[Research progress in methylation modification in tooth root development]

Methylation modification is one of the most common epigenetic modification regulation in eukaryotes, including histone methylation, DNA methylation, RNA methylation, etc., which plays an important regulatory role in physiological processes and pathologic occurrence and development. Tooth root development is carried out by both epithelial and mesenchymal cells and involves a variety of cell-molecular interactions. In recent years, a large number of studies have found that methylation plays a key role in the regulation of tooth root development and expands the mechanism network of tooth root development. In this paper, we review the role and mechanism of methylation modification during root development.

Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15  PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.

[Comparative study of percutaneous transfacet screw and pedicle screw in oblique lumbar interbody fusion for the treatment of single-level lumbar spinal stenosis]

Objective: To conduct a comparative study of radiological and clinical outcomes between percutaneous transfacet screw (TFS) and pedicle screw (BPS) in oblique lateral lumbar interbody fusion (OLIF) for single-level lumbar spinal stenosis. Methods: A retrospective cohort study. Patients who underwent OLIF with TFS or BPS for the treatment of single-level lumbar spinal stenosis at Beijing Jishuitan Hospital from January 2019 to June 2022 were retrospectively analyzed. Radiological parameters and clinical indicators were compared between the two groups. Radiological parameters included preoperative, immediate postoperative (within 5 days), and 1-year postoperative measurements of disc height and segmental lordosis angle, as well as interbody fusion status at 1 year postoperatively. Clinical indicators included operative time, blood loss, length of hospital stay, complications, and Oswestry Disability Index (ODI), visual analogue scale (VAS) scores for back pain, and leg pain before and 1 year after surgery. Results: Four male and 10 female patients with an average age of (61.0±11.2) years underwent OLIF with TFS, while 9 male and 12 female patients underwent OLIF with BPS, with a mean age of (60.9±6.7) years. There was no statistically significant difference in preoperative disc height between the TFS and BPS groups (P>0.05). The immediate postoperative disc height was (12.9±2.1) mm and it was (10.4±1.7) mm at 1-year follow-up in the TFS group; in the BPS group, it was (12.9±2.1) mm immediately postoperatively and (11.9±2.1) mm at 1-year follow-up; there was statistically significant difference between the two groups at 1-year follow-up (P=0.037). The segmental lordosis angle showed no significant differences within each group or between the two groups at preoperative, immediate postoperative, or 1-year postoperative follow-up (all P>0.05). At 1-year postoperative follow-up, the fusion rates was 92.9%(13/14) in the TFS group and 95.2%(20/21) in the BPS group, with no statistically significant difference between the two groups (P>0.05). The TFS group had a significantly shorter operative time and less blood loss compared to the BPS group [(164.3±33.9) minutes vs (191.7±31.8) minutes and (74.3±46.9) ml vs (124.8±54.0) ml, respectively] (both P<0.05). Both groups showed significant improvement in ODI and VAS scores at 1 year postoperatively compared to those preoperatively, but with no statistically significant difference was found between the groups (both P>0.05). Conclusions: OLIF with TFS fixation can effectively restore disc height and alleviate back and leg pain in patients with single-level lumbar spinal stenosis. Compared to the OLIF with BPS procedure, OLIF with TFS has shorter operative time and less blood loss.

TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution

Transformer-based method has demonstrated promising performance in image super-resolution tasks, due to its long-range and global aggregation capability. However, the existing Transformer brings two critical challenges for applying it in large-area earth observation scenes: (1) redundant token representation due to most irrelevant tokens; (2) single-scale representation which ignores scale correlation modeling of similar ground observation targets. To this end, this paper proposes to adaptively eliminate the interference of irreverent tokens for a more compact self-attention calculation. Specifically, we devise a Residual Token Selective Group (RTSG) to grasp the most crucial token by dynamically selecting the top- k keys in terms of score ranking for each query. For better feature aggregation, a Multi-scale Feed-forward Layer (MFL) is developed to generate an enriched representation of multi-scale feature mixtures during feed-forward process. Moreover, we also proposed a Global Context Attention (GCA) to fully explore the most informative components, thus introducing more inductive bias to the RTSG for an accurate reconstruction. In particular, multiple cascaded RTSGs form our final Top- k Token Selective Transformer (TTST) to achieve progressive representation. Extensive experiments on simulated and real-world remote sensing datasets demonstrate our TTST could perform favorably against state-of-the-art CNN-based and Transformer-based methods, both qualitatively and quantitatively. In brief, TTST outperforms the state-of-the-art approach (HAT-L) in terms of PSNR by 0.14 dB on average, but only accounts for 47.26% and 46.97% of its computational cost and parameters. The code and pre-trained TTST will be available at https://github.com/XY-boy/TTST for validation.

DNA damage response-related immune activation signature predicts the response to immune checkpoint inhibitors: from gastrointestinal cancer analysis to pan-cancer validation

OBJECTIVE

DNA damage response (DDR) deficiency has emerged as a prominent determinant of tumor immunogenicity. This study aimed to construct a DDR-related immune activation (DRIA) signature and evaluate the predictive accuracy of the DRIA signature for response to immune checkpoint inhibitor (ICI) therapy in gastrointestinal (GI) cancer.

METHODS

A DRIA signature was established based on two previously reported DNA damage immune response assays. Clinical and gene expression data from two published GI cancer cohorts were used to assess and validate the association between the DRIA score and response to ICI therapy. The predictive accuracy of the DRIA score was validated based on one ICI-treated melanoma and three pan-cancer published cohorts.

RESULTS

The DRIA signature includes three genes (CXCL10, IDO1, and IFI44L). In the discovery cancer cohort, DRIA-high patients with gastric cancer achieved a higher response rate to ICI therapy than DRIA-low patients (81.8% vs. 8.8%; P < 0.001), and the predictive accuracy of the DRIA score [area under the receiver operating characteristic curve (AUC) = 0.845] was superior to the predictive accuracy of PD-L1 expression, tumor mutational burden, microsatellite instability, and Epstein-Barr virus status. The validation cohort demonstrated that the DRIA score identified responders with microsatellite-stable colorectal and pancreatic adenocarcinoma who received dual PD-1 and CTLA-4 blockade with radiation therapy. Furthermore, the predictive performance of the DRIA score was shown to be robust through an extended validation in melanoma, urothelial cancer, and pan-cancer.

CONCLUSIONS

The DRIA signature has superior and robust predictive accuracy for the efficacy of ICI therapy in GI cancer and pan-cancer, indicating that the DRIA signature may serve as a powerful biomarker for guiding ICI therapy decisions.

Measurement of Ultra-High-Energy Diffuse Gamma-Ray Emission of the Galactic Plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic γ-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this Letter, we report the measurements of diffuse γ rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner (15°10  TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of -2.99±0.04, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of ∼3 than the prediction. A similar spectrum with an index of -2.99±0.07 is found in the outer Galaxy region, and the absolute flux for 10≲E≲60  TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.

Serum human epidermal growth factor receptor-2 extracellular domain, carcinoma embryonic antigen and carbohydrate antigen 15-3 combined detection in early diagnosis of breast cancer

The multi-markers combined detection can make up for the deficiency of single marker detection and significantly increase the positive detection rates of tumors. This study aimed to assess the performance of serum HER-2 extracellular domain (HER-2/neu ECD), carcinoembryonic antigen (CEA), and cancer antigen 15-3 (CA15-3) in early screening and auxiliary diagnosis of breast cancer. The HER-2, CEA, and CA15-3 serum levels were measured in 164 healthy volunteers, 111 patients with benign nodules (BN), 123 with early breast cancer (EBC), and 25 with advanced breast cancer. In distinguishing health and EBC, the sensitivity and specificity of joint detection of HER-2, CEA, and CA15-3 were 96.75% and 96.95%, respectively; the accuracy was up to 96.19%, and the AUC was 0.994. In the cohort for distinguishing BN from EBC, serum HER-2, CEA, and CA15-3 sensitivities were 77.03%, 75.27%, and 48.65%, respectively. Combined with three markers, the sensitivity was increased to 84.46%, the AUC was 0.834. All in all, through the combined detection of serum HER-2, CEA and CA15-3 levels in healthy volunteers, BN and EBC, our study found that this method can significantly improve the diagnosis level of breast cancer, suggesting that the three markers panel can be used as an effective tool to improve the early screening level, early diagnosis, and clinical intervention of breast cancer.

[Prognostic significance and immune cell infiltration analysis of differentially expressed genes in malignant pleural mesothelioma]

Objective: To explore and analyze differential expressed genes in malignant pleural mesothelioma (MPM) by bioinformatics method, and to study their prognostic value in MPM and their potential role in immunotherapy. Methods: In January 2022, the dataset GSE51024 was downloaded from the GEO database, and MPM (55 cases) and normal tissue (41 cases) samples were obtained. Using R software and HMDD and miRNet database, MPM-related differential genes were screened and co-expressed genes were identified. Co-expressed genes were enriched and functionally annotated, and protein-protein interaction (PPI) networks were constructed and key genes were identified using the STRING database and Cytoscape software. TRRUST and GEPIA databases were used to predict transcription factors of key genes and to analyze prognosis and survival. The correlation between key genes and the degree of infiltration of immune cells was analyzed using TIMER. Results: A total of 435 co-expressed genes were obtained, which were mainly concentrated in the extracellular matrix tissue and the signaling pathways of cell adhesion molecules. Combined with PPI and TRRUST database, seven key MPM prognostic genes were identified. Among them, cyclin 20 (CDC20) , cell cycle checkpoint kinase 1 (CHEK1) , enhancer of Zeste homolog 2 (EZH2) , ribonucleotide reductase subunit M2 (RRM2) , topoisomerase 2A (TOP2A) , ubiquitin like plant homeodomain and ring finger domain 1 (UHRF1) were significantly up-regulated in MPM, while cyclin A1 (CCNA1) was significantly down-regulated. The expressions of CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 genes were significantly associated with MPM overall survival (P<0.05) . The expressions of CDC20, CHEK1, EZH2, RRM2 and TOP2A genes were positively correlated with B cells and dendritic cells (P<0.05) , and negatively correlated with neutrophils (P<0.05) . Conclusion: CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 may be potential prognostic markers in MPM patients, and their expressions may be related to MPM tumor immunity.

Association of CDX2 and mucin expression with chemotherapeutic benefits in patients with stage II/III gastric cancer

BACKGROUND

Better predictors of patients with stage II/III gastric cancer (GC) most likely to benefit from adjuvant chemotherapy are urgently needed. This study aimed to assess the ability of CDX2 and mucin markers to predict prognosis and fluorouracil-based adjuvant chemotherapy benefits.

METHODS

CDX2 and mucin protein expressions were examined by immunohistochemistry and compared with survival and adjuvant chemotherapy benefits in a prospective evaluation cohort of 782 stage II/III GC patients. Then, the main findings were validated in an independent validation cohort (n = 386) and an external mRNA sequencing dataset (ACRG cohort, n = 193).

RESULTS

In the evaluation cohort, CDX2, CD10, MUC2, MUC5AC, and MUC6 expressions were observed in 59.7%, 26.7%, 27.6%, 55.1%, and 57.7% of patients, respectively. However, only the expression of CDX2 was found to be associated with adjuvant chemotherapy benefits. Most importantly, CDX2-negative patients had a poorer prognosis when treated with surgery only, while the prognosis of CDX2-negative and CDX2-positive patients was similar when receiving postoperative adjuvant chemotherapy. Further analysis revealed that patients with CDX2 negative tumors benefited from chemotherapy (5-year overall survival rates: 60.0% with chemotherapy vs. 23.2% with surgery-only, p < 0.001), whereas patients with CDX2 positive tumors did not (pinteraction  = 0.004). Consistent results were obtained in the validation and ACRG cohorts.

CONCLUSIONS

Negative expression of CDX2 is an independent risk factor for survival in stage II/III GC, but subsequent adjuvant chemotherapy is able to compensate for this unfavorable effect. Therefore, active chemotherapy is more urgent for patients with negative CDX2 expression than for patients with positive CDX2 expression.

A tera-electron volt afterglow from a narrow jet in an extremely bright gamma-ray burst

Some gamma-ray bursts (GRBs) have a tera-electron volt (TeV) afterglow, but the early onset of this has not been observed. We report observations with the Large High Altitude Air Shower Observatory of the bright GRB 221009A, which serendipitously occurred within the instrument field of view. More than 64,000 photons >0.2 TeV were detected within the first 3000 seconds. The TeV flux began several minutes after the GRB trigger, then rose to a peak about 10 seconds later. This was followed by a decay phase, which became more rapid ~650 seconds after the peak. We interpret the emission using a model of a relativistic jet with half-opening angle ~0.8°. This is consistent with the core of a structured jet and could explain the high isotropic energy of this GRB.

Hyperspectral Image Denoising: From Model-Driven, Data-Driven, to Model-Data-Driven

Mixed noise pollution in HSI severely disturbs subsequent interpretations and applications. In this technical review, we first give the noise analysis in different noisy HSIs and conclude crucial points for programming HSI denoising algorithms. Then, a general HSI restoration model is formulated for optimization. Later, we comprehensively review existing HSI denoising methods, from model-driven strategy (nonlocal mean, total variation, sparse representation, low-rank matrix approximation, and low-rank tensor factorization), data-driven strategy 2-D convolutional neural network (CNN), 3-D CNN, hybrid, and unsupervised networks, to model-data-driven strategy. The advantages and disadvantages of each strategy for HSI denoising are summarized and contrasted. Behind this, we present an evaluation of the HSI denoising methods for various noisy HSIs in simulated and real experiments. The classification results of denoised HSIs and execution efficiency are depicted through these HSI denoising methods. Finally, prospects of future HSI denoising methods are listed in this technical review to guide the ongoing road for HSI denoising. The HSI denoising dataset could be found at https://qzhang95.github.io.

Mass Measurement of Upper fp-Shell N=Z-2 and N=Z-1 Nuclei and the Importance of Three-Nucleon Force along the N=Z Line

Using a novel method of isochronous mass spectrometry, the masses of ^{62}Ge, ^{64}As, ^{66}Se, and ^{70}Kr are measured for the first time, and the masses of ^{58}Zn, ^{61}Ga, ^{63}Ge, ^{65}As, ^{67}Se, ^{71}Kr, and ^{75}Sr are redetermined with improved accuracy. The new masses allow us to derive residual proton-neutron interactions (δV_{pn}) in the N=Z nuclei, which are found to decrease (increase) with increasing mass A for even-even (odd-odd) nuclei beyond Z=28. This bifurcation of δV_{pn} cannot be reproduced by the available mass models, nor is it consistent with expectations of a pseudo-SU(4) symmetry restoration in the fp shell. We performed ab initio calculations with a chiral three-nucleon force (3NF) included, which indicate the enhancement of the T=1 pn pairing over the T=0 pn pairing in this mass region, leading to the opposite evolving trends of δV_{pn} in even-even and odd-odd nuclei.

E3 ubiquitin ligase RNF180 prevents excessive PCDH10 methylation to suppress the proliferation and metastasis of gastric cancer cells by promoting ubiquitination of DNMT1

BACKGROUND

Downregulation of certain tumor-suppressor genes (TSGs) by aberrant methylation of CpG islands in the promoter region contributes a great deal to the oncogenesis and progression of several cancers, including gastric cancer (GC). Protocadherin 10 (PCDH10) is a newly identified TSG in various cancers and is downregulated in GC; however, the specific mechanisms of PCDH10 in GC remain elusive. Here, we elucidated a novel epigenetic regulatory signaling pathway involving the E3 ubiquitin ligase RNF180 and DNA methyltransferase 1 (DNMT1), responsible for modulating PCDH10 expression by affecting its promoter methylation.

RESULTS

We revealed that PCDH10 was downregulated in GC cells and tissues, and low PCDH10 expression was correlated with lymph node metastasis and poor prognosis in patients with GC. Additionally, PCDH10 overexpression suppressed GC cell proliferation and metastasis. Mechanistically, DNMT1-mediated promoter hypermethylation resulted in decreased expression of PCDH10 in GC tissues and cells. Further analysis revealed that RNF180 can bind directly to DNMT1 and was involved in DNMT1 degradation via ubiquitination. Additionally, a positive correlation was found between RNF180 and PCDH10 expression and an inverse association between DNMT1 and PCDH10 expression showed considerable prognostic significance.

CONCLUSION

Our data showed that RNF180 overexpression upregulated PCDH10 expression via ubiquitin-dependent degradation of DNMT1, thus suppressing GC cell proliferation, indicating that the RNF180/DNMT1/PCDH10 axis could be a potential therapeutic target for GC treatment.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms

PURPOSE

Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration.

METHODS

We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC).

RESULTS

A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity.

CONCLUSION

ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

[Study on the related factors of antiviral treatment in previously reported hepatitis C patients based on the Andersen model]

Objective: To understand the basic characteristics of previously reported patients with hepatitis C and analyze the related factors affecting their antiviral treatment. Methods: A convenient sampling method was adopted. Patients who had been previously diagnosed with hepatitis C in the Wenshan Prefecture of Yunnan Province and Xuzhou City of Jiangsu Province were contacted by telephone for an interview study. The Andersen health service utilization behavior model and related literature were used to design the research framework for antiviral treatment in previously reported hepatitis C patients. A step-by-step multivariate regression analysis was used in previously reported hepatitis C patients treated with antiviral therapy. Results: A total of 483 hepatitis C patients, aged 51.73 ± 12.06 years, were investigated. The proportion of male, agricultural occupants who were registered permanent residents, farmers and migrant workers was 65.24%, 67.49%, and 58.18%, respectively. Han ethnicity (70.81%), married (77.02%), and junior high school and below educational level (82.61%) were the main ones. Multivariate logistic regression analysis results showed that married patients with hepatitis C (OR = 3.19, 95% CI: 1.93-5.25, compared with unmarried, divorced, and widowed patients) with high school education or above (OR = 2.54, 95% CI: 1.54-4.20, compared with patients with junior high school education or below) were more likely to receive antiviral treatment in the predisposition module. Patients with severe self-perceived hepatitis C in the need factor module (compared with patients with mild self-perceived disease, OR = 3.36, 95% CI: 2.09-5.40) were more likely to receive treatment. In the competency module, the family's per capita monthly income was more than 1,000 yuan (compared with patients with per capita monthly income below 1,000 yuan, OR = 1.59, 95% CI: 1.02-2.47), and the patients had a high level of awareness of hepatitis C knowledge (compared with patients with a low level of knowledge, OR = 1.54, 95% CI: 1.01-2.35), and the family members who knew the patient's infection status (compared with patients with an unknown infection status, OR = 4.59, 95% CI: 2.24-9.39) were more likely to receive antiviral treatment. Conclusion: Different income, educational, and marital statuses are related to antiviral treatment behavior in hepatitis C patients. Family support of hepatitis C patients receiving hepatitis C-related knowledge and their families knowing the infection status is more important in promoting the antiviral treatment of patients, suggesting that in the future, we should further strengthen the hepatitis C knowledge of hepatitis C patients, especially the family support of hepatitis C patients' families in treatment.

A new perspective to satellite-based retrieval of ground-level air pollution: Simultaneous estimation of multiple pollutants based on physics-informed multi-task learning

Remote sensing of air pollution is essential for air quality management and health risk assessment. Many machine-learning-based retrieval models have been established for estimating various kinds of air pollutants. These methods mainly aimed to estimate a single pollutant (single-pollutant approach). However, different air pollutants interact with each other and are highly correlated. Building a unified model and conducting a joint retrieval of multiple pollutant can make a better use of these connections and improve the model efficiency. This study proposed a physics-informed multi-task deep neural network (phyMTDNN) for the joint retrieval of six main air pollutants, i.e., PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃. The relationships among these pollutants were used to design the physics-informed network structure and loss function. Top-of-atmosphere reflectance which can generate retrieval results at ultrahigh resolution was used as model input. Experiments for mainland China in 2019 showed that the proposed model successfully achieved simultaneous estimation of six air pollutants, with the cross-validated R² for the six pollutants varying from 0.72 to 0.90. The contrast experiments proved that physics-informed network structure contributed to the most of the model performance improvement. Compared to the single-pollutant approach, phyMTDNN ameliorated the model accuracy on traces gases retrieval. Furthermore, the modeling efficiency was largely improved in that a lot of repetitive work was avoided and modeling method was optimized. The proposed new multiple-pollutant retrieval frame can be applied to various fields for multi-variate retrieval or estimation.

High spatiotemporal resolution estimation of AOD from Himawari-8 using an ensemble machine learning gap-filling method

The data incompleteness of aerosol optical depth (AOD) products and their lack of availability in highly urbanized areas limit their great potential of application in air quality research. In this study, we developed an ensemble machine-learning approach that integrated random forest-based Space Interpolation Model (SIM) and deep neural network-based Time Interpolation Model (TIM) to achieve high spatiotemporal resolution dataset of AOD. The spatial interpolation model first filled the spatial gaps in the Level-2 Himawari-8 hourly AOD product in 0.05° (∼5 km) spatial resolution, while the time interpolation model further improved the temporal resolution to 10 min on its basis. A full-coverage AOD dataset of Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) in 2020 was obtained as a practical implementation. The validation against in-situ AOD observations from AERONET and SONET indicated that this new dataset was satisfactory (R = 0.80), and especially in spring and summer. Overall, our ensemble machine-learning model provided an effective scheme for reconstruction of AOD with high spatiotemporal resolution of 0.05° and 10 min, which may further advance the near-real-time monitoring of air-quality in urban areas.

Constraints on Heavy Decaying Dark Matter from 570 Days of LHAASO Observations

The kilometer square array (KM2A) of the large high altitude air shower observatory (LHAASO) aims at surveying the northern γ-ray sky at energies above 10 TeV with unprecedented sensitivity. γ-ray observations have long been one of the most powerful tools for dark matter searches, as, e.g., high-energy γ rays could be produced by the decays of heavy dark matter particles. In this Letter, we present the first dark matter analysis with LHAASO-KM2A, using the first 340 days of data from 1/2-KM2A and 230 days of data from 3/4-KM2A. Several regions of interest are used to search for a signal and account for the residual cosmic-ray background after γ/hadron separation. We find no excess of dark matter signals, and thus place some of the strongest γ-ray constraints on the lifetime of heavy dark matter particles with mass between 10^{5} and 10^{9}  GeV. Our results with LHAASO are robust, and have important implications for dark matter interpretations of the diffuse astrophysical high-energy neutrino emission.

Generating a long-term (2003-2020) hourly 0.25° global PM2.5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS)

Generating a long-term high-spatiotemporal resolution global PM_2.5 dataset is of great significance for environmental management to mitigate the air pollution concerns worldwide. However, the current long-term (2003-2020) global reanalysis dataset Copernicus Atmosphere Monitoring Service (CAMS) reanalysis has drawbacks in fine-scale research due to its coarse spatiotemporal resolution (0.75°, 3-h). Hence, this paper developed a deep learning-based framework (DeepCAMS) to downscale CAMS PM_2.5 product on the spatiotemporal dimension for resolution enhancement. The nonlinear statistical downscaling from low-resolution (LR) to high-resolution (HR) data can be learned from the high quality (0.25°, hourly) but short-term (2018-2020) Goddard Earth Observing System composition forecast (GEOS-CF) system PM_2.5 product. Compared to the conventional spatiotemporal interpolation methods, simulation validations on GEOS-CF demonstrate that DeepCAMS is capable of producing accurate temporal variations with an improvement of Root-Mean-Squared Error (RMSE) of 0.84 (4.46 to 5.30) ug/m³ and spatial details with an improvement of Mean Absolute Error (MAE) of 0.16 (0.34 to 0.50) ug/m³. The real validations on CAMS reflect convincing spatial consistency and temporal continuity at both regional and global scales. Furthermore, the proposed dataset is validated with OpenAQ air quality data from 2017 to 2019, and the in-situ validations illustrate that the DeepCAMS maintains the consistent precision (R: 0.597) as the original CAMS (R: 0.593) while tripling the spatiotemporal resolution. The proposed dataset will be available at https://doi.org/10.5281/zenodo.6381600.

[A multicenter study on childhood Hodgkin lymphoma treated with HL-2013 regimen in China]

Objective: To evaluate the efficacy of the Hodgkin lymphoma (HL)-2013 regimen in the treatment of children with HL, and to investigate the prognostic factors of childhood HL. Methods: Clinical data of 145 children (aged ≤18 years) with newly diagnosed HL, treated with HL-2013 regimen in 8 tertiary referral centers for childhood cancer from August 2011 to April 2021 were analyzed retrospectively. All the diagnosis were confirmed by histopathological morphology and immunohistochemical examination. The clinical characteristics and treatment outcomes were summarized, and the patients were divided into different groups according to clinical characteristics. Kaplan-Meier method was used for survival analysis, and the comparison of survival rates between groups was performed with Log-rank test. Results: Of the 145 cases, there were 115 males and 30 females, the age at diagnosis was 7.9 (5.8, 10.6) years. Cervical lymph node enlargement (114 cases, 78.6%) was the common symptom of the disease, and 57 patients (39.3%) were accompanied by large masses. The most common pathological classification was mixed cell type (93 cases, 64.1%). According to the Ann Arbor staging system, there were 9 cases of stage Ⅰ, 62 cases of stage Ⅱ, 45 cases of stage Ⅲ, 29 cases of stage Ⅳ. According to the risk stratification: there were 14 cases of low-risk group, 76 cases of medium-risk group and 55 cases of high-risk group. Of all patients, 68 cases (46.9%) achieved an early complete remission (CR) after 2 courses of chemotherapy, and the CR rate was 93.8% (136/145) after first-line treatment. Disease recurrence or progression occurred in 22 cases (15.2%). Of all patients, 125 cases survived, 6 cases died and 14 cases were lost to follow-up. Among the survived cases, 123 cases were continuously at CR state,and the follow-up time was 55 (40, 76) months. The 5-year overall survival (OS) and event free survival (EFS) rates were (95.3±1.9)% and (84.2±3.0)% for the entire group, respectively. 5-year OS and EFS rates for patients with stage Ⅲ-Ⅳ were both lower than those for patients with stage Ⅰ-Ⅱ (χ²=6.28 and 7.58, both P<0.05), the 5-year OS and EFS rates for patients in high-risk group were both lower than those for patients in low-risk and medium-risk group (χ²=10.93, 7.79, both P<0.05). The 5-year OS rates for the patient with early CR and without early CR were 100.0% and (90.9±3.6)% (χ²=5.77, P=0.016). EFS rates for the patient with early CR (68 cases) and without early CR (77 cases) were (93.8±3.0)% and (75.8±5.0)% (χ²=8.78, P=0.003). Conclusions: HL-2013 regimen is significantly effective in the treatment of pediatric HL. However, the patients in high-risk group and those without early CR are prone to disease recurrence or progression. Stage Ⅲ-Ⅳ and without early CR were associated with worse prognosis.

Cooperated Spectral Low-Rankness Prior and Deep Spatial Prior for HSI Unsupervised Denoising

Model-driven methods and data-driven methods have been widely developed for hyperspectral image (HSI) denoising. However, there are pros and cons in both model-driven and data-driven methods. To address this issue, we develop a self-supervised HSI denoising method via integrating model-driven with data-driven strategy. The proposed framework simultaneously cooperates the spectral low-rankness prior and deep spatial prior (SLRP-DSP) for HSI self-supervised denoising. SLRP-DSP introduces the Tucker factorization via orthogonal basis and reduced factor, to capture the global spectral low-rankness prior in HSI. Besides, SLRP-DSP adopts a self-supervised way to learn the deep spatial prior. The proposed method doesn't need a large number of clean HSIs as the label samples. Through the self-supervised learning, SLRP-DSP can adaptively adjust the deep spatial prior from self-spatial information for reduced spatial factor denoising. An alternating iterative optimization framework is developed to exploit the internal low-rankness prior of third-order tensors and the spatial feature extraction capacity of convolutional neural network. Compared with both existing model-driven methods and data-driven methods, experimental results manifest that the proposed SLRP-DSP outperforms on mixed noise removal in different noisy HSIs.

[Accuracy and retention of denture bases fabricated by injection molding, milling, and three-dimensional printing]

Objective: To compare the accuracy and retention of denture bases fabricated by injection molding, milling, and three-dimensional (3D) printing fabricating, in order to provide some references for clinical practice. Methods: A maxillary edentulous jaw model made was used to duplicated 10 working casts. The casts were numbered and scanned. The wax pattern was designed by digital ways and conventional methods and then the denture bases were fabricated by injection molding, milling, and 3D printing. The tissue surface of experimental denture base was obtained using a dental laboratory scanner. The deviation between the tissue surface of the fabricated denture bases and the working model was evaluated. A digital force gauge was used to measure the traction force. Results: The milling group [(0.076±0.026) mm] was more accurate than the 3D printing group [(0.117±0.041) mm] (P<0.05) and the injection group [(0.120± 0.025) mm] (P<0.05). The accuracy of 3D printing group and that of injection group were not statistically significant (P>0.05). The milling group [(9.55±2.44) N] demonstrated greater retentive force than 3D printing group [(5.19±0.06) N] and injection molding group [(1.52±0.52) N] (P<0.05). Conclusions: The denture base fabricated by milling was more accurate and showed the greatest retentive force than the other groups. And 3D printing group showed better retentive force than the injection molding group. Both digital manufacturing methods can meet the requirements of clinical application.

Spectral Response Function-Guided Deep Optimization-Driven Network for Spectral Super-Resolution

Hyperspectral images (HSIs) are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high-spatial-resolution (HR) HSIs from HR multispectral images. Traditional SSR methods include model-driven algorithms and deep learning. By unfolding a variational method, this article proposes an optimization-driven convolutional neural network (CNN) with a deep spatial-spectral prior, resulting in physically interpretable networks. Unlike the fully data-driven CNN, auxiliary spectral response function (SRF) is utilized to guide CNNs to group the bands with spectral relevance. In addition, the channel attention module (CAM) and the reformulated spectral angle mapper loss function are applied to achieve an effective reconstruction model. Finally, experiments on two types of data sets, including natural and remote sensing images, demonstrate the spectral enhancement effect of the proposed method, and also, the classification results on the remote sensing data set verified the validity of the information enhanced by the proposed method.

Safety and tolerance of Lacticaseibacillus paracasei N1115 in caesarean-born young children: a randomised, placebo-controlled trial

The administration of probiotics may help to improve dysbiosis and related health problems in children delivered by caesarean section. However, the effects are strain specific, and safety combined tolerance are considered a priority. The aim of this study was to evaluate the safety and tolerance of Lacticaseibacillus paracasei N1115 in caesarean-born children aged 6-24 months via a randomised, placebo-controlled intervention study. In total, 101 children were included and randomised to receive either a sachet of L. paracasei N1115 (2×1010 cfu/g, 2 g/day) or placebo (maltodextrin, 2 g/day) per day for 12 weeks. Anthropometric parameters were measured by trained nurses, and defecation characteristics, gastrointestinal symptoms, (serious) adverse events ((s)AEs), crying patterns and lifestyle behaviours were recorded by parents or guardians. Neurocognitive development was assessed by the Ages and Stages Questionnaires-3 (ASQ-3) before and after the intervention. The only difference between groups regarding defecation characteristics was a significant treatment × time effect on stool frequency (P=0.007), as the number of defecations was significantly higher in the probiotic group (around 1.2-1.3 times/day) than in the placebo group (around 1.0 times/day) in the later intervention period (P=0.035 at week 9; P=0.048 at week 10; P=0.026 at week 12). The use of L. paracasei N1115 also reduced the incidence rate of constipation (Incidence rate ratio (IRR): 0.120; 95% confidence interval (CI): 0.015, 0.967; P=0.046) and abdominal pain (IRR: 0.562; 95% CI: 0.358, 0.882; P=0.012). Changes in anthropometric parameters, including weight, height and head circumference, did not differ significantly between groups, nor did measures of crying, sleep, outdoor activity, temper, appetite or the ASQ-3 scores. No adverse events associated with consumption of the probiotic were reported. Thus, the administration of L. paracasei N1115 is safe and well-tolerated in caesarean-born children aged 6-24 months. Furthermore, it may ameliorate gastrointestinal function to some extent.

Estimation of high spatial resolution ground-level ozone concentrations based on Landsat 8 TIR bands with deep forest model

In recent years, China has been facing severe ozone (O₃) pollution, which poses a remarkable threat to human health. Most estimation methods only provide ozone products at a relatively coarse resolution, such as 5 km, but high-resolution ozone data are essential for ozone pollution prevention and control. To this end, we proposed a new framework for estimating ozone concentrations at 300 m resolution in China based on Landsat 8 infrared (IR) bands and meteorological data using a deep forest (DF) model. DF combines the excellent performance of tree integration with the expressive power of hierarchical distributed representations of neural networks. The accuracy and mapping results of DF are considerably better than some widely used machine learning methods (generalized regression neural regression network and random forest). The sample-based cross-validation (CV), station-based CV, time-based CV, and extrapolation validation show that the estimations of DF are in high agreement with the station observations with determination coefficient values of 0.938, 0.926, 0.687, and 0.660, respectively. The proposed method was used to analyze the spatial and temporal ozone variations at fine scales in three typical Chinese cities (Beijing, Wuhan and Guangzhou), where the mean ozone concentrations during the polluted season are consistent with the land use and urban heat island distribution. The rationality of ozone estimates was verified, and the advantages of high-resolution mapping was demonstrated by comparing the monitoring data from municipal controlling stations in Beijing, 10 km ozone products, and satellite images. Our product can represent spatial details and locate local pollution sources, such as temples. The proposed method has important implications for the fine-scale monitoring of ozone pollution.

Retraction Note: The carcinogenic complex lncRNA FOXP4-AS1/EZH2/LSD1 accelerates proliferation, migration and invasion of gastric cancer

The article "The carcinogenic complex lncRNA FOXP4-AS1/EZH2/LSD1 accelerates proliferation, migration and invasion of gastric cancer, by R.-Y. Chen, Q. Ju, L.-M. Feng, Q. Yuan, L. Zhang, published in Eur Rev Med Pharmacol Sci 2019; 23 (19): 8371-8376-DOI: 10.26355/eurrev_201910_19148-PMID: 31646567" has been retracted by the authors. After publication, the authors raised concerns about the reliability of the data used to conduct the study by stating that some data cannot be repeated by further research. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/19148.

Ultrahigh-resolution PM2.5 estimation from top-of-atmosphere reflectance with machine learning: Theories, methods, and applications

Intra-urban pollution monitoring requires fine particulate (PM_2.5) concentration mapping at ultrahigh-resolution (dozens to hundreds of meters). However, current PM_2.5 concentration estimation, which is mainly based on aerosol optical depth (AOD) and meteorological data, usually had a low spatial resolution (kilometers) and severe spatial missing problem, cannot be applied to intra-urban pollution monitoring. To solve these problems, top-of-atmosphere reflectance (TOAR), which contains both the information about land and atmosphere and has high resolution and large spatial coverage, may be efficiently used for PM_2.5 estimation. This study aims to systematically evaluate the feasibility of retrieving ultrahigh-resolution PM_2.5 concentration at a large scale (national level) from TOAR. Firstly, we make a detailed discussion about several important but unsolved theoretic problems on TOAR-based PM_2.5 retrieval, including the band selection, scale effect, cloud impact, and mapping quality evaluation. Secondly, four types and eight retrieval models are compared in terms of quantitative accuracy, mapping quality, model generalization, and model efficiency, with the pros and cons of each type summarized. Deep neural network (DNN) model shows the highest retrieval accuracy, and linear models were the best in efficiency and generalization. As a compromise, ensemble learning shows the best overall performance. Thirdly, using the highly accurate DNN model (cross-validated R² equals 0.93) and through combining Landsat 8 and Sentinel 2 images, a 90 m and ∼4-day resolution PM_2.5 product was generated. The retrieved maps were used for analyzing the fine-scale interannual pollution change inner the city and the pollution variations during novel coronavirus disease 2019 (COVID-19). Results of this study proves that ultrahigh resolution can bring new findings of intra-urban pollution change, which cannot be observed at previous coarse resolution. Lastly, some suggestions for future ultrahigh-resolution PM_2.5 mapping research were given.

Single-Cell Transcriptomic Atlas of Gingival Mucosa in Type 2 Diabetes

The oral gingival barrier is a constantly stimulated and dynamic environment where homeostasis is often disrupted, resulting in inflammatory periodontal diseases. Type 2 diabetes (T2D) has been reported to be associated with gingival barrier dysfunction, but the effect and underlying mechanism are inconclusive. Herein, we performed single-cell RNA sequencing (scRNA-seq) of gingiva from leptin receptor-deficient mice (db/db) to examine the gingival heterogeneity in the context of T2D. Periodontal health of control mice is characterized by populations of Krt14⁺-expressing epithelial cells and Col1a1⁺-fibroblasts mediating immune homeostasis primarily through the enrichment of innate lymphoid cells. The db/db gingiva exhibited decreased epithelial/stromal ratio and dysfunctional barrier. We further observed stromal, particularly fibroblast immune hyperresponsiveness, linked to the recruitment of myeloid-derived cells at the db/db gingiva. Both scRNA-seq and histological analysis suggested the inflammatory signaling between fibroblasts and neutrophils as a potential driver of diabetes-induced periodontal damage. Notably, the "immune-like" stromal cells were wired toward the induction of gingival γδ T hyperresponsiveness in db/db mice. Our work reveals that the "immune-like" fibroblasts with transcriptional diversity are involved in the innate immune homeostasis at the diabetic gingiva. It highlights a potentially significant role of these cell types in its pathogenesis.

Percutaneous CT-Guided Microwave Ablation Combined with Vertebral Augmentation for Treatment of Painful Spinal Metastases

BACKGROUND AND PURPOSE

Percutaneous thermal ablation followed by vertebral augmentation is an emerging minimally invasive therapeutic alternative for the management of spinal metastases. This study aimed to retrospectively evaluate the effectiveness and safety of microwave ablation combined with vertebral augmentation for the treatment of painful vertebral metastases.

MATERIALS AND METHODS

Overall, 91 patients with 140 metastatic vertebrae who experienced refractory moderate-to-severe pain were treated with CT-guided microwave ablation and vertebral augmentation. Procedural effectiveness was determined using the visual analog scale, daily morphine consumption, and the Oswestry Disability Index preprocedurally and during follow-up. Local tumor control was assessed at follow-up imaging.

RESULTS

The procedure was technically successful in all patients. The median visual analog scale score and mean morphine dose were 6 (range, 4-10) and 77.8 (SD, 31.5) mg (range, 15-143 mg), preprocedurally; 5 (range 3-8) and 34.5 (SD, 23.8) mg (range, 0-88 mg) at 3 days; 4 (range, 2-7) and 28.7 (SD, 16.4) mg (range, 0-73 mg) at 1 week; 3 (range, 1-6) and 24.6 (SD, 13.2) mg (range, 0-70 mg) at 1 month; 3 (range, 1-6) and 21.70 (SD, 10.0) mg (range, 0-42 mg) at 3 months; and 3 (range, 1-8) and 21.0 (SD, 9.9) mg (range, 0-46 mg) at 6 months postprocedurally (all P < .05). A decrease in the Oswestry Disability Index score was also observed (P < .01). Local control was achieved in 94.8% of the treated metastatic vertebrae during the 6-month follow-up period. Asymptomatic cement leakage occurred in 42 (30%) treated vertebrae. A grade 3 neural injury was observed in 1 patient (1.1%). The patient's neurologic function returned to normal following treatment with mannitol, glucocorticoids, and radiation therapy.

CONCLUSIONS

This study demonstrates that percutaneous CT-guided microwave ablation combined with vertebral augmentation is a safe and effective minimally invasive intervention for the treatment of painful spinal metastases.

Gnas Loss Causes Chondrocyte Fate Conversion in Cranial Suture Formation

Calvaria development is distinct from limb formation. Craniosynostosis is a skull deformity characterized by premature cranial suture fusion due to the loss of the GNAS gene and, consequently, its encoded protein Gαs. This birth defect requires surgery, with potential lethal consequences. So far, hardly any early-stage nonsurgical interventions for GNAS loss-related craniosynostosis are available. Here, we investigated the role of the Gnas gene in mice in guarding the distinctiveness of intramembranous ossification and how loss of Gnas triggered endochondral-like ossification within the cranial sutures. Single-cell RNA sequencing (scRNA-seq) of normal neonatal mice cranial suture chondrocytes showed a Hedgehog (Hh) inactivation pattern, which was associated with Gαs signaling activation. Loss of Gnas evoked chondrocyte-to-osteoblast fate conversion and resulted in cartilage heterotopic ossification (HO) within cranial sutures and fontanels of the mouse model, leading to a skull deformity resembling craniosynostosis in patients with loss of GNAS. Activation of ectopic Hh signaling within cranial chondrocytes stimulated the conversion of cell identity through a hypertrophy-like stage, which shared features of endochondral ossification in vivo. Reduction of Gli transcription activity by crossing with a loss-of-function Gli2 allele or injecting GLI1/2 antagonist hindered the progression of cartilage HO in neonatal stage mice. Our study uncovered the role of Gαs in maintaining cranial chondrocyte identity during neonatal calvaria development in mice and how reduction of Hh signaling could be a nonsurgical intervention to reduce skull deformity in craniosynostosis due to loss of GNAS.

Exploring Lorentz Invariance Violation from Ultrahigh-Energy γ Rays Observed by LHAASO

Recently, the LHAASO Collaboration published the detection of 12 ultrahigh-energy γ-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV γ rays from astrophysical sources may provide a very sensitive probe of the effect of the Lorentz invariance violation (LIV), which results in decay of high-energy γ rays in the superluminal scenario and hence a sharp cutoff of the energy spectrum. Two highest energy sources are studied in this work. No signature of the existence of the LIV is found in their energy spectra, and the lower limits on the LIV energy scale are derived. Our results show that the first-order LIV energy scale should be higher than about 10^{5} times the Planck scale M_{Pl} and that the second-order LIV scale is >10^{-3}M_{Pl}. Both limits improve by at least one order of magnitude the previous results.

Full-coverage spatiotemporal mapping of ambient PM2.5 and PM10 over China from Sentinel-5P and assimilated datasets: Considering the precursors and chemical compositions

Ambient concentrations of particulate matters (PM_2.5 and PM₁₀) are significant indicators for monitoring the air quality relevant to living conditions. At present, most remote sensing based approaches for the estimation of PM_2.5 and PM₁₀ employed Aerosol Optical Depth (AOD) products as the main variate. Nevertheless, the coverage of missing data is generally large in AOD products, which can cause deviations in practical applications of estimated PM_2.5 and PM₁₀ (e.g., air quality monitoring and exposure evaluation). To efficiently address this issue, our study explores a novel approach using the datasets of the precursors & chemical compositions for PM_2.5 and PM₁₀ instead of AOD products. Specifically, the daily full-coverage ambient concentrations of PM_2.5 and PM₁₀ are estimated at 5-km (0.05°) spatial girds across China based on Sentinel-5P and assimilated datasets (GEOS-FP). The estimation models are acquired via an advanced ensemble learning method named Light Gradient Boosting Machine in this paper. For comparison, the Deep Blue AOD product from VIIRS is adopted in a similar framework as a baseline (AOD-based). Validation results show that the ambient concentrations are well estimated through the proposed approach, with the space-based Cross-Validation R²s and RMSEs of 0.88 (0.83) and 11.549 (22.9) μg/m³ for PM_2.5 (PM₁₀), respectively. Meanwhile, the proposed approach achieves better performance than the AOD-based in different cases (e.g., overall and seasonal). Compared to the related previous works over China, the estimation accuracy of our method is also satisfactory. Regarding the mapping, the estimated results through the proposed approach display consecutive spatial distribution and can exactly express the seasonal variations of PM_2.5 and PM₁₀. The proposed approach could efficiently present daily full-coverage results at 5-km spatial grids. It has a large potential to be extended for providing global accurate ambient concentrations of PM_2.5 and PM₁₀ at multiple temporal scales (e.g., daily and annual).

[Clinical analysis of 60 children with anaplastic large cell lymphoma in a single center]

Objective: To summarize the clinical features, treatment outcome and prognostic factors of childhood anaplastic large cell lymphoma (ALCL). Methods: Clinical data of 60 newly diagnosed and biopsy-proven ALCL pediatric patients (≤18 years of age) at Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine from January 2010 to December 2018 were collected. All patients were treated with the Chinese Children Cancer Group-B cell-non-Hodgkin Lymphoma 2010 (CCCG-BNHL-2010) regimen. Overall survival (OS), event free survival (EFS) and progression free survival (PFS) rates were calculated by the Kaplan-Meier method. Univariate analysis was performed with Log-Rank test to find factors of poor prognosis. Results: Among 60 ALCL patients included in the current study, 39 were males and 21 females, the age of onset was 7.9 (1.2-16.7) years. Among all cases, 43 (72%) had B syndrome (any of the following: fever, drenching, weight loss). Forty-nine (82%) cases had lactate dehydrogenase (LDH) levels<2 times upper limit of normal (ULN) and 11 (18%) cases had LDH levels 2-<4 times ULN. The distribution of stages was stage Ⅰ,Ⅱ,Ⅲ, and Ⅳ in 2% (1/60), 5% (3/60), 92% (55/60), and 2% (1/60) of patients, respectively. Of 58 cases who had results of anaplastic lymphoma kinase (ALK) immunohistochemical staining, 53 (91%, 53/58) cases were positive. Visceral involvement was observed in 12 patients (20%). The 4-year OS and EFS rates were (88±4)% and (76±6)% for the entire group, respectively. Univariate analysis for gender, B symptoms, LDH level, ALK expression, clinical stage and visceral involvement showed that only LDH level correlated with an inferior OS rate (χ²=6.571, P=0.010) while not correlated with EFS rate. No independent risk factor for disease progression or recurrence was found by Logistic regression. Up to the last follow-up, 44 cases were continuously at complete remission state, and their follow-up time was 50 (13-119) months. Of 13 (23%) cases experienced disease progression or relapse, 3 cases abandoned treatment, 2 cases progressed to death, 8 cases received second line or salvage treatment (6 survived at last follow-up). For post progression or relapse cases, the 2-year OS and PFS rates were (60±16)% and (16±14)%, respectively. The treatment related death occurred in 3 cases (5%) and all of them were due to severe infection during the chemotherapy. Conclusions: The efficacy of CCCG-BNHL-2010 regimen in the treatment of children with ALCL was good. However, the safety needs to be improved as the treatment-related mortality in the present study was slightly higher. Efficient second line or salvage treatment can achieve cure in pediatric patients post progression or recurrence. LDH ≥2 times ULN was associated with worse prognosis.

[Investigation of contamination of SARS-CoV-2 in imported frozen seafood from a foreign cargo ship and risk factors for infection in stevedores in Qingdao]

Objective: To investigate the contamination status of SARS-CoV-2 in imported frozen seafood from a Russia cargo ship in Qingdao and to analyze the risk factors for infection in local stevedores. Methods: The method of "two-stage, full coverage and mixed sampling" was used to collect the seafood packaging samples for the nucleic acid detection of SARS-CoV-2 by real-time fluorescent quantitative RT-PCR. A unified questionnaire was designed to investigate 71 stevedores in two shifts through telephone interview. The stevedores were divided into two groups, with 23 in the shit with two infections was group A and 48 in the shift without infection was group B. Software Epi Info7.2 was used to identify the risk factors for SARS-CoV-2 infections in the stevedores. Results: In the frozen seafood from a Russia cargo ship, the total positive rate of SARS-CoV-2 nucleic acid in the frozen seafood was 11.53% (106/919). The positive rate of SARS-CoV-2 nucleic acid in the frozen seafood unloaded by group A (14.29%,70/490) was significantly higher than that in the frozen seafood unloaded by group B (8.39%,36/429)(χ²=7.79,P=0.01) and the viral loads detected in the frozen seafood unloaded by group A were higher than those detected in the frozen seafood unloaded by group B. The scores of personal protection and behaviors in the stevedores in group A were significantly lower than those in group B (P<0.05), and toilet use, smoking and improper hand washing before meals were the risk factors for the infection. Conclusions: The imported frozen seafood was contaminated by SARS-CoV-2 and the contamination distribution was uneven. Supervision and management of personal occupational protection and behaviors of workers engaged in imported frozen food transportation should be strengthened. It is suggested that a closed-loop monitoring and management system for the whole process of "fishing-transport- loading/unloading" should be established by marine fishery authority.

CBD Promotes Oral Ulcer Healing via Inhibiting CMPK2-Mediated Inflammasome

Oral ulcer is a common oral inflammatory lesion accompanied by severe pain but with few effective treatments. Cannabidiol (CBD) is recently emerging for its therapeutic potential in a range of diseases, including inflammatory conditions and cancers. Here we show that CBD oral spray on acid- or trauma-induced oral ulcers on mice tongue inhibits inflammation, relieves pain, and accelerates lesion closure. Notably, the enrichment of genes associated with the NOD, LRR, and NLRP3 pyrin domain-containing protein 3 (NLRP3) inflammasome pathway is downregulated after CBD treatment. The expression of cleaved-gasdermin D (GSDMD) and the percentage of pyroptotic cells are reduced as well. In addition, CBD decreases the expression of cytidine/uridine monophosphate kinase 2 (CMPK2), which subsequently inhibits the generation of oxidized mitochondria DNA and suppresses inflammasome activation. These immunomodulating effects of CBD are mostly blocked by peroxisome proliferator activated receptor γ (PPARγ) antagonist and partially antagonized by CB₁ receptor antagonist. Our results demonstrate that CBD accelerates oral ulcer healing by inhibiting CMPK2-mediated NLRP3 inflammasome activation and pyroptosis, which are mediated mostly by PPARγ in the nucleus and partially by CB₁ in the plasma membrane.

Peta-electron volt gamma-ray emission from the Crab Nebula

The Crab Nebula is a bright source of gamma rays powered by the Crab Pulsar's rotational energy through the formation and termination of a relativistic electron-positron wind. We report the detection of gamma rays from this source with energies from 5 × 10^-4 to 1.1 peta-electron volts with a spectrum showing gradual steepening over three energy decades. The ultrahigh-energy photons imply the presence of a peta-electron volt electron accelerator (a pevatron) in the nebula, with an acceleration rate exceeding 15% of the theoretical limit. We constrain the pevatron's size between 0.025 and 0.1 parsecs and the magnetic field to ≈110 microgauss. The production rate of peta-electron volt electrons, 2.5 × 10³⁶ ergs per second, constitutes 0.5% of the pulsar spin-down luminosity, although we cannot exclude a contribution of peta-electron volt protons to the production of the highest-energy gamma rays.

Extended Very-High-Energy Gamma-Ray Emission Surrounding PSR J0622+3749 Observed by LHAASO-KM2A

We report the discovery of an extended very-high-energy (VHE) gamma-ray source around the location of the middle-aged (207.8 kyr) pulsar PSR J0622+3749 with the Large High-Altitude Air Shower Observatory (LHAASO). The source is detected with a significance of 8.2σ for E>25  TeV assuming a Gaussian template. The best-fit location is (right ascension, declination) =(95.47°±0.11°,37.92°±0.09°), and the extension is 0.40°±0.07°. The energy spectrum can be described by a power-law spectrum with an index of -2.92±0.17_{stat}±0.02_{sys}. No clear extended multiwavelength counterpart of the LHAASO source has been found from the radio to sub-TeV bands. The LHAASO observations are consistent with the scenario that VHE electrons escaped from the pulsar, diffused in the interstellar medium, and scattered the interstellar radiation field. If interpreted as the pulsar halo scenario, the diffusion coefficient, inferred for electrons with median energies of ∼160  TeV, is consistent with those obtained from the extended halos around Geminga and Monogem and much smaller than that derived from cosmic ray secondaries. The LHAASO discovery of this source thus likely enriches the class of so-called pulsar halos and confirms that high-energy particles generally diffuse very slowly in the disturbed medium around pulsars.

[Effectiveness of the "14 plus 7 day quarantine" and "nucleic acid plus total antibody testing" strategy for screening imported patients with COVID-19 in Xiamen]

Objective: To analysis effectiveness of the "14 plus 7 day quarantine" and "nucleic acid plus total antibody testing" strategy (combined screening strategy) for screenin the imported patients with COVID-19 in Xiamen. Methods: The study populations were overseas travelers arriving in Xiamen from March 17 to December 31, 2020, and overseas travelers who had quarantine outside Xiamen for less than 21 days from July 18 to December 31, 2020. Data were collected and analyzed on the timing of detection, pathways, and test results of the imported patients with COVID-19 after implementing combined screening strategy. Results: A total of 304 imported patients with COVID-19 were found from 174 628 overseas travelers and 943 overseas travelers from other cities. A total of 163 cases (53.6%) were diagnosed by multitime, multisite intensive nucleic acid testing after positive finding in total antibody testing. Among them, 27 (8.9%) were first positive for nucleic acid in 14 plus 7 day quarantine and 136 were first positive for nucleic acid in 14-day quarantine. Only 8 of these individuals were tested positive for nucleic acid after positive total antibody testing. The other 128 individuals were tested positive for nucleic acid after being negative for average 2.3 times (maximum of 6 times). Aditional 155 cases might be detected by using the combined "14 plus 7 day quarantine" and " nucleic acid plus total antibody testing" strategy compared with "14-day quarantine and nucleic acid testing" strategy, accounting for 51.0% of the total inbound infections. So the combined screening strategy doubled the detection rate for imported patients with COVID-19. No second-generation case caused by overseas travelers had been reported in Xiamen as of February 26, 2021. Conclusions: Xiamen's combined screening strategy can effectively screen the imported patients with COVID-19 who were first positive for nucleic acid after 14 day quarantine. Compared with "14 day quarantine and nucleic acid testing", the combined screening strategy improved detection rate and further reduced the risk of the secondary transmission caused by the imported patients with COVID-19.

[Advances in application of tissue clearing technique in hard tissues]

Tissue clearing is a novel technique developed within recent years, which could make the tissue optical transparency using physical or chemical methods by refractive index matching. Combined with fluorescence imaging and three-dimensional reconstruction technology, it could achieve three-dimensional observing and analyze the tissue structure at the cellular resolution. The tissue clearing technique is mainly applied to soft tissues, as less to hard tissues. In recent years, many researchers have modified tissue clearing methods and made them suitable for hard tissues, such as bone and teeth. The present paper reviews the recent application of tissue clearing techniques in hard tissues.

Ultrahigh-energy photons up to 1.4 petaelectronvolts from 12 γ-ray Galactic sources

The extension of the cosmic-ray spectrum beyond 1 petaelectronvolt (PeV; 10¹⁵ electronvolts) indicates the existence of the so-called PeVatrons-cosmic-ray factories that accelerate particles to PeV energies. We need to locate and identify such objects to find the origin of Galactic cosmic rays¹. The principal signature of both electron and proton PeVatrons is ultrahigh-energy (exceeding 100 TeV) γ radiation. Evidence of the presence of a proton PeVatron has been found in the Galactic Centre, according to the detection of a hard-spectrum radiation extending to 0.04 PeV (ref. ²). Although γ-rays with energies slightly higher than 0.1 PeV have been reported from a few objects in the Galactic plane^3-6, unbiased identification and in-depth exploration of PeVatrons requires detection of γ-rays with energies well above 0.1 PeV. Here we report the detection of more than 530 photons at energies above 100 teraelectronvolts and up to 1.4 PeV from 12 ultrahigh-energy γ-ray sources with a statistical significance greater than seven standard deviations. Despite having several potential counterparts in their proximity, including pulsar wind nebulae, supernova remnants and star-forming regions, the PeVatrons responsible for the ultrahigh-energy γ-rays have not yet been firmly localized and identified (except for the Crab Nebula), leaving open the origin of these extreme accelerators.

Deep learning analysis of the primary tumour and the prediction of lymph node metastases in gastric cancer

BACKGROUND

Lymph node metastasis (LNM) in gastric cancer is a prognostic factor and has implications for the extent of lymph node dissection. The lymphatic drainage of the stomach involves multiple nodal stations with different risks of metastases. The aim of this study was to develop a deep learning system for predicting LNMs in multiple nodal stations based on preoperative CT images in patients with gastric cancer.

METHODS

Preoperative CT images from patients who underwent gastrectomy with lymph node dissection at two medical centres were analysed retrospectively. Using a discovery patient cohort, a system of deep convolutional neural networks was developed to predict pathologically confirmed LNMs at 11 regional nodal stations. To gain understanding about the networks' prediction ability, gradient-weighted class activation mapping for visualization was assessed. The performance was tested in an external cohort of patients by analysis of area under the receiver operating characteristic (ROC) curves (AUC), sensitivity and specificity.

RESULTS

The discovery and external cohorts included 1172 and 527 patients respectively. The deep learning system demonstrated excellent prediction accuracy in the external validation cohort, with a median AUC of 0·876 (range 0·856-0·893), sensitivity of 0·743 (0·551-0·859) and specificity of 0·936 (0·672-0·966) for 11 nodal stations. The imaging models substantially outperformed clinicopathological variables for predicting LNMs (median AUC 0·652, range 0·571-0·763). By visualizing nearly 19 000 subnetworks, imaging features related to intratumoral heterogeneity and the invasive front were found to be most useful for predicting LNMs.

CONCLUSION

A deep learning system for the prediction of LNMs was developed based on preoperative CT images of gastric cancer. The models require further validation but may be used to inform prognosis and guide individualized surgical treatment.

Measurement of the Cosmic Ray Helium Energy Spectrum from 70 GeV to 80 TeV with the DAMPE Space Mission

The measurement of the energy spectrum of cosmic ray helium nuclei from 70 GeV to 80 TeV using 4.5 years of data recorded by the Dark Matter Particle Explorer (DAMPE) is reported in this work. A hardening of the spectrum is observed at an energy of about 1.3 TeV, similar to previous observations. In addition, a spectral softening at about 34 TeV is revealed for the first time with large statistics and well controlled systematic uncertainties, with an overall significance of 4.3σ. The DAMPE spectral measurements of both cosmic protons and helium nuclei suggest a particle charge dependent softening energy, although with current uncertainties a dependence on the number of nucleons cannot be ruled out.

[The suppressive effects of microRNA-139-5p on proliferation and invasion of esophageal squamous cell carcinoma]

Objective: To investigate the role of microRNA-139-5p (miR-139-5p) in the occurrence and development of esophageal squamous cell carcinoma (ESCC) and its effects on cell proliferation and invasion of ESCC cells and its molecular mechanisms. Methods: Seventy-five cases of ESCC tissues and paired normal tissues were obtained from thoracic surgery of the First Affiliated Hospital of Zhengzhou University from February 2017 to March 2018. Experiment was divided into two group: ESCC (n=75) and normal esophageal tissues (n=75).GEO datasets and real-time quantitative PCR (qRT-PCR) were used to detect the expression of miR-139-5p in ESCC tissues and cells. miR-139-5p inhibitor, miR-139-5p mimic, negative control, control siRNA, T-box transcliption factor 1(TBX1) siRNA, pcDNA3.1 and pcDNA3.1-TBX1 were transfected into ESCC Eca109 and TE1 cells. qRT-PCR was used to detect the expressions of miR-139-5p and TBX1 in transfected ESCC cells. Cell counting kit 8 (CCK-8) and Transwell chamber were employed to detect cell proliferation and invasion of ESCC cells, respectively. Dual-Luciferase Reporter assay was used to analyze the interaction between miR-139-5p with TBX1. qRT-PCR, Western blot and immunohistochemistry were utilized to detect the expression of TBX1 in ESCC tissues. Western blot was used to detect the expressions of E-cadherin, N-cadherin and Vimentin after transfection. Results: The level of miR-139-5p in ESCC tissues was significantly lower than that in normal tissues (1.17±0.43 vs 5.16±3.62,P<0.001). Log-rank test showed that the survival rate of ESCC patients with high miR-139-5p level (n = 43) was significantly higher than that with low miR-139-5p level (n=32) (67.44% vs 25.00%, P = 0.005). The expression level of miR-139-5p in ESCC cells was significantly lower than that of normal esophageal epithelial cell Het-1A (all P<0.001). The proliferation and invasion ability of ECA109 and TE1 cells with high expression of miR-139-5p were significantly lower than those transfected with negative control (NC) (all P<0.05). Dual-Luciferase Reporter assay showed that miR-139-5p could bind to the 3'-untranslated region of TBX1. miR-139-5p mimic or inhibitor suppressed or promoted the expression of TBX1 protein in Eca109 and TE1 cells, respectively (all P<0.05). Downregulation of TBX1 significantly suppressed proliferation and invasion of ECA109 and TE1 cells, while overexpression of TBX1 significantly promoted proliferation and invasion of ECA109 and TE1 cells (all P<0.05). In addition, pcDNA3.1-TBX1 partially reversed the inhibition of miR-139-5p-mediated invasion ability (all P<0.05), while TBX1 siRNA partially reversed the enhancement of miR-139-5p inhibitor-mediated invasion ability (all P<0.05). Conclusion: miR-139-5p suppressed ESCC cell proliferation and invasion by targeting TBX1.

MiR-449b-5p inhibits human glioblastoma cell proliferation by inactivating WNT2B/Wnt/β-catenin signaling pathway

OBJECTIVE

As the most common primary brain cancer in adults, glioblastoma shows an extremely poor prognosis. Glioblastoma-associated deaths account for approximately 3%-4% of all malignancy-associated deaths. Numerous microRNAs (miRNAs) play important roles in the occurrence and progression of solid tumors. Herein, identifying functional miRNAs and the central molecular mechanisms would provide novel proofs for the development of targeted cancer therapies. In this study, we described the role of miR-449b-5p in restraining ontogenesis and progression of glioblastoma.

PATIENTS AND METHODS

Human glioblastoma tissues were provided by our hospital. Human U251 glioblastoma cells were infected with lentivirus induced miR-449b-5p mimics or miR-449b-5p siRNA. Real-time qPCR was carried out to determine miRNA expression. Tumor spheres formation, MTT assay, and BrdU cell proliferation assay were used to evaluate the growth ability of U251 cells. Western blot assay was performed to measure protein expression. ChIP was used to detect the capacity of β-catenin to recruit its downstream genes. Dual-Luciferase assay was conducted to detect the ability of miR-449b-5p to regulate the 3'UTR (untranslated regions) of WNT2B. TOP/FOP ratio was used to evaluate the activity of Wnt/β-catenin signaling pathway.

RESULTS

Down-regulation of miR-449b-5p expression was found in both human glioblastoma tissues and cell lines, which was negatively associated with the clinical stages. Up-regulation of miR-449b-5p inhibited tumor spheres formation, cell viability and proliferation ability of glioblastoma cells. The expression levels of WNT2B and nuclear β-catenin were negatively associated with miR-449b-5p levels in glioblastoma cells. MiR-449b-5p inhibited Wnt/β-catenin signaling by targeting WNT2B.

CONCLUSIONS

MiR-449b-5p acts as a tumor suppressor and retards the oncogenesis of glioblastoma, which is achieved via inactivation of Wnt/β-catenin signaling by directly targeting WNT2B.

Quasifree Neutron Knockout Reaction Reveals a Small s-Orbital Component in the Borromean Nucleus ^{17}B

A kinematically complete quasifree (p,pn) experiment in inverse kinematics was performed to study the structure of the Borromean nucleus ^{17}B, which had long been considered to have a neutron halo. By analyzing the momentum distributions and exclusive cross sections, we obtained the spectroscopic factors for 1s_{1/2} and 0d_{5/2} orbitals, and a surprisingly small percentage of 9(2)% was determined for 1s_{1/2}. Our finding of such a small 1s_{1/2} component and the halo features reported in prior experiments can be explained by the deformed relativistic Hartree-Bogoliubov theory in continuum, revealing a definite but not dominant neutron halo in ^{17}B. The present work gives the smallest s- or p-orbital component among known nuclei exhibiting halo features and implies that the dominant occupation of s or p orbitals is not a prerequisite for the occurrence of a neutron halo.

Estimate hourly PM2.5 concentrations from Himawari-8 TOA reflectance directly using geo-intelligent long short-term memory network

Fine particulate matter (PM_2.5) has attracted extensive attention because of its baneful influence on human health and the environment. However, the sparse distribution of PM_2.5 measuring stations limits its application to public utility and scientific research, which can be remedied by satellite observations. Therefore, we developed a Geo-intelligent long short-term network (Geoi-LSTM) to estimate hourly ground-level PM_2.5 concentrations in 2017 in Wuhan Urban Agglomeration (WUA). We conducted contrast experiments to verify the effectiveness of our model and explored the optimal modeling strategy. It turned out that Geoi-LSTM with TOA reflectance, meteorological conditions, and NDVI as inputs performs best. The station-based cross-validation R², root mean squared error and mean absolute error are 0.82, 15.44 μg/m³, 10.63 μg/m³, respectively. Based on model results, we revealed spatiotemporal characteristics of PM_2.5 in WUA. Generally speaking, during the day, PM_2.5 concentration remained stable at a relatively high level in the morning and decreased continuously in the afternoon. While during the year, PM_2.5 concentrations were highest in winter, lowest in summer, and in-between in spring and autumn. Combined with meteorological conditions, we further analyzed the whole process of a PM_2.5 pollution event. Finally, we discussed the loss in removing clouds-covered pixels and compared our model with several popular models. Overall, our results can reflect hourly PM_2.5 concentrations seamlessly and accurately with a spatial resolution of 5 km, which benefits PM_2.5 exposure evaluations and policy regulations.