety of CGH algorithms, paving the way for improved holographic displays.

Prior-free 3D tracking of a fast-moving object at 6667 frames per second with single-pixel detectors.

Real-time tracking and 3D trajectory computation of fast-moving objects is a promising technology, especially in the field of autonomous driving. However, existing image-based tracking methods face significant challenges when it comes to real-time tracking, primarily due to the limitation of storage space and computational resources. Here, we propose a novel approach that enables real-time 3D tracking of a fast-moving object without any prior motion information and at a very low computational cost. To enable 3D coordinate synthesis with a space-efficient optical setup, geometric moment patterns are projected on two non-orthogonal planes with a spatial resolution of 125 µm. Our experiment demonstrates an impressive tracking speed of 6667 frames per second (FPS) with a 20 kHz digital micromirror device (DMD), which is more than 200 times faster than the widely adopted video-based tracking methods. To the best of our knowledge, this is the highest tracking speed record in the field of single-pixel 3D trajectory tracking. This method promotes the development of real-time tracking techniques with single-pixel imaging (SPI).

Image-free single-pixel keypoint detection for privacy preserving human pose estimation.

Computer vision technology has been applied in various fields such as identification, surveillance, and robot vision. However, computer vision algorithms used for human-related tasks operate on human images, which raises data security and privacy concerns. In this Letter, we propose an image-free human keypoint detection technique using a few coded illuminations and a single-pixel detector. Our proposed method can complete the keypoint detection task at an ultralow sampling rate on a measured one-dimensional sequence without image reconstruction, thus protecting privacy from the data collection stage and preventing the acquisition of detailed visual information from the source. The network is designed to optimize both the illumination patterns and the human keypoint predictor with an encoder-decoder framework. For model training and validation, we used 2000 images from Leeds Sport Dataset and COCO Dataset. By incorporating EfficientNet backbone, the inference time is reduced from 4 s to 0.10 s. In the simulation, the proposed network achieves 91.7% average precision. Our experimental results show an average precision of 88.4% at a remarkably low sampling rate of 0.015. In summary, our proposed method has the advantages of privacy protection and resource efficiency, which can be applied to many monitoring and healthcare tasks, such as clinical monitoring, construction site monitoring, and home service robots.

YY1: a key regulator inhibits gastric cancer ferroptosis and mediating apatinib-resistance.

OBJECTIVE: Gastric cancer (GC) stands as a prevalent and deadly global malignancy. Despite its role as a preoperative neoadjuvant therapy, Apatinib's effectiveness is curtailed among GC patients exhibiting elevated YY1 expression. YY1's connection to adverse prognosis, drug resistance, and GC metastasis is established, yet the precise underlying mechanisms remain elusive. This study aims to unravel potential pathogenic pathways attributed to YY1. DESIGN: Utilizing bioinformatics analysis, we conducted differentially expressed genes, functional annotation, and pathway enrichment analyses, and further validation through cellular and animal experiments. RESULTS: Higher YY1 expression correlated with diminished postoperative progression-free survival (PFS) and disease-specific survival (DSS) rates in TCGA analysis, identifying YY1 as an independent DSS indicator in gastric cancer (GC) patients. Notably, YY1 exhibited significantly elevated expression in tumor tissues compared to adjacent normal tissues. Bioinformatics analysis revealed noteworthy differentially expressed genes (DEGs), transcriptional targets, factors, and co-expressed genes associated with YY1. LASSO Cox analysis unveiled Transferrin as a prospective pivotal protein regulated by YY1, with heightened expression linked to adverse DSS and PFS outcomes. YY1's role in governing the p53 signaling pathway and ferroptosis in GC cells was further elucidated. Moreover, YY1 overexpression dampened immune cell infiltration within GC tumors. Additionally, YY1 overexpression hindered GC cell ferroptosis and mediated Apatinib resistance via the p53 pathway. Remarkably, IFN-a demonstrated efficacy in reversing Apatinib resistance and immune suppression in GC tissues. CONCLUSIONS: Our findings underscore the pivotal role of YY1 in driving GC progression and influencing prognosis, thus pinpointing it as a promising therapeutic target to enhance patient outcomes.

A scoring system to predict the technical difficulty of endoscopic resection for cardial submucosal tumors.

BACKGROUND AND AIM: Endoscopic resection has been successfully used for the removal of digestive submucosal tumors (SMTs). However, the cardia has been considered a challenging location for endoscopic resection due to its narrow lumen and sharp angle. The objective of this study was to establish a clinical scoring model to grade the technical difficulty of endoscopic resection for cardial SMTs. METHODS: A total of 246 patients who suffered cardial SMTs and received endoscopic resection were included in this retrospective study. All of them were randomized into the training cohort (n = 123) or internal validation cohort (n = 123). Potential predictors were analyzed using univariate analysis. Then, covariates with P < 0.05 were selected for the multivariate logistic regression model. The ß coefficients from the logistic regression model were used to create a scoring system for technical difficulty prediction by rounding the score to the nearest integer of the absolute ß coefficient value. RESULTS: The clinical score consisted of the following factors: male gender (2 points), extraluminal growth (3 points), and maximum diameter ≥3 cm (3 points). The scoring model demonstrated good discriminatory power, with an area under the receiver operating characteristic curve of 0.860 and a 95% confidence interval of 0.763-0.958. The model also showed a good goodness of fit in the Hosmer-Lemeshow test (P = 0.979). In the training cohort, the probability of encountering technical difficulty in the easy (score = 0), intermediate (score = 1-3), difficult (score = 4-6), and very difficult (score >6) categories was 0, 6.8%, 33.3%, and 100.0%, respectively; similarly, in the validation cohort, it was 0, 5.6%, 22.2%, and 50.0%, respectively. CONCLUSIONS: This scoring system could serve as a valuable tool for clinicians in predicting the technical difficulty of endoscopic resection for cardial SMTs.

Non B Cell-Derived Immunoglobulins in Intestinal Tract.

Intestinal epithelium constitutes a barrier to the unrestricted movement of pathogens, and other detrimental substances from the external world (gut lumen) into the interstitial environment. Intestinal epithelial cells obstruct harmful substances passing through the epithelium as a physical and chemical barrier; Moreover, the epithelial cells can express Toll-like receptors (TLRs) and cytokines to exert innate immune function. In addition, high levels of immunoglobulin A (IgA) and other antibodies exist in the intestinal mucosa, maintaining intestinal immune homeostasis in conjunction with intestinal probiotics. Traditionally, these antibodies have been deemed to be secreted by submucosal plasma cells. Nonetheless, in recent years, it has been demonstrated that intestinal epithelial cells produce a substantial amount of Igs, especially IgA or free Ig light chains, which are involved in intestinal immune homeostasis and the survival of normal epithelial cells. Furthermore, mounting evidence affirms that many human carcinoma cells, including colorectal cancer (CRC), can overexpress Igs, particularly IgG. Cancer-derived Igs exhibit a unique V(D)J rearrangement pattern distinct from B cell-derived Ig; moreover, this cancer cell-derived IgG also has a unique sialic acid modification on the 162 site of CH1 domain (SIA-IgG). The SIA-IgG plays a crucial role in promoting cancer initiation, progression, metastasis, and tumour immune escape. Simultaneously, CRC cells can also express free Ig light chains, which promote colitis, colitis-associated colon carcinogenesis, and CRC progression. Therefore, Igs expressed by CRC cells could be a potential target for diagnosing and preventing the transformation of inflammation into cancer, as well as treating CRC.

End-to-end compression-aware computer-generated holography.

Joint photographic experts group (JPEG) compression standard is widely adopted for digital images. However, as JPEG encoding is not designed for holograms, applying it typically leads to severe distortions in holographic projections. In this work, we overcome this problem by taking into account the influence of JPEG compression on hologram generation in an end-to-end fashion. To this end, we introduce a novel approach to merge the process of hologram generation and JPEG compression with one differentiable model, enabling joint optimization via efficient first-order solvers. Our JPEG-aware end-to-end optimized holograms show significant improvements compared to conventional holograms compressed using JPEG standard both in simulation and on experimental display prototype. Specifically, the proposed algorithm shows improvements of 4 dB in peak signal-to-noise ratio (PSNR) and 0.27 in structural similarity (SSIM) metrics, under the same compression rate. When maintained with the same reconstruction quality, our method reduces the size of compressed holograms by about 35% compared to conventional JPEG-compressed holograms. Consistent with simulations, the experimental results further demonstrate that our method is robust to JPEG compression loss. Moreover, our method generates holograms compatible with the JPEG standard, making it friendly to a wide range of commercial software and edge devices.

Muscular injury as an independent risk factor for esophageal stenosis after endoscopic submucosal dissection of esophageal squamous cell cancer.

BACKGROUND AND AIMS: Stenosis after esophageal endoscopic submucosal dissection (ESD) has a high incidence, and muscular injury is an important risk factor for esophageal stenosis. Hence, this study aimed to classify muscular injury degrees and investigate their association with postoperative stenosis. METHODS: This retrospective study included 1033 patients with esophageal mucosal lesions treated with ESD between August 2015 and March 2021. Demographic and clinical parameters were analyzed, and stenosis risk factors were identified using multivariate logistic regression. A novel muscular injury classification system was proposed and used to investigate the association between different muscular injury degrees and postoperative stenosis. Finally, a scoring system was established to predict muscular injury. RESULTS: Of 1033 patients, 118 (11.4%) had esophageal stenosis. The multivariate analysis demonstrated that the history of endoscopic esophageal treatment, circumferential range, and muscular injury were significant risk factors for esophageal stenosis. Patients with type II muscular injuries tended to develop complex stenosis (n = 13 [36.1%], P < .05), and type II muscular injuries were more likely to predispose patients to severe stenosis than type I (73.3% and 92.3%, respectively). The scoring system showed that patients with high scores (3-6) were more likely to have muscular injury. The score model presented good discriminatory power in the internal validation (area under the receiver-operating characteristic curve, .706; 95% confidence interval, .645-.767) and goodness-of-fit in the Hosmer-Lemeshow test (P = .865). CONCLUSIONS: Muscular injury was an independent risk factor for esophageal stenosis. The scoring system demonstrated good performance in predicting muscular injury during ESD.

Risk factors for complications and incomplete resection after endoscopic resection for duodenal submucosal tumors.

BACKGROUND AND AIM: Endoscopic resection (ER) has been used to remove submucosal tumors (SMTs) in recent years; however, duodenal ER is associated with high rates of immediate or delayed bleeding and perforation. Whether ER can be recommended for the treatment of duodenal SMTs remains controversial. Therefore, we aimed to investigate the clinical outcomes associated with the ER of duodenal SMTs and to assess possible predictive factors for complications and incomplete resection. METHODS: This retrospective study included 141 patients with duodenal SMTs. The therapeutic outcomes from ER and procedure-related complications were analyzed. RESULTS: Of the 141 patients, 78.7% achieved complete resection and nine (6.4%) developed complications. The multivariate analysis suggested that location near the duodenal papilla (P = 0.010) and diameter exceeding 15 mm (P = 0.091) of duodenal SMTs were independent risk factors for complications in ER. Besides, submucosal fibrosis (P = 0.042), location near the duodenal papilla (P = 0.049), and irregular morphology (P = 0.067) were independent risk factors for incomplete resection. CONCLUSIONS: ER can be recommended as an effective and minimally invasive treatment for duodenal SMTs.

A prediction model and nomogram for technical difficulty of peroral endoscopic myotomy.

BACKGROUND AND AIMS: Peroral endoscopic myotomy (POEM) is a promising endoscopic technique for achalasia. We aimed to establish a regression model and develop a simple nomogram to predict the technical difficulty of POEM in a single center with large volume cases. METHODS: 3385 achalasia patients treated with POEM were included, and the technical difficulty was systemically evaluated. All of them were randomized into the training cohort (n = 1693) or internal validation cohort (n = 1692). Then, the prediction model and nomogram were proposed based on multivariate logistic regression analysis in the training cohort and assessed in the validation cohort. RESULTS: Of 3385 patients, technical difficulty happened in 417 (12.32%) cases. In the training stage, six factors were weighted based on the ß coefficient from the regression model, including age, disease duration, sigmoid esophagus, mucosal edema, submucosal fibrosis, and tunnel length. The patients were categorized into low-risk (< 0.1), medium-risk (0.1-0.25), and high-risk (> = 0.25) groups. Our score model performed satisfying discrimination with the areas under the receiver-operating characteristic curve (AUC) of 0.743 (95% confidence interval (CI), 0.701-0.785) and calibration with goodness of fit in the Hosmer-Lemeshow test (P = 0.088) in internal validation. CONCLUSIONS: The prediction model and nomogram demonstrated good performance in predicting the technical difficulty of POEM.