Compression of phase-only holograms with JPEG standard and deep learning

It is a critical issue to reduce the enormous amount of data in the processing, storage and transmission of a hologram in digital format. In photograph compression, the JPEG standard is commonly supported by almost every system and device. It will be favorable if JPEG standard is applicable to hologram compression, with advantages of universal compatibility. However, the reconstructed image from a JPEG compressed hologram suffers from severe quality degradation since some high frequency features in the hologram will be lost during the compression process. In this work, we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram. Simulation and experimental results reveal that our proposed "JPEG + deep learning" hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram after compression

Effect of multiple clinical factors on recurrent angina after percutaneous coronary intervention: A retrospective study from 398 ST-segment elevation myocardial infarction patients

Recurrent angina (RA) has an important influence on health status of patients after percutaneous coronary intervention (PCI). This study aimed to retrospectively investigate the effect of multiple clinical factors on both short-term and long-term development of RA.A total of 398 ST-segment elevation myocardial infarction (STEMI) patients were studied for up to 12 months. The primary clinical outcome, RA, was assessed at 1-month and 12-month. In multivariate analyses, the effect of clinical factors, including baseline demographics, medical history, infarction-related arteries, procedural characteristics of PCI, and the use of medicines, was investigated in patients with and without RA.The Logistic regression analysis showed that the patients with treatment through radial approach PCI (odds ratio [OR]: 0.42, 95% confidence interval [CI]: 0.18-0.96, P < 0.05) were less likely to have RA during 1-month assessment. During 12 months after PCI, male patients (OR: 0.53, 95% CI: 0.29-0.96, P < 0.05), and/or those treated with radial approach PCI (OR: 0.45, 95% CI: 0.21-0.97, P < 0.05) were less likely to have RA, whereas the patients with infarction related artery (IRA) in left anterior descending (LAD) (OR: 2.41, 95% CI: 1.20-4.84, P < 0.01) were more likely to have RA at follow-up. The Cox regression analysis further revealed that the patients with infarction of the LAD artery (hazard ratio [HR]: 2.08, 95% CI: 1.10-3.92, P < 0.05), but not with treatment through radial artery during PCI (HR: 0.42, 95% CI: 0.18-0.96, P < 0.05) had higher potential of development of RA during 12 months after PCI.We studied the effects of multiple clinical factors on the development of RA after PCI. Our findings suggest that patients with infarction of the LAD artery, and/or treatment not through radial artery during PCI were associated with higher risk of RA and may require close follow-up

A facile approach to build Bi2O2CO3/PCN nanohybrid photocatalysts for gaseous acetaldehyde efficient removal

Constructing heterojunction between two semiconductors is a cost-effective pathway to fabricate efficient photocatalysts for environmental remediation and energy-related applications, which is with profound significance and high desirability to contemporary era. In this work, we demonstrate an extremely facile approach to couple bismuth subcarbonate with polymeric carbon nitride (denoted as BIOC@PCN) by ion exchange between home-made rose-like Bi2O2(OH)(NO3) (denoted as BION) and PCN bulks at 433 K solvothermal condition. PCN bulks play multi-roles in this ingenious one-pot method. Firstly, PCN bulks guarantee the negatively charged surface to anchor plentiful bismuth precursor salts. More importantly, solvothermal treatment affords a weak basic and sufficient CO32− ions environment to promote the following ion exchange reaction. The evolution of morphology, components and structure from rose-like BION to BIOC@PCN were symmetrically characterized by means of SEM, HR-TEM, XRD, FTIR, TG, UV–vis, BET-BJH and XPS. The as-prepared nanohybrid photocatalyst (0.5BIOC@PCN) presents optimal photocatalytic performance for gaseous acetaldehyde removal, which is showing 10, 6.5 and 2 times higher than that of the PCN-Bulk, BION and mechanical mixed BIOC/PCN counterparts, respectively. Transient photocurrent response and EPR results further verify the validity of the established heterojunction of BIOC@PCN in facilitating the separation of charge carriers. The performance improvement gains from the efficient separation of charge carriers in BIOC@PCN heterojunction, manifested by PL spectra, transient photocurrent response and EPR results. In this study, a facile and cost-effective approach to build PCN-based nanohybrid photocatalysts for gaseous acetaldehyde efficient removal was established

Case Report: Sequential Chemotherapy and Immunotherapy Produce Sustained Response in Osteosarcoma With High Tumor Mutational Burden

BackgroundImmunotherapy has provided an effective method for the treatment of many cancers. However, its efficacy in osteosarcoma is not satisfactory so far.Case PresentationHere, we presented a case of osteosarcoma treated with sequential chemotherapy and immunotherapy and showed promising therapeutic potential. The 29-year-old female patient presented 9th rib osteosarcoma with suspected right lung lower lobe metastasis. Surgery was performed to remove the primary lesion, and a series of chemotherapies were given afterward in consideration of the response and tolerance. The right lung lower lobe metastasis was under control first but progressed (PD) 9 months after the initiation of therapy. The lesion was surgically removed and subsequent chemotherapy was implemented. The patient had good tolerance with chemotherapy and maintained well for approximately 11 months before the discovery of 11th rib and right lung upper lobe metastases. Surgery was then performed on both lesions and achieved complete response. Post-surgical brief chemotherapy and subsequent long-term immunotherapy (pembrolizumab) maintained continuous remission for 33 months. The patient survived for 60 months with well-controlled disease from the time of confirmed diagnosis. Genetic alterations of all primary and metastatic lesions were investigated by whole-exome sequencing (WES). Substantial similarity in mutational landscape between the primary lesion and 11th rib metastasis and between the two lung metastases were revealed, while substantial heterogeneity was found between the rib lesions and lung metastases. The tumor mutational burden (TMB) for the 9th rib primary lesion, the metastatic 11th rib lesion, and the metastatic right upper and lower lobe nodule tissues was 8.02, 2.38, 4.61, and 0.14 mutations/Mb, respectively. The primary lesion exhibited the most diverse copy number variation (CNV) changes among all lesions. Furthermore, pathway enrichment analysis also suggested significant heterogeneity among the lesions.ConclusionsSurgery with sequential chemotherapy and maintenance immunotherapy was shown to have good response for the first time on osteosarcoma patient who had high TMB tumor lesions and good tolerance for chemotherapy and immunotherapy

Compression of Phase-Only Holograms with JPEG Standard and Deep Learning

It is a critical issue to reduce the enormous amount of data in the processing, storage and transmission of a hologram in digital format. In photograph compression, the JPEG standard is commonly supported by almost every system and device. It will be favorable if JPEG standard is applicable to hologram compression, with advantages of universal compatibility. However, the reconstructed image from a JPEG compressed hologram suffers from severe quality degradation since some high frequency features in the hologram will be lost during the compression process. In this work, we employ a deep convolutional neural network to reduce the artifacts in a JPEG compressed hologram. Simulation and experimental results reveal that our proposed &ldquo;JPEG + deep learning&rdquo; hologram compression scheme can achieve satisfactory reconstruction results for a computer-generated phase-only hologram after compression

Comparative proteomic analysis of pepper (Capsicum annuum L.) seedlings under selenium stress

Selenium (Se) is an essential trace element for human and animal health. Se fertilizer has been used to increase the Se content in crops to meet the Se requirements in humans and animals. To address the challenge of Se poisoning in plants, the mechanisms underlying Se-induced stress in plants must be understood. Here, to elucidate the effects of Se stress on the protein levels in pepper, we used an integrated approach involving tandem mass tag labeling, high performance liquid chromatography fractionation, and mass spectrometry-based analysis. A total of 4,693 proteins were identified, 3,938 of which yielded quantitative information. Among them, the expression of 172 proteins was up-regulated, and the expression of 28 proteins was down-regulated in the Se/mock treatment comparison. According to the above data, we performed a systematic bioinformatics analysis of all identified proteins and differentially expressed proteins (DEPs). The DEPs were most strongly associated with the terms “metabolic process,” “posttranslational modification, protein turnover, chaperones,” and “protein processing in endoplasmic reticulum” according to Gene Ontology, eukaryotic orthologous groups classification, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, respectively. Furthermore, several heat shock proteins were identified as DEPs. These results provide insights that may facilitate further studies on the pepper proteome expressed downstream of the Se stress response. Our data revealed that the responses of pepper to Se stress involve various pathways

Atomic Replacement of PtNi Nanoalloys within Zn-ZIF‑8 for the Fabrication of a Multisite CO₂ Reduction Electrocatalyst

Exploring the transformation/interconversion pathways of catalytic active metal species (single atoms, clusters, nanoparticles) on a support is crucial for the fabrication of high-efficiency catalysts, the investigation of how catalysts are deactivated, and the regeneration of spent catalysts. Sintering and redispersion represent the two main transformation modes for metal active components in heterogeneous catalysts. Herein, we established a novel solid-state atomic replacement transformation for metal catalysts, through which metal atoms exchanged between single atoms and nanoalloys to form a new set of nanoalloys and single atoms. Specifically, we found that the Ni of the PtNi nanoalloy and the Zn of the ZIF-8-derived Zn1 on nitrogen-doped carbon (Zn1-CN) experienced metal interchange to produce PtZn nanocrystals and Ni single atoms (Ni1-CN) at high temperature. The elemental migration and chemical bond evolution during the atomic replacement displayed a Ni and Zn mutual migration feature. Density functional theory calculations revealed that the atomic replacement was realized by endothermically stretching Zn from the CN support into the nanoalloy and exothermically trapping Ni with defects on the CN support. Owing to the synergistic effect of the PtZn nanocrystal and Ni1-CN, the obtained (PtZn)n/Ni1-CN multisite catalyst showed a lower energy barrier of CO2 protonation and CO desorption than that of the reference catalysts in the CO2 reduction reaction (CO2RR), resulting in a much enhanced CO2RR catalytic performance. This unique atomic replacement transformation was also applicable to other metal alloys such as PtPd