Exosomal MALAT1 promotes the proliferation of esophageal squamous cell carcinoma through glyoxalase 1-dependent methylglyoxal removal

In previous study we characterized the oncogenic role of long non-coding RNA MALAT1 in esophageal squamous cell carcinoma (ESCC), but the detailed mechanism remains obscure. Here we identified glyoxalase 1 (GLO1) as the most possible executor of MALAT1 by microarray screening. GLO1 is responsible for degradation of cytotoxic methylglyoxal (MGO), which is by-product of tumor glycolysis. Accumulated MGO may lead to glycation of DNA and protein, resulting in elevated advanced glycation end products (AGEs), while glyoxalase 1 detoxify MGO to alleviate its cytotoxic effect to tumor cells. GLO1 interfering led to accumulation of AGEs and following activation of DNA injury biomarkers, which lead to cell cycle arrest and growth inhibition. In silico analysis based on online database revealed abundant enrichment of histone acetylation marker H3K27ac in GLO1 promotor, and acetyltransferase inhibitor C646 declined GLO1 expression. Acetyltransferase KAT2B, which was also identified as a target of MALAT, mediated histone lysine acetylation of GLO1 promotor, which was confirmed by ChIP-qPCR experiment. Shared binding sites of miR-206 were found on MALAT1 and KAT2B mRNA. Dual-luciferase reporter assays confirmed interaction within MALAT1-miR-206-GLO1. Finally, we identified MALAT1 encapsuled by exosome from donor cells, and transferred malignant behaviors to recipient cells. The secreted exosomes may enter circulation, and serum MALAT1 level combined with traditional tumor markers showed potential power for ESCC diagnosis.

Iridium(III) complexes conjugated with naproxen exhibit potent anti-tumor activities by inducing mitochondrial damage, modulating inflammation, and enhancing immunity

A series of Ir(III)-naproxen (NPX) conjugates with the molecular formula [Ir(C^N)2bpy(4-CH2ONPX-4'-CH2ONPX)](PF6) (Ir-NPX-1-3) were designed and synthesized, including C^N = 2-phenylpyridine (ppy, Ir-NPX-1), 2-(2-thienyl)pyridine (thpy, Ir-NPX-2) and 2-(2,4-difluorophenyl)pyridine (dfppy, Ir-NPX-3). Cytotoxicity tests showed that Ir-NPX-1-3 exhibited excellent antitumor activity, especially in A549R cells. The cellular uptake experiment showed that the complexes were mainly localized in mitochondria, and induced apoptosis in A549R cells by damaging the structure and function of mitochondria. The main manifestations are a decrease in the mitochondrial membrane potential (MMP), an increase in reactive oxygen species (ROS) levels, and cell cycle arrest. Furthermore, Ir-NPX-1-3 could inhibit the migration and colony formation of cancer cells, demonstrating potential anti-metastatic ability. Finally, the anti-inflammatory and immunological applications of Ir-NPX-1-3 were verified. The downregulation of cyclooxygenase-2 (COX-2) and programmed death-ligand 1 (PD-L1) expression levels and the release of immunogenic cell death (ICD) related signaling molecules such as damage-associated molecular patterns (DAMPs) (cell surface calreticulin (CRT), high mobility group box 1 (HMGB1), and adenosine triphosphate (ATP)) indicate that these Ir(III) -NPX conjugates are novel ICD inducers with synergistic effects in multiple anti-tumor pathways.

Online quantification of nicotine in e-cigarette aerosols by vacuum ultraviolet photoionization mass spectrometry

The growing popularity of e-cigarettes and the associated risks of nicotine addiction present a new challenge to global public health security. Measuring the nicotine levels in e-cigarette aerosols is essential to assess the safety of e-cigarettes. In this study, a rapid in situ method was developed for online quantification of nicotine in e-cigarette aerosols by using a homemade vacuum ultraviolet photoionization aerosol mass spectrometer (VUV-AMS). E-cigarette liquids with different nicotine concentrations were prepared to generate aerosols containing different levels of nicotine, which were employed as the calibration sources for nicotine quantification by VUV-AMS. The results showed that the mass concentration of nicotine in e-cigarette aerosols has a good linear relationship with its signal intensity in the mass spectrum, and the limits of detection and quantitation of nicotine by VUV-AMS were found to be 2.0 and 6.2 μg per puff respectively. Then the online method was utilized to measure five commercial e-cigarettes, and their nicotine yields were determined to be between 31 and 188 μg per puff with the nicotine fluxes from 7.7 to 70 μg s-1, agreeing with the results of the gas chromatography with a flame ionization detector (GC-FID). This study demonstrated the feasibility and advantages of VUV-AMS for quick quantification of nicotine in e-cigarette aerosols within seconds.

mTOR signaling pathway regulation HIF-1 α effects on LPS induced intestinal mucosal epithelial model damage

BACKGROUND

Sepsis-induced small-intestinal injury is associated with increased morbidity and mortality. Our previous study and other papers have shown that HIF-1α has a protective effect on intestinal mucosal injury in septic rats. The purpose of this study is to further verify the protective effect of HIF-1α on intestinal mucosa and its molecular mechanism in vitro experiments.

METHODS

Caco-2 cells were selected and experiment was divided into 2 parts. Part I: HIF-1α activator and inhibitor were used to treat lipopolysacchrides (LPS)-stimulated Caco-2 cells respectively, to explore the effect of HIF-1α on LPS induced Caco-2 cell epithelial model; Part II: mTOR activator or inhibitor combined with or without HIF-1α activator, inhibitor to treat LPS-stimulated Caco-2 cells respectively, and then the molecular mechanism of HIF-1α reducing LPS induced Caco-2 cell epithelial model damage was detected.

RESULTS

The results showed that HIF-1α activator decreased the permeability and up regulated tight junction (TJ) expression, while HIF-1α inhibitor had the opposite effect with the HIF-1α activator. mTOR activation increased, while mTOR inhibition decreased HIF-1α protein and expression of its downstream target molecules, which can be attenuated by HIF-1α activator or inhibitor.

CONCLUSION

This study once again confirmed that HIF-1α alleviates LPS-induced mucosal epithelial model damage through P70S6K signalling pathway. It is of great value to explore whether HIF-2α plays crucial roles in the regulation of mucosal epithelial model functions in the future.

Extracorporeal membrane oxygenation technology for adults: an evidence mapping based on systematic reviews

BACKGROUND

Extracorporeal membrane oxygenation (ECMO) is a cutting-edge life-support measure for patients with severe cardiac and pulmonary illnesses. Although there are several systematic reviews (SRs) about ECMO, it remains to be seen how quality they are and how efficacy and safe the information about ECMO they describe is in these SRs. Therefore, performing an overview of available SRs concerning ECMO is crucial.

METHODS

We searched four electronic databases from inception to January 2023 to identify SRs with or without meta-analyses. The Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system were used to assess the methodological quality, and evidence quality for SRs, respectively. A bubble plot was used to visually display clinical topics, literature size, number of SRs, evidence quality, and an overall estimate of efficacy.

RESULTS

A total of 17 SRs met eligibility criteria, which were combined into 9 different clinical topics. The methodological quality of the included SRs in this mapping was "Critically low" to "Moderate". One of the SRs was high-quality evidence, three on moderate, three on low, and two on very low-quality evidence. The most prevalent study used to evaluate ECMO technology was observational or cohort study with frequently small sample sizes. ECMO has been proven beneficial for severe ARDS and ALI due to the H1N1 influenza infection. For ARDS, ALF or ACLF, and cardiac arrest were concluded to be probably beneficial. For dependent ARDS, ARF, ARF due to the H1N1 influenza pandemic, and cardiac arrest of cardiac origin came to an inconclusive conclusion. There was no evidence for a harmful association between ECMO and the range of clinical topics.

CONCLUSIONS

There is limited available evidence for ECMO that large sample, multi-center, and multinational RCTs are needed. Most clinical topics are reported as beneficial or probably beneficial of SRs for ECMO. Evidence mapping is a valuable and reliable methodology to identify and present the existing evidence about therapeutic interventions.

Prognosis Prediction of Diffuse Large B-cell Lymphoma in 18F-FDG PET images Based on Multi-Deep-Learning Models

Diffuse large B-cell lymphoma (DLBCL), a cancer of B cells, has been one of the most challenging and complicated diseases because of its considerable variation in clinical behavior, response to therapy, and prognosis. Radiomic features from medical images, such as PET images, have become one of the most valuable features for disease classification or prognosis prediction using learning-based methods. In this paper, a new flexible ensemble deep learning model is proposed for the prognosis prediction of the DLBCL in 18F-FDG PET images. This study proposes the multi-R-signature construction through selected pre-trained deep learning models for predicting progression-free survival (PFS) and overall survival (OS). The proposed method is trained and validated on two datasets from different imaging centers. Through analyzing and comparing the results, the prediction models, including Age, Ann abor stage, Bulky disease, SUVmax, TMTV, and multi-R-signature, achieve the almost best PFS prediction performance (C-index: 0.770, 95% CI: 0.705-0.834, with feature adding fusion method and C-index: 0.764, 95% CI: 0.695-0.832, with feature concatenate fusion method) and OS prediction (C-index: 0.770 (0.692-0.848) and 0.771 (0.694-0.849)) on the validation dataset. The developed multiparametric model could achieve accurate survival risk stratification of DLBCL patients. The outcomes of this study will be helpful for the early identification of high-risk DLBCL patients with refractory relapses and for guiding individualized treatment strategies.

[Research on Position Verification of Multi-Leaf Collimator (MLC) and Dose Verification Based on Electronic Portal Imaging Device]

Objective

A quality control (QC) system based on the electronic portal imaging device (EPID) system was used to realize the Multi-Leaf Collimator (MLC) position verification and dose verification functions on Primus and VenusX accelerators.

Methods

The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation. The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation. The dose data obtained by EPID and two-dimensional matrix (MapCheck/PTW) were compared with the dose calculated by Pinnacle/TiGRT TPS for γ passing rate analysis.

Results

The position error of VenusX MLC was less than 1 mm. The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID. For the dose reconstructed by EPID, the average γ passing rates of Primus were 98.86% and 91.39% under the criteria of 3%/3 mm, 10% threshold and 2%/2 mm, 10% threshold, respectively. The average γ passing rates of VenusX were 98.49% and 91.11%, respectively.

Conclusion

The EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes

The study aimed to investigate the clinical significance of the interaction between hypoxia and the immune system in esophageal squamous cell carcinoma (ESCC) microenvironment. A comprehensive evaluation of 13 hypoxia phenotype-related genes (HPRs) was conducted using data from TCGA-ESCC and two GEO cohorts. Three distinct HPRclusters were identified, and the HPRscore was established as an independent prognostic factor (p = 0.001), with higher scores indicating poorer prognosis. The HPRscore was validated in various immunotherapy cohorts, demonstrating its efficacy in evaluating immunotherapy and chemotherapy outcomes. Additionally, phenome-wide association study (PheWAS) analysis showed that PKP1 had no significant correlation with other traits at the gene level. PKP1 was identified as a potential prognostic marker for ESCC, with upregulated expression observed in ESCC patients. In vitro experiments showed that the knockdown of PKP1 inhibited ESCC cell proliferation and migration. These findings suggest that the novel HPRscore and PKP1 may serve as prognostic tools and therapeutic targets for ESCC patients.

GAN-based metal artifacts region inpainting in brain MRI imaging with reflective registration

BACKGROUND AND OBJECTIVE

Metallic magnetic resonance imaging (MRI) implants can introduce magnetic field distortions, resulting in image distortion, such as bulk shifts and signal-loss artifacts. Metal Artifacts Region Inpainting Network (MARINet), using the symmetry of brain MRI images, has been developed to generate normal MRI images in the image domain and improve image quality.

METHODS

T1-weighted MRI images containing or located near the teeth of 100 patients were collected. A total of 9000 slices were obtained after data augmentation. Then, MARINet based on U-Net with a dual-path encoder was employed to inpaint the artifacts in MRI images. The input of MARINet contains the original image and the flipped registered image, with partial convolution used concurrently. Subsequently, we compared PConv with partial convolution, and GConv with gated convolution, SDEdit using a diffusion model for inpainting the artifact region of MRI images. The mean absolute error (MAE) and peak signal-to-noise ratio (PSNR) for the mask were used to compare the results of these methods. In addition, the artifact masks of clinical MRI images were inpainted by physicians.

RESULTS

MARINet could directly and effectively inpaint the incomplete MRI images generated by masks in the image domain. For the test results of PConv, GConv, SDEdit, and MARINet, the masked MAEs were 0.1938, 0.1904, 0.1876, and 0.1834, respectively, and the masked PSNRs were 17.39, 17.40, 17.49, and 17.60 dB, respectively. The visualization results also suggest that the network can recover the tissue texture, alveolar shape, and tooth contour. Additionally, for clinical artifact MRI images, MARINet completed the artifact region inpainting task more effectively when compared with other models.

CONCLUSIONS

By leveraging the quasi-symmetry of brain MRI images, MARINet can directly and effectively inpaint the metal artifacts in MRI images in the image domain, restoring the tooth contour and detail, thereby enhancing the image quality.

A novel disulfidptosis-related prognostic gene signature and experimental validation identify ACTN4 as a novel therapeutic target in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a prevalent form of malignancy globally. Disulfidptosis is novel programmed cell death pathway based on disulfide proteins, may have a positive impact on the development of LUAD treatment strategies.

OBJECTIVE

To investigate the impact of disulfidptosis-related genes (DRGs) on the prognosis of LUAD, developed a risk model to facilitate the diagnosis and prognostication of patients. We also explored ACTN4 (DRGs) as a new therapeutic biomarker for LUAD.

METHODS

We investigated the expression patterns of DRGs in both LUAD and noncancerous tissues. To assess the prognostic value of the DRGs, we developed risk models through univariate Cox analysis and lasso regression. The expression and function of ACTN4 was evaluated by qRT-PCR, immunohistochemistry and in vitro experiments. The TIMER examined the association between ACTN4 expression and immune infiltration in LUAD.

RESULTS

Ten differentially expressed DRGs were identified. And ACTN4 was identified as potential risk factors through univariate Cox regression analysis (P< 0.05). ACTN4 expression and riskscore were used to construct a risk model to predict overall survival in LUAD, and high-risk demonstrated a significantly higher mortality rate compared to the low-risk cohort. qRT-PCR and immunohistochemistry assays indicated ACTN4 was upregulated in LUAD, and the upregulation was associated with clinicopathologic features. In vitro experiments showed the knockdown of ACTN4 expression inhibited the proliferation in LUAD cells. The TIMER analysis demonstrated a correlation between the expression of ACTN4 and the infiltration of diverse immune cells. Elevated ACTN4 expression was associated with a reduction in memory B cell count. Additionally, the ACTN4 expression was associated with m6A modification genes.

CONCLUSIONS

Our study introduced a prognostic model based on DRGs, which could forecast the prognosis of patients with LUAD. The biomarker ACTN4 exhibits promise for the diagnosis and management of LUAD, given its correlation with tumor immune infiltration and m6A modification.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer

OBJECTIVE

This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients.

METHODS

4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT.

RESULTS

The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT.

CONCLUSIONS

Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

A Lightweight Image Super-Resolution Reconstruction Algorithm Based on the Residual Feature Distillation Mechanism

In recent years, the development of image super-resolution (SR) has explored the capabilities of convolutional neural networks (CNNs). The current research tends to use deeper CNNs to improve performance. However, blindly increasing the depth of the network does not effectively enhance its performance. Moreover, as the network depth increases, more issues arise during the training process, requiring additional training techniques. In this paper, we propose a lightweight image super-resolution reconstruction algorithm (SISR-RFDM) based on the residual feature distillation mechanism (RFDM). Building upon residual blocks, we introduce spatial attention (SA) modules to provide more informative cues for recovering high-frequency details such as image edges and textures. Additionally, the output of each residual block is utilized as hierarchical features for global feature fusion (GFF), enhancing inter-layer information flow and feature reuse. Finally, all these features are fed into the reconstruction module to restore high-quality images. Experimental results demonstrate that our proposed algorithm outperforms other comparative algorithms in terms of both subjective visual effects and objective evaluation quality. The peak signal-to-noise ratio (PSNR) is improved by 0.23 dB, and the structural similarity index (SSIM) reaches 0.9607.

Magnetically driven formation of 3D freestanding soft bioscaffolds

3D soft bioscaffolds have great promise in tissue engineering, biohybrid robotics, and organ-on-a-chip engineering applications. Though emerging three-dimensional (3D) printing techniques offer versatility for assembling soft biomaterials, challenges persist in overcoming the deformation or collapse of delicate 3D structures during fabrication, especially for overhanging or thin features. This study introduces a magnet-assisted fabrication strategy that uses a magnetic field to trigger shape morphing and provide remote temporary support, enabling the straightforward creation of soft bioscaffolds with overhangs and thin-walled structures in 3D. We demonstrate the versatility and effectiveness of our strategy through the fabrication of bioscaffolds that replicate the complex 3D topology of branching vascular systems. Furthermore, we engineered hydrogel-based bioscaffolds to support biohybrid soft actuators capable of walking motion triggered by cardiomyocytes. This approach opens new possibilities for shaping hydrogel materials into complex 3D morphologies, which will further empower a broad range of biomedical applications.

A Radiographic Analysis of Coronal Morphological Parameters of Lower Limbs in Chinese Non-knee Osteoarthritis Populations

OBJECTIVES

Analyzing the lower limb coronal morphological parameters in populations without knee osteoarthritis (KOA) holds significant value in predicting, diagnosing, and formulating surgical strategies for KOA. This study aimed to comprehensively analyze the variability in these parameters among Chinese non-KOA populations, employing a substantial sample size.

METHODS

A cross-sectional retrospective analysis was performed on the Chinese non-KOA populations (n = 407; 49.9% females). The study employed an in-house developed artificial intelligence software to meticulously assess the coronal morphological parameters of all 814 lower limbs. The parameters evaluated included the hip-knee-ankle angle (HKAA), weight-bearing line ratio (WBLR), joint line convergence angle (JLCA), mechanical lateral-proximal-femoral angle (mLPFA), mechanical lateral-distal-femoral angle (mLDFA), mechanical medial-proximal-tibial angle (mMPTA), and mechanical lateral-distal-tibial angle (mLDTA). Differences in these parameters were compared between left and right limbs, different genders, and different age groups (with 50 years as the cut-off point).

RESULTS

HKAA and JLCA exhibited left-right differences (left vs. right: 178.2° ± 3.0° vs. 178.6° ± 2.9° for HKAA, p = 0.001; and 1.8° ± 1.5° vs. 1.4° ± 1.6° for JLCA, p < 0.001); except for the mLPFA, all other parameters show gender-related differences (male vs. female: 177.9° ± 2.8° vs. 179.0° ± 3.0° for HKAA, p < 0.001; 1.5° ± 1.5° vs. 1.8° ± 1.7° for JLCA, p = 0.003; 87.1° ± 2.1° vs. 88.1° ± 2.1° for mMPTA, p < 0.001; 90.2° ± 4.0° vs. 91.1° ± 3.2° for mLDTA, p < 0.001; 38.7% ± 12.9% vs. 43.6% ± 14.1% for WBLR, p < 0.001; and 87.7° ± 2.3° vs. 87.4° ± 2.7° for mLDTA, p = 0.045); mLPFA increase with age (younger vs. older: 90.1° ± 7.2° vs. 93.4° ± 4.9° for mLPFA, p < 0.001), while no statistical difference exists for other parameters.

CONCLUSIONS

There were differences in lower limb coronal morphological parameters among Chinese non-KOA populations between left and right sides, different genders, and age.

Toward a low carbon path: Do E-commerce reduce CO2 emissions? Evidence from China

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality.

General Analysis of Heat Shock Factors in the Cymbidium ensifolium Genome Provided Insights into Their Evolution and Special Roles with Response to Temperature

Heat shock factors (HSFs) are the key regulators of heat stress responses and play pivotal roles in tissue development and the temperature-induced regulation of secondary metabolites. In order to elucidate the roles of HSFs in Cymbidium ensifolium, we conducted a genome-wide identification of CeHSF genes and predicted their functions based on their structural features and splicing patterns. Our results revealed 22 HSF family members, with each gene containing more than one intron. According to phylogenetic analysis, 59.1% of HSFs were grouped into the A subfamily, while subfamily HSFC contained only two HSFs. And the HSF gene families were differentiated evolutionarily between plant species. Two tandem repeats were found on Chr02, and two segmental duplication pairs were observed on Chr12, Chr17, and Chr19; this provided evidence for whole-genome duplication (WGD) events in C. ensifolium. The core region of the promoter in most CeHSF genes contained cis-acting elements such as AP2/ERF and bHLH, which were associated with plant growth, development, and stress responses. Except for CeHSF11, 14, and 19, each of the remaining CeHSFs contained at least one miRNA binding site. This included binding sites for miR156, miR393, and miR319, which were responsive to temperature and other stresses. The HSF gene family exhibited significant tissue specificity in both vegetative and floral organs of C. ensifolium. CeHSF13 and CeHSF15 showed relatively significant expression in flowers compared to other genes. During flower development, CeHSF15 exhibited markedly elevated expression in the early stages of flower opening, implicating critical regulatory functions in organ development and floral scent-related regulations. During the poikilothermic treatment, CeHSF14 was upregulated over 200-fold after 6 h of heat treatment. CeHSF13 and CeHSF14 showed the highest expression at 6 h of low temperature, while the expression of CeHSF15 and CeHSF21 continuously decreased at a low temperature. The expression patterns of CeHSFs further confirmed their role in responding to temperature stress. Our study may help reveal the important roles of HSFs in plant development and metabolic regulation and show insight for the further molecular design breeding of C. ensifolium.

Efficient Defect Detection of Rotating Goods under the Background of Intelligent Retail

Dynamic visual vending machines are rapidly growing in popularity, offering convenience and speed to customers. However, there is a prevalent issue with consumers damaging goods and then returning them to the machine, severely affecting business interests. This paper addresses the issue from the standpoint of defect detection. Although existing industrial defect detection algorithms, such as PatchCore, perform well, they face challenges, including handling goods in various orientations, detection speeds that do not meet real-time monitoring requirements, and complex backgrounds that hinder detection accuracy. These challenges hinder their application in dynamic vending environments. It is crucial to note that efficient visual features play a vital role in memory banks, yet current memory repositories for industrial inspection algorithms do not adequately address the problem of location-specific feature redundancy. To tackle these issues, this paper introduces a novel defect detection algorithm for goods using adaptive subsampling and partitioned memory banks. Firstly, Grad-CAM is utilized to extract deep features, which, in combination with shallow features, mitigate the impact of complex backgrounds on detection accuracy. Next, graph convolutional networks extract rotationally invariant features. The adaptive subsampling partitioned memory bank is then employed to store features of non-defective goods, which reduces memory consumption and enhances training speed. Experimental results on the MVTec AD dataset demonstrate that the proposed algorithm achieves a marked improvement in detection speed while maintaining accuracy that is comparable to state-of-the-art models.

Remote Photoplethysmography and Motion Tracking Convolutional Neural Network with Bidirectional Long Short-Term Memory: Non-Invasive Fatigue Detection Method Based on Multi-Modal Fusion

Existing vision-based fatigue detection methods commonly utilize RGB cameras to extract facial and physiological features for monitoring driver fatigue. These features often include single indicators such as eyelid movement, yawning frequency, and heart rate. However, the accuracy of RGB cameras can be affected by factors like varying lighting conditions and motion. To address these challenges, we propose a non-invasive method for multi-modal fusion fatigue detection called RPPMT-CNN-BiLSTM. This method incorporates a feature extraction enhancement module based on the improved Pan-Tompkins algorithm and 1D-MTCNN. This enhances the accuracy of heart rate signal extraction and eyelid features. Furthermore, we use one-dimensional neural networks to construct two models based on heart rate and PERCLOS values, forming a fatigue detection model. To enhance the robustness and accuracy of fatigue detection, the trained model data results are input into the BiLSTM network. This generates a time-fitting relationship between the data extracted from the CNN, allowing for effective dynamic modeling and achieving multi-modal fusion fatigue detection. Numerous experiments validate the effectiveness of the proposed method, achieving an accuracy of 98.2% on the self-made MDAD (Multi-Modal Driver Alertness Dataset). This underscores the feasibility of the algorithm. In comparison with traditional methods, our approach demonstrates higher accuracy and positively contributes to maintaining traffic safety, thereby advancing the field of smart transportation.

Investigation of the Alternations in Lipid Oxidation and Lipase Activity in Air-Dried Hairtail (Trichiurus lepturus) during Chilled Storage

The effects of water content and water activity on the lipid stability of air-dried hairtail (Trichiurus haumela) were investigated during chilled storage. Air-dried hairtail samples with high and low water contents were comparatively analyzed over 8 days of storage at 4 °C. The results indicated that the decreases in water activity and increases in the NaCl content significantly inhibited lipid oxidation in the air-dried hairtail samples. The peroxidation value (PV), conjugated diene value (CD), thiobarbituric acid reactive substance (TBARS) value, and p-anisidine value (p-AnV) of the air-dried hairtail significantly increased with the extension of storage time. The low water content significantly inhibited the activity of neutral and alkaline lipase, in addition to lipoxygenase, and retarded the rapid increases in the non-esterified fatty acid (NEFA) content in the hairtail samples. The correlation analysis results showed that the TBARS, p-AnV, and lipase activity were positively correlated in the air-dried hairtail samples, and the lower water content significantly inhibited the progress of lipid oxidation. This study offers a theoretical framework for the industrial processing and storage of air-dried hairtail products.

A Comprehensive Analysis of Auxin Response Factor Gene Family in Melastoma dodecandrum Genome

Auxin Response Factors (ARFs) mediate auxin signaling and govern diverse biological processes. However, a comprehensive analysis of the ARF gene family and identification of their key regulatory functions have not been conducted in Melastoma dodecandrum, leading to a weak understanding of further use and development for this functional shrub. In this study, we successfully identified a total of 27 members of the ARF gene family in M. dodecandrum and classified them into Class I-III. Class II-III showed more significant gene duplication than Class I, especially for MedARF16s. According to the prediction of cis-regulatory elements, the AP2/ERF, BHLH, and bZIP transcription factor families may serve as regulatory factors controlling the transcriptional pre-initiation expression of MedARF. Analysis of miRNA editing sites reveals that miR160 may play a regulatory role in the post-transcriptional expression of MeARF. Expression profiles revealed that more than half of the MedARFs exhibited high expression levels in the stem compared to other organs. While there are some specific genes expressed only in flowers, it is noteworthy that MedARF16s, MedARF7A, and MedARF9B, which are highly expressed in stems, also demonstrate high expressions in other organs of M. dodecandrum. Further hormone treatment experiments revealed that these MedARFs were sensitive to auxin changes, with MedARF6C and MedARF7A showing significant and rapid changes in expression upon increasing exogenous auxin. In brief, our findings suggest a crucial role in regulating plant growth and development in M. dodecandrum by responding to changes in auxin. These results can provide a theoretical basis for future molecular breeding in Myrtaceae.

The Genome-Level Survey of the WOX Gene Family in Melastoma dodecandrum Lour

Though conserved in higher plants, the WOX transcription factors play crucial roles in plant growth and development of Melastoma dodecandrum Lour., which shows pioneer position in land ecosystem formation and produces nutritional fruits. Identifying the WOX family genes in M. dodecandrum is imperative for elucidating its growth and development mechanisms. However, the WOX genes in M. dodecandrum have not yet been characterized. In this study, by identification 22 WOX genes in M. dodecandrum based on current genome data, we classified family genes into three clades and nine types with homeodomains. We highlighted gene duplications of MedWOX4, which offered evidences of whole-genome duplication events. Promoter analysis illustrated that cis-regulatory elements related to light and stress responses and plant growth were enriched. Expression pattern and RT-qPCR results demonstrated that the majority of WOX genes exhibited expression in the stem. MedWOX13s displayed highest expression across various tissues. MedWOX4s displayed a specific expression in the stem. Collectively, our study provided foundations for elucidating WOX gene functions and further molecular design breeding in M. dodecandrum.

A Combined Model Integrating Radiomics and Deep Learning Based on Contrast-Enhanced CT for Preoperative Staging of Laryngeal Carcinoma

RATIONALE AND OBJECTIVES

Accurate staging of laryngeal carcinoma can inform appropriate treatment decision-making. We developed a radiomics model, a deep learning (DL) model, and a combined model (incorporating radiomics features and DL features) based on the venous-phase CT images and explored the performance of these models in stratifying patients with laryngeal carcinoma into stage I-II and stage III-IV, and also compared these models with radiologists.

MATERIALS AND METHODS

Three hundreds and nineteen patients with pathologically confirmed laryngeal carcinoma were randomly divided into a training set (n = 223) and a test set (n = 96). In the training set, the radiomics features with inter- and intraclass correlation coefficients (ICCs)> 0.75 were screened by Spearman correlation analysis and recursive feature elimination (RFE); then support vector machine (SVM) classifier was applied to develop the radiomics model. The DL model was built using ResNet 18 by the cropped 2D regions of interest (ROIs) in the maximum tumor ROI slices and the last fully connected layer of this network served as the DL feature extractor. Finally, a combined model was developed by pooling the radiomics features and extracted DL features to predict the staging.

RESULTS

The area under the curves (AUCs) for radiomics model, DL model, and combined model in the test set were 0.704 (95% confidence interval [CI]: 0.588-0.820), 0.724 (95% CI: 0.613-0.835), and 0.849 (95% CI: 0.755-0.943), respectively. The combined model outperformed the radiomics model and the DL model in discriminating stage I-II from stage III-IV (p = 0.031 and p = 0.020, respectively). Only the combined model performed significantly better than radiologists (p < 0.050 for both).

CONCLUSION

The combined model can help tailor the therapeutic strategy for laryngeal carcinoma patients by enabling more accurate preoperative staging.

Bioinformatic Assessment and Expression Profiles of the AP2/ERF Superfamily in the Melastoma dodecandrum Genome

AP2/ERF transcription factors play crucial roles in various biological activities, including plant growth, development, and responses to biotic and abiotic stressors. However, limited research has been conducted on the AP2/ERF genes of Melastoma dodecandrum for breeding of this potential fruit crop. Leveraging the recently published whole genome sequence, we conducted a comprehensive assessment of this superfamily and explored the expression patterns of AP2/ERF genes at a genome-wide level. A significant number of genes, totaling 218, were discovered to possess the AP2 domain sequence and displayed notable structural variations among five subfamilies. An uneven distribution of these genes was observed on 12 pseudochromosomes as the result of gene expansion facilitated by segmental duplications. Analysis of cis-acting elements within promoter sites and 87.6% miRNA splicing genes predicted their involvement in multiple hormone responses and abiotic stresses through transcriptional and post-transcriptional regulations. Transcriptome analysis combined with qRT-PCR results indicated that certain candidate genes are involved in tissue formation and the response to developmental changes induced by IAA hormones. Overall, our study provides valuable insights into the evolution of ERF genes in angiosperms and lays a solid foundation for future breeding investigations aimed at improving fruit quality and enhancing adaptation to barren land environments.

Compression properties and constitutive model of short glass fiber reinforced poly-ether-ether-ketone (PEEK)

To analyze the deformation behavior of short glass fiber-reinforced poly-ether-ether-ketone (SGFR-PEEK) under various conditions through numerical simulations, it is crucial to construct a constitutive model that can describe its stress-strain behavior over a wide range of strain rates and temperatures. In this study, quasi-static compression tests were conducted on SGFR-PEEK composites with varying mass fractions, and dynamic tests were performed using a Split Hopkinson Pressure Bar to acquire the material's compressive stress-strain response under quasi-static and dynamic conditions. The results indicate that, under compression, the yield stress of SGFR-PEEK composites increases with an augmentation in glass fiber content, rises with increasing strain rate, and decreases with elevated temperature. Based on experimental findings, a modified Johnson-Cook constitutive model was established to characterize the mechanical performance of SGFR-PEEK. In comparison to the traditional Johnson-Cook intrinsic structure model, the modified model takes into account the glass fiber mass fraction as comprehensively as possible and better predicts the material's flow behavior at high strain rates. Finally, this modified constitutive model was implemented in the ABAQUS software using the user-defined subroutine VUMAT to simulate the compression behavior of SGFR-PEEK composites under different loading conditions, and the model was validated. This research provides valuable insights for the practical application of SGFR-PEEK composites in engineering.

Multi-omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma

BACKGROUND

Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ).

METHODS

Primary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed.

RESULTS

WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion.

CONCLUSIONS

This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.

Multiple Facial Basal Cell Carcinoma With Xeroderma Pigmentosum

Multiple basal cell carcinomas are rare in children and adolescents. Xeroderma pigmentosum (XP) is a rare autosomal recessive hereditary disease characterized by photosensitivity, changes in skin pigmentation, and early onset of skin cancer. XP is extremely rare in clinical practice, with only a few cases worldwide. XP is clinically incurable. The main goal of treating this disease is to diagnose as early as possible, educate patients to strictly avoid ultraviolet radiation for life, and follow up regularly to treat skin malignant tumors in time. The authors report a 15-year-old boy with facial multiple basal cell carcinoma with XP. Its medical history, clinical features, auxiliary examination, and surgical treatment process have great reference value for the in-depth understanding of the disease. The authors will discuss how to delay the progression of the disease and treat the existing lesions in different clinical stages of the disease in combination with the existing relevant literature.

A transformer-based dual-domain network for reconstructing FOV extended cone-beam CT images from truncated sinograms in radiation therapy

BACKGROUND AND OBJECTIVE

Cone-beam computed tomography (CBCT) is widely used in clinical radiotherapy, but its small field of view (sFOV) limits its application potential. In this study, a transformer-based dual-domain network (dual_swin), which combined image domain restoration and sinogram domain restoration, was proposed for the reconstruction of complete CBCT images with extended FOV from truncated sinograms.

METHODS

The planning CT images with large FOV (LFOV) of 330 patients who received radiation therapy were collected. The synthetic CBCT (sCBCT) images with LFOV were generated from CT images by the trained cycleGAN network, and CBCT images with sFOV were obtained through forward projection, projection truncation, and filtered back projection (FBP), comprising the training and test data. The proposed dual_swin includes sinogram domain restoration, image domain restoration, and FBP layer, and the swin transformer blocks were used as the basic feature extraction module in the network to improve the global feature extraction ability. The proposed dual_swin was compared with the image domain method, the sinogram domain method, the U-Net based dual domain network (dual_Unet), and the traditional iterative reconstruction method based on prior image and conjugate gradient least-squares (CGLS) in the test of sCBCT images and clinical CBCT images. The HU accuracy and body contour accuracy of the predicted images by each method were evaluated.

RESULTS

The images generated using the CGLS method were fuzzy and obtained the lowest structural similarity (SSIM) among all methods in the test of sCBCT and clinical CBCT images. The predicted images by the image domain methods are quite different from the ground truth and have low accuracy on HU value and body contour. In comparison with image domain methods, sinogram domain methods improved the accuracy of HU value and body contour but introduced secondary artifacts and distorted bone tissue. The proposed dual_swin achieved the highest HU and contour accuracy with mean absolute error (MAE) of 23.0 HU, SSIM of 95.7%, dice similarity coefficient (DSC) of 99.6%, and Hausdorff distance (HD) of 4.1 mm in the test of sCBCT images. In the test of clinical patients, images that were predicted by dual_swin yielded MAE, SSIM, DSC, and HD of 38.2 HU, 91.7%, 99.0%, and 5.4 mm, respectively. The predicted images by the proposed dual_swin has significantly higher accuracy than the other methods (P < 0.05).

CONCLUSIONS

The proposed dual_swin can accurately reconstruct FOV extended CBCT images from the truncated sinogram to improve the application potential of CBCT images in radiotherapy.

Transversus abdominis plane block vs quadratus lumborum block for postoperative analgesia in inguinal hernia repair: A systematic review and meta-analysis

PURPOSE

The present review was designed to differentiate between the analgesic value of transversus abdominis plane block (TAP) vs the quadratus lumborum block (QLB) for patients undergoing inguinal hernia surgery.

METHODS

PubMed, CENTRAL, Scopus, Embase, Google Scholar, Open gray, and a clinical trial registry were searched up to 18th February 2023 for randomized controlled trials (RCTs) comparing TAP and QLB for inguinal hernia repair.

RESULTS

Six RCTs from India, Turkey, and Norway published between the years 2019 to 2023 were included. Anesthetic agents and dosages were similar for TAP and QLB groups in each study. On meta-analysis, pain scores were not statistically significant different between TAP and QLB at 3-6 h (MD: 0.46 95% CI: -0.11, 1.03 I2 = 86%), 12 h (MD: 1.34 95% CI: -0.12, 2.80 I2 = 97%), and 24 h (MD: 0.38 95% CI: -0.77, 1.53 I2 = 97%). Meta-analysis of total analgesic consumption showed a tendency of reduced analgesic consumption with QLB as compared to TAP but the difference was not significant (SMD: 0.69 95% CI: 0.00, 1.37 I2 = 83%). Data on complications was scarcely available. GRADE assessment of the evidence was low to moderate.

CONCLUSION

Low to moderate-quality preliminary evidence suggests no difference in the analgesic efficacy of TAP and QLB for adult patients undergoing inguinal hernia repair. While there was a tendency for lower postoperative analgesic consumption with QLB, it needs to be verified by future studies.

Cell-free fat extract-loaded microneedles attenuate inflammation-induced apoptosis and mitochondrial damage in tendinopathy

Existing clinical treatments for tendinopathy mainly focus on reducing pain, whereas inhibiting or reversing disease progression remains challenging. Local therapeutic drugs, such as glucocorticoids, cause adverse effects on the metabolism of tendon tissues and injection-related complications. Therefore, new administration modalities for tendinopathy need to be developed. In this study, we designed a hydrogel-based microneedle (MN) system for the long-term transdermal delivery of our novel biological cell-free fat extract (CEFFE) to treat tendinopathies. We found that CEFFE-loaded MNs (CEFFE-MNs) had good biosafety and inhibited lipopolysaccharide (LPS)-induced apoptosis and matrix degradation in Achilles tendon cells of rats. The Achilles tendons of rats returned to their maximum mechanical strength after applying CEFFE-MNs. The administration of CEFFE-MNs had better anti-apoptosis and tendon repair-promoting effects than CEFEF injections in vivo. Transcriptome sequencing indicated that the anti-apoptosis effect of CEFFE-MNs was highly related to tumor necrosis factor (TNF) signaling. CEFFE-MNs inhibited the expression of TNF, TNF receptor 1, and downstream nuclear factor-kappa B signaling. Additionally, CEFFE-MNs rescued LPS-induced mitochondrial dynamics in tendon cells via the TNF-Drp1 axis. Our study reports a novel CEFFE-MN system that exhibits long-term anti-inflammatory and anti-apoptotic effects, suggesting it as a new treatment route for tendinopathy with broad clinical translation prospects.

Efficacy and safety of traditional Chinese medicine adjuvant therapy for severe pneumonia: evidence mapping of the randomized controlled trials, systematic reviews, and meta-analyses

Background and Objective: Severe pneumonia is a critical respiratory disease with high mortality. There is insufficient evidence on the efficacy and safety of traditional Chinese medicine (TCM) adjuvant therapy for severe pneumonia. This study aims to identify, describe, assess, and summarize the currently available high-quality design evidence on TCM adjuvant therapy for severe pneumonia to identify evidence gaps using the evidence mapping approach. Methods: Systematic searches were performed on English and Chinese online databases (PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, WanFang Data, CQVIP, and SinoMed) to identify papers from inception until August 2023 for inclusion into the review. Randomized controlled trials (RCTs), systematic reviews (SRs), and meta-analyses concerning TCM adjuvant therapy for severe pneumonia or its complications in adults were included. The risk of bias in RCTs was evaluated by using the Cochrane Handbook ROB tool. The Assessment of Multiple Systematic Reviews 2 (AMSTAR-2), the Risk of Bias in Systematic Review (ROBIS) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system were used to assess the methodological quality, risk of bias, and evidence quality of SRs or meta-analyses, respectively. Then, a bubble plot was designed to visually display information in four dimensions. Results: A total of 354 RCTs and 17 SRs or meta-analyses met the inclusion criteria. The published RCTs had several flaws, such as unreasonable design, limited sample size, insufficient attention to non-drug therapy studies and syndrome differentiation, improper selection or use of outcome indicators, and failure to provide high-quality evidence. Sixteen SRs or meta-analyses of methodological quality scored "Critically Low" confidence. Twelve SRs or meta-analyses were rated as "High Risk." Most outcomes were rated as "Low" evidence quality. We found that TCM combined with conventional treatment could improve the clinical total effective rate and the TCM syndromes efficacy. The combined approach could also shorten mechanical ventilation time, infection control time, and length of hospital and ICU stay; significantly reduce temperature, respiratory rate, heart rate, white blood cell counts, levels of C-reactive protein, procalcitonin, blood inflammatory factors, bacteriological response, and D-dimer; decrease CPIS, APACHE II score, and PSI score; improve pulmonary imaging features, arterial blood gas indicators (including arterial oxygen pressure, arterial oxygen saturation, and oxygen index), and lung function (including forced vital capacity and forced expiratory volume in the first second) for severe pneumonia compared with conventional treatment only (p < 0.05). There was no significant difference in adverse reactions and incidence of adverse events (p > 0.05). In addition, compared with conventional treatment only, most SRs or meta-analyses concluded that TCM combined with conventional treatment was "Beneficial" or "Probably beneficial." Conclusion: TCM combined with conventional treatment had advantages in efficacy, clinical signs, laboratory results, and life quality outcomes of severe pneumonia, with no difference in safety outcomes compared with conventional treatment only. QingJin Huatan decoction is the most promising target, and Xuanbai Chengqi decoction has a "Probably beneficial" conclusion. XueBiJing injection and TanReQing injection are two commonly used Chinese herbal injections for treating severe pneumonia, and both are "Probably beneficial." However, there was a need for multicenter RCTs with large sample sizes and high methodological quality in the future. In addition, the methodological design and quality of SRs or meta-analyses should be improved to form high-quality, evidence-based medical evidence and provide evidence for the effectiveness and safety of TCM adjuvant therapy for severe pneumonia.

Sanguinarine Improves Intestinal Health in Grass Carp Fed High-Fat Diets: Involvement of Antioxidant, Physical and Immune Barrier, and Intestinal Microbiota

An eight-week trial was conducted to investigate the effects of sanguinarine supplementation (600 μg and 1200 μg/kg) in high-fat (crude fat: 10%) diets (HF) on the intestinal physiological function of Ctenopharyngodon idellus (initial weight 50.21 ± 0.68 g), based on a basic diet (5% crude fat, CON), which were named HFLS and HFHS, respectively. The results showed that the HF diet significantly impaired the intestinal immune and physical barrier function, and disrupted the balance of the intestinal microbiota in grass carp. Compared to the HF diet, sanguinarine supplementation significantly improved the levels of serum C4, C3, AKP, IgA, and IgM, and enhanced the intestinal antioxidant capacity (gr, CuZnsod, gpx4, cat, gsto, and nrf2 expression were significantly up-regulated). Sanguinarine significantly down-regulated the expression of claudin-15 and up-regulated the expression of claudin-b, claudin-c, occludin, and zo-1 by inhibiting MLCK signaling molecules. Additionally, sanguinarine significantly down-regulated the expression of il-6, il-1β, and tnf-α and up-regulated the expression of il-10, tgf-β2, and tgf-β1 by inhibiting NF-κB signaling molecules, thereby alleviating intestinal inflammation caused by HF diets. Furthermore, compared to the HF diet, the abundance of Fusobacterium and Cetobacterium in the HFHS diet increased significantly, while the abundance of Firmicutes and Streptococcus showed the opposite trend. In conclusion, the HF diet had a negative impact on grass carp, while sanguinarine supplementation enhanced intestinal antioxidant ability, alleviated intestinal barrier damage, and ameliorated the homeostasis of the intestinal microbiota.

3D-printed biodegradable magnesium alloy scaffolds with zoledronic acid-loaded ceramic composite coating promote osteoporotic bone defect repair

Osteoporotic fracture is one of the most serious complications of osteoporosis. Most fracture sites have bone defects, and restoring the balance between local osteogenesis and bone destruction is difficult during the repair of osteoporotic bone defects. In this study, we successfully fabricated three-dimensional (3D)-printed biodegradable magnesium alloy (Mg-Nd-Zn-Zr) scaffolds and prepared a zoledronic acid-loaded ceramic composite coating on the surface of the scaffolds. The osteogenic effect of Mg and the osteoclast inhibition effect of zoledronic acid were combined to promote osteoporotic bone defect repair. In vitro degradation and drug release experiments showed that the coating significantly reduced the degradation rate of 3D-printed Mg alloy scaffolds and achieved a slow release of loaded drugs. The degradation products of drug-loaded coating scaffolds can promote osteogenic differentiation of bone marrow mesenchymal stem cells as well as inhibit the formation of osteoclasts and the bone resorption by regulating the expression of related genes. Compared with the uncoated scaffolds, the drug-coated scaffolds degraded at a slower rate, and more new bone grew into these scaffolds. The healing rate and quality of the osteoporotic bone defects significantly improved in the drug-coated scaffold group. This study provides a new method for theoretical research and clinical treatment using functional materials for repairing osteoporotic bone defects.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO₂ showed the highest decrease ratio of -49.5%, while the relative fraction of NO₃^- in PM_2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM_2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC _lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) _lock/pre (1.01-1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO₃^- and SO₄^2- during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

A Torsion-Bending Antagonistic Bistable Actuator Enables Untethered Crawling and Swimming of Miniature Robots

Miniature robots show great potential in exploring narrow and confined spaces to perform various tasks, but many applications are limited by the dependence of these robots on electrical or pneumatic tethers to power supplies outboard. Developing an onboard actuator that is small in size and powerful enough to carry all the components onboard is a major challenge to eliminate the need for a tether. Bistability can trigger a dramatic energy release during switching between the 2 stable states, thus providing a promising way to overcome the intrinsic limitation of insufficient power of small actuators. In this work, the antagonistic action between torsional deflection and bending deflection in a lamina emergent torsional joint is utilized to achieve bistability, yielding a buckling-free bistable design. The unique configuration of this bistable design enables integrating of a single bending electroactive artificial muscle in the structure to form a compact, self-switching bistable actuator. A low-voltage ionic polymer-metal composites artificial muscle is employed, yielding a bistable actuator capable of generating an instantaneous angular velocity exceeding 300 °/s by a 3.75-V voltage. Two untethered robotic demonstrations using the bistable actuator are presented, including a crawling robot (gross weight of 2.7 g, including actuator, battery, and on-board circuit) that can generate a maximum instantaneous velocity of 40 mm/s and a swimming robot equipped with a pair of origami-inspired paddles that swims breaststroke. The low-voltage bistable actuator shows potential for achieving autonomous motion of various fully untethered miniature robots.

New technique and application of truncated CBCT processing in adaptive radiotherapy for breast cancer

OBJECTIVE

A generative adversarial network (TCBCTNet) was proposed to generate synthetic computed tomography (sCT) from truncated low-dose cone-beam computed tomography (CBCT) and planning CT (pCT). The sCT was applied to the dose calculation of radiotherapy for patients with breast cancer.

METHODS

The low-dose CBCT and pCT images of 80 female thoracic patients were used for training. The CBCT, pCT, and replanning CT (rCT) images of 20 thoracic patients and 20 patients with breast cancer were used for testing. All patients were fixed in the same posture with a vacuum pad. The CBCT images were scanned under the Fast Chest M20 protocol with a 50% reduction in projection frames compared with the standard Chest M20 protocol. Rigid registration was performed between pCT and CBCT, and deformation registration was performed between rCT and CBCT. In the training stage of the TCBCTNet, truncated CBCT images obtained from complete CBCT images by simulation were used. The input of the CBCT→CT generator was truncated CBCT and pCT, and TCBCTNet was applied to patients with breast cancer after training. The accuracy of the sCT was evaluated by anatomy and dosimetry and compared with the generative adversarial network with UNet and ResNet as the generators (named as UnetGAN, ResGAN).

RESULTS

The three models could improve the image quality of CBCT and reduce the scattering artifacts while preserving the anatomical geometry of CBCT. For the chest test set, TCBCTNet achieved the best mean absolute error (MAE, 21.18±3.76 HU), better than 23.06±3.90 HU in UnetGAN and 22.47±3.57 HU in ResGAN. When applied to patients with breast cancer, TCBCTNet performance decreased, and MAE was 25.34±6.09 HU. Compared with rCT, sCT by TCBCTNet showed consistent dose distribution and subtle absolute dose differences between the target and the organ at risk. The 3D gamma pass rates were 98.98%±0.64% and 99.69%±0.22% at 2 mm/2% and 3 mm/3%, respectively. Ablation experiments confirmed that pCT and content loss played important roles in TCBCTNet.

CONCLUSIONS

High-quality sCT images could be synthesized from truncated low-dose CBCT and pCT by using the proposed TCBCTNet model. In addition, sCT could be used to accurately calculate the dose distribution for patients with breast cancer.

Synthesis, Characterization, and Antitumor Mechanism Investigation of Ruthenium(II)/Rhenium(I)-Daminozide Conjugates

Daminozide, a plant growth regulator, is an effective inhibitor of the Jumonji domain-containing protein (JMJD) histone demethylase. Herein, four ruthenium(II)/rhenium(I)-daminozide conjugates, with molecular formulas [Ru(N-N)2bpy(4-CH2OH-4′-CH2O-daminozide)](PF6)2 (Ru-1/Ru-2) (N-N = 1,10-phenanthroline (phen, in Ru-1) and 4,7-diphenyl-1,10-phenanthroline (DIP, in Ru-2)) and Re(N-N)(CO)3(PyCH2O-daminozide) (Re-1/Re-2) (Py = pyridine, N-N = phen (in Re-1) and DIP (in Re-2)), were synthesized and characterized. Among these complexes, Ru-2 and Re-2 exhibited higher cytotoxicity against tumor cells than cisplatin. Upregulation of H3K9Me3 expression level was found in human cervical cancer cells (HeLa) treated with Ru-2 and Re-2, indicating that these two complexes can inhibit the activity of JMJD histone demethylase. Further investigation revealed that Re-2 can selectively accumulate in the mitochondria of HeLa cells. Both Ru-2 and Re-2 can cause mitochondrial damage, induce apoptosis, and inhibit cell migration and colony formation of HeLa cells. Overall, these complexes exhibit multiple anticancer functions, including inhibiting JMJD, inducing apoptosis, and inhibiting cell invasion, making them promising candidates for anticancer drugs.

Recognition of Occluded Goods under Prior Inference Based on Generative Adversarial Network

Aiming at the recognition of intelligent retail dynamic visual container goods, two problems that lead to low recognition accuracy must be addressed; one is the lack of goods features caused by the occlusion of the hand, and the other is the high similarity of goods. Therefore, this study proposes an approach for occluding goods recognition based on a generative adversarial network combined with prior inference to address the two abovementioned problems. With DarkNet53 as the backbone network, semantic segmentation is used to locate the occluded part in the feature extraction network, and simultaneously, the YOLOX decoupling head is used to obtain the detection frame. Subsequently, a generative adversarial network under prior inference is used to restore and expand the features of the occluded parts, and a multi-scale spatial attention and effective channel attention weighted attention mechanism module is proposed to select fine-grained features of goods. Finally, a metric learning method based on von Mises-Fisher distribution is proposed to increase the class spacing of features to achieve the effect of feature distinction, whilst the distinguished features are utilized to recognize goods at a fine-grained level. The experimental data used in this study were all obtained from the self-made smart retail container dataset, which contains a total of 12 types of goods used for recognition and includes four couples of similar goods. Experimental results reveal that the peak signal-to-noise ratio and structural similarity under improved prior inference are 0.7743 and 0.0183 higher than those of the other models, respectively. Compared with other optimal models, mAP improves the recognition accuracy by 1.2% and the recognition accuracy by 2.82%. This study solves two problems: one is the occlusion caused by hands, and the other is the high similarity of goods, thus meeting the requirements of commodity recognition accuracy in the field of intelligent retail and exhibiting good application prospects.

Inpainting truncated areas of CT images based on generative adversarial networks with gated convolution for radiotherapy

This study aimed to inpaint the truncated areas of CT images by using generative adversarial networks with gated convolution (GatedConv) and apply these images to dose calculations in radiotherapy. CT images were collected from 100 patients with esophageal cancer under thermoplastic membrane placement, and 85 cases were used for training based on randomly generated circle masks. In the prediction stage, 15 cases of data were used to evaluate the accuracy of the inpainted CT in anatomy and dosimetry based on the mask with a truncated volume covering 40% of the arm volume, and they were compared with the inpainted CT synthesized by U-Net, pix2pix, and PConv with partial convolution. The results showed that GatedConv could directly and effectively inpaint incomplete CT images in the image domain. For the results of U-Net, pix2pix, PConv, and GatedConv, the mean absolute errors for the truncated tissue were 195.54, 196.20, 190.40, and 158.45 HU, respectively. The mean dose of the planning target volume, heart, and lung in the truncated CT was statistically different (p < 0.05) from those of the ground truth CT ([Formula: see text]). The differences in dose distribution between the inpainted CT obtained by the four models and [Formula: see text] were minimal. The inpainting effect of clinical truncated CT images based on GatedConv showed better stability compared with the other models. GatedConv can effectively inpaint the truncated areas with high image quality, and it is closer to [Formula: see text] in terms of image visualization and dosimetry than other inpainting models.

Detection of Occluded Small Commodities Based on Feature Enhancement under Super-Resolution

As small commodity features are often few in number and easily occluded by hands, the overall detection accuracy is low, and small commodity detection is still a great challenge. Therefore, in this study, a new algorithm for occlusion detection is proposed. Firstly, a super-resolution algorithm with an outline feature extraction module is used to process the input video frames to restore high-frequency details, such as the contours and textures of the commodities. Next, residual dense networks are used for feature extraction, and the network is guided to extract commodity feature information under the effects of an attention mechanism. As small commodity features are easily ignored by the network, a new local adaptive feature enhancement module is designed to enhance the regional commodity features in the shallow feature map to enhance the expression of the small commodity feature information. Finally, a small commodity detection box is generated through the regional regression network to complete the small commodity detection task. Compared to RetinaNet, the F1-score improved by 2.6%, and the mean average precision improved by 2.45%. The experimental results reveal that the proposed method can effectively enhance the expressions of the salient features of small commodities and further improve the detection accuracy for small commodities.

Streaking artifact reduction for CBCT-based synthetic CT generation in adaptive radiotherapy

BACKGROUND

Cone-beam computed tomography (CBCT) is widely used for daily image guidance in radiation therapy, enhancing the reproducibility of patient setup. However, its application in adaptive radiotherapy (ART) is limited by many imaging artifacts and inaccurate Hounsfield units (HUs). The correction of CBCT image is necessary and of great value for CBCT-based ART.

PURPOSE

To explore the synthetic CT (sCT) generation from CBCT images of thorax and abdomen patients, which usually surfer from serious artifacts duo to organ state changes. In this study, a streaking artifact reduction network (SARN) is proposed to reduce artifacts and combine with cycleGAN to generate high-quality sCT images from CBCT and achieve an accurate dose calculation.

METHODS

The proposed SARN was trained in a self-supervised manner. Artifact-CT images were generated from planning CT by random deformation and projection replacement, and SARN was trained based on paired artifact-CT and CT images. The planning CT and CBCT images of 260 patients with cancer, including 120 thoracic and 140 abdominal CT scans, were used to train and evaluate neural networks. The CBCT images of another 12 patients in late treatment fractions, which contained large anatomy changes, were also tested by trained models. The trained models include commonly used U-Net, cycleGAN, attention-gated cycleGAN (cycAT), and cascade models combined SARN with cycleGAN or cycAT. The generated sCT images were compared in terms of image quality and dose calculation accuracy.

RESULTS

The sCT images generated by SARN combined with cycleGAN and cycAT showed the best image quality, removed the most artifacts, and retained the normal anatomical structure. The SARN+cycleGAN performed best in streaking artifacts removal with the maximum percent integrity uniformity (PIU_m ) of 91.0% and minimum standard deviation (SD) of 35.4 HU for delineated artifact regions among all models. The mean absolute error (MAE) of CBCT images in the thorax and abdomen were 71.6 and 55.2 HU, respectively, using planning CT images after deformable registration as ground truth. Compared with CBCT, the thoracic and abdominal sCT images generated by each model had significantly improved image quality with smaller MAE (p < 0.05). The SARN+cycAT obtained the minimum MAEs of 42.5 HU in the thorax while SARN+cycleGAN got the minimum MAEs of 32.0 HU in the abdomen. The sCT generated by U-Net had a remarkably lower anatomical structure accuracy compared with the other models. The thoracic and abdominal sCT images generated by SARN+cycleGAN showed optimal dose calculation accuracy with gamma passing rates (2 mm/2%) of 98.2% and 96.9%, respectively.

CONCLUSIONS

The proposed SARN can reduce serious streaking artifacts in CBCT images. The SARN combined with cycleGAN can generate high-quality sCT images with fewer artifacts, high-accuracy HU values, and accurate anatomical structures, thus providing reliable dose calculation in ART.

Classification for thyroid nodule using ViT with contrastive learning in ultrasound images

The lack of representative features between benign nodules, especially level 3 of Thyroid Imaging Reporting and Data System (TI-RADS), and malignant nodules limits diagnostic accuracy, leading to inconsistent interpretation, overdiagnosis, and unnecessary biopsies. We propose a Vision-Transformer-based (ViT) thyroid nodule classification model using contrast learning, called TC-ViT, to improve accuracy of diagnosis and specificity of biopsy recommendations. ViT can explore the global features of thyroid nodules well. Nodule images are used as ROI to enhance the local features of the ViT. Contrast learning can minimize the representation distance between nodules of the same category, enhance the representation consistency of global and local features, and achieve accurate diagnosis of TI-RADS 3 or malignant nodules. The test results achieve an accuracy of 86.9%. The evaluation metrics show that the network outperforms other classical deep learning-based networks in terms of classification performance. TC-ViT can achieve automatic classification of TI-RADS 3 and malignant nodules on ultrasound images. It can also be used as a key step in computer-aided diagnosis for comprehensive analysis and accurate diagnosis. The code will be available at https://github.com/Jiawei217/TC-ViT.

A RASSF8-AS1 based exosomal lncRNAs panel used for diagnostic and prognostic biomarkers for esophageal squamous cell carcinoma

BACKGROUND

Exosomal long non-coding RNA (lncRNA) has been shown to be potential biomarker for cancer diagnosis and follow up. However, little is known about its application in esophageal squamous cell carcinoma (ESCC) detection. Here, we sought to develop a novel diagnostic model based on serum exosomal lncRNAs to improve ESCC screening efficiency.

METHODS

A multiphase, case-control study was conducted among 140 ESCC patients and 140 healthy controls. Microarray screening was performed to acquire differentially expressed exosomal lncRNAs in the discovery phase. The diagnostic model Index I was constructed based on a panel of three lncRNAs using logistic regression in the training phase, and were confirmed in a subsequent validation phase. A receiver operating characteristic (ROC) curve was generated to calculate the diagnostic value. The effects of the selected lncRNAs level on ESCC mortality were evaluated using a Cox hazard regression model and Kaplan-Meier curve analysis, and the expression level with clinicopathological features was also calculated. Finally, we explored the oncogenic potential of candidate lncRNA RASSF8-AS1 in vitro and by target mRNA sequencing.

RESULTS

Index I was able to discriminate ESCC patients from healthy controls, and showed superiority to classic tumor biomarkers. Moreover, serum levels of the exosomal lncRNAs correlated with clinicopathological features and prognosis. The in vitro assays showed that RASSF8-AS1 played an oncogenic role in ESCC. Target mRNA scanning results suggested involvement of RASSF8-AS1 in tumor immunity and metabolism.

CONCLUSION

The newly identified serum exosomal lncRNAs could be used as new biomarkers for ESCC, and showed oncogenic potential in ESCC.

Functionalized TiCu/TiCuN coating promotes osteoporotic fracture healing by upregulating the Wnt/β-catenin pathway

Osteoporosis results in decreased bone mass and insufficient osteogenic function. Existing titanium alloy implants have insufficient osteoinductivity and delayed/incomplete fracture union can occur when used to treat osteoporotic fractures. Copper ions have good osteogenic activity, but their dose-dependent cytotoxicity limits their clinical use for bone implants. In this study, titanium alloy implants functionalized with a TiCu/TiCuN coating by arc ion plating achieved a controlled release of copper ions in vitro for 28 days. The coated alloy was co-cultured with bone marrow mesenchymal stem cells and showed excellent biocompatibility and osteoinductivity in vitro. A further exploration of the underlying mechanism by quantitative real-time polymerase chain reaction and western blotting revealed that the enhancement effects are related to the upregulation of genes and proteins (such as axin2, β-catenin, GSK-3β, p-GSK-3β, LEF1 and TCF1/TCF7) involved in the Wnt/β-catenin pathway. In vivo experiments showed that the TiCu/TiCuN coating significantly promoted osteoporotic fracture healing in a rat femur fracture model, and has good in vivo biocompatibility based on various staining results. Our study confirmed that TiCu/TiCuN-coated Ti promotes osteoporotic fracture healing associated with the Wnt pathway. Because the coating effectively accelerates the healing of osteoporotic fractures and improves bone quality, it has significant clinical application prospects.

Lightweight and anchor-free frame detection strategy based on improved CenterNet for multiscale ships in SAR images

Ship detection using synthetic aperture radar (SAR) images has important applications in military and civilian fields, but the different sizes of the ship downgrade the detection accuracy of multiscale ships. Aiming at the problem of the poor accuracy and low efficiency of multiscale ship detection in complex scenes, this paper proposes a lightweight and anchor-free frame detection strategy for multiscale ships in SAR images. First, to deal with the problems of limited training samples, different sizes, attitudes, and angles of the ships in SAR images, a data augmentation strategy suitable for SAR images is adopted to expand the training space, followed by multiscale training to enhance the model generalization ability for multiscale ship detection. Second, a lightweight and anchor-free ship detection model based on the improved CenterNet is proposed, which abandons the dense anchor frame generation and extracts the key point of the ships for detection and positioning. Compared with the anchor frame-based detection method, this proposed detection model does not need to use the post-processing method to remove redundant anchor frames, and can accurately locate the center point of the ships with a better detection performance. Third, to reduce the model size and simplify the model parameters, a more lightweight network design is adopted in combination with the characteristics of SAR images. Hence, a residual network (ResNet) with fewer convolutional layers is constructed as the backbone network, and the cross-stage partial network (CSPNet) and spatial pyramid pooling (SPP) network are designed as the bottleneck network. The shallow ResNet can fully extract the SAR image features and reduce the training overfitting, and CSPNet and SPP can effectively combine the low-level image features to obtain the high-level features, reducing the model computation while at the same time enhancing the feature extraction ability. Finally, the evaluation index of the common objects in the context dataset is introduced, which can provide higher-quality evaluation results for ship detection accuracy and provide comprehensive evaluation indicators for multiscale ship detection. Experimental results show that the proposed strategy has the advantages of high detection efficiency, strong detection ability, and good generalization performance, which can achieve real-time and high-precision detection of the multiscale ship in complex SAR images.

Quantitative multi-image analysis in metals research

Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure-property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1557/s43579-022-00265-7.

Niobium promotes fracture healing in rats by regulating the PI3K-Akt signalling pathway: An in vivo and in vitro study

Background

Stable fixation is crucial in fracture treatment. Currently, optimal fracture fixation devices with osteoinductivity, mechanical compatibility, and corrosion resistance are urgently needed for clinical practice. Niobium (Nb), whose mechanical properties are similar to those of bone tissue, has excellent biocompatibility and corrosion resistance, so it has the potential to be the most appropriate fixation material for internal fracture treatment. However, not much attention has been paid to the use of Nb in the area of clinical implants. Yet its role and mechanism of promoting fracture healing remain unclear. Hence, this study aims at elucidating on the effectiveness of Nb by systematically evaluating its osteogenic performance via in vivo and ex vivo tests.

Methods

Systematic in vivo and in vitro experiments were conducted to evaluate the osteogenic properties of Nb. In vitro experiments, the biocompatibility and osteopromoting activity of Nb were assessed. And the osteoinductive activity of Nb was assessed by alizarin red, ALP staining and PCR test. In vivo experiments, the effectiveness and biosafety of Nb in promoting fracture healing were evaluated using a rat femoral fracture model. Through the analysis of gene sequencing results of bone scab tissues, the upregulation of PI3K-Akt pathway expression was detected and it was verified by histochemical staining and WB experiments.

Results

Experiments in this study had proved that Nb had excellent in-vitro cell adhesion and proliferation-promoting effects without cytotoxicity. In addition, ALP activity, alizarin red staining and semi-quantitative analysis in the Nb group had indicated its profound impact on enhancing osteogenic differentiation of MC3T3-E1 cells. We also found that the use of Nb implants can accelerate fracture healing compared to that with Ti6Al4V using an animal model of femur fracture in rats, and the biosafety of Nb was confirmed in vivo via histological evaluation. Furthermore, we found that the osteogenic effects of Nb were achieved through activation of the PIK/Akt3 signalling pathway.

Conclusion

As is shown in the present research, Nb possessed excellent biosafety in clinical implants and accelerated fracture healing by activating the PI3K-Akt signalling pathway, which had good prospects for clinical translation, and it can replace titanium alloy as a material for new functional implants.

[Analysis of outcome indicators in clinical trials on Chinese medicine as adjuvant therapy for severe pneumonia]

This study analyzed the outcome indicators in randomized controlled trial(RCT) on Chinese medicine as adjuvant therapy for severe pneumonia in the past years, laying a foundation for the design of clinical trials on and construction of core outcome set(COS) for severe pneumonia. To be specific, related RCT was retrieved from CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, Web of Science, Chinese Clinical Trial Registry, and ClinicalTrials.gov(from January 1,2011 to April 9,2022). Then data in the trials were extracted, and the quality of included RCT was assessed according to Cochrane handbook, followed by descriptive analysis of the use of outcome indicators. A total of 11 833 articles were screened out, and finally 34 RCTs were included(2 were protocols). The included trials involved 109 outcome indicators with emergence frequency of 320, which were mainly classified into 9 categories: physicochemical indicators(54, frequency 167), time to achieve the efficacy(15, frequency 38), clinical effective rate(10, frequency 36), quality of life(11, frequency 35), symptoms and signs(7, frequency 18), traditional Chinese medicine(TCM) syndrome(4, frequency 13), safety(3, frequency 8), economic evaluation(1, frequency 1), other indicators(4, frequency 4). The indicators with high frequency followed the order: total effective rate, arterial oxygen partial pressure, C-reactive protein, white blood cell count, arterial blood carbon dioxide partial pressure. A total of 5 articles(14.71%) reported the main outcome indicators and 11 articles(32.35%) adopted the efficacy on TCM syndromes as the outcome indicator. There are many problems in the selection of outcome indicators in RCT on the treatment of severe pneumonia with Chinese medicine, mainly manifested as the disregard of clinical endpoint indicators, the inappropriate selection of surrogate indicators, and the non-standard evaluation criteria for the efficacy on TCM syndrome. It is suggested that the evaluation system for the efficacy of Chinese medicine on severe pneumonia should be established in accordance with the method for international COS to improve the quality of clinical trials.