ß-Galactosidase-guided self-assembled 68Ga nanofibers probe for micro-PET tumor imaging.

ß-galactosidase (ß-gal) has high activity in various malignancies, which is suitable for targeted positron emission tomography (PET) imaging. Meanwhile, ß-gal can successfully guide the formation of nanofibers, which enhances the intensity of imaging and extends the imaging time. Herein, we designed a ß-galactosidase-guided self-assembled PET imaging probe [68Ga]Nap-NOTA-1Gal. We envisage that ß-gal could recognize and cleave the target site, bringing about self-assembling to form nanofibers, thereby enhancing the PET imaging effect. The targeting specificity of [68Ga]Nap-NOTA-1Gal for detecting ß-gal activity was examined using the control probe [68Ga]Nap-NOTA-1. Micro-PET imaging showed that tumor regions of [68Ga]Nap-NOTA-1Gal were visible after injection. And the tumor uptake of [68Ga]Nap-NOTA-1Gal was higher than [68Ga]Nap-NOTA-1 at all-time points. Our results demonstrated that the [68Ga]Nap-NOTA-1Gal can be used for the purpose of a new promising PET probe for helping diagnose cancer with high levels of ß-gal activity.

Microphysiologically Engineered Vessel-Tumor Model to Investigate Vascular Transport Dynamics of Immune Cells.

Cancer immunotherapy has emerged as a promising therapeutic strategy to combat cancer effectively. However, it is hard to observe and quantify how this in vivo process happens. Three-dimensional (3D) microfluidic vessel-tumor models offer valuable capability to study how immune cells transport during cancer progression. We presented an advanced 3D vessel-supported tumor model consisting of the endothelial lumen and vessel network for the study of T cells' transportation. The process of T cell transport through the vessel network and interaction with tumor spheroids was represented and monitored in vitro. Specifically, we demonstrate that the endothelial glycocalyx serving in the T cells' transport can influence the endothelium-immune interaction. Furthermore, after vascular transport, how programmed cell death protein 1 (PD-1) immune checkpoint inhibition influences the delivered activated-T cells on tumor killing was evaluated. Our in vitro vessel-tumor model provides a microphysiologically engineered platform to represent T cell vascular transportation during tumor immunotherapy. The reported innovative vessel-tumor platform is believed to have the potential to explore the tumor-induced immune response mechanism and preclinically evaluate immunotherapy's effectiveness.

Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system.

Purpose: We developed an Infant Retinal Intelligent Diagnosis System (IRIDS), an automated system to aid early diagnosis and monitoring of infantile fundus diseases and health conditions to satisfy urgent needs of ophthalmologists. Methods: We developed IRIDS by combining convolutional neural networks and transformer structures, using a dataset of 7697 retinal images (1089 infants) from four hospitals. It identifies nine fundus diseases and conditions, namely, retinopathy of prematurity (ROP) (mild ROP, moderate ROP, and severe ROP), retinoblastoma (RB), retinitis pigmentosa (RP), Coats disease, coloboma of the choroid, congenital retinal fold (CRF), and normal. IRIDS also includes depth attention modules, ResNet-18 (Res-18), and Multi-Axis Vision Transformer (MaxViT). Performance was compared to that of ophthalmologists using 450 retinal images. The IRIDS employed a five-fold cross-validation approach to generate the classification results. Results: Several baseline models achieved the following metrics: accuracy, precision, recall, F1-score (F1), kappa, and area under the receiver operating characteristic curve (AUC) with best values of 94.62% (95% CI, 94.34%-94.90%), 94.07% (95% CI, 93.32%-94.82%), 90.56% (95% CI, 88.64%-92.48%), 92.34% (95% CI, 91.87%-92.81%), 91.15% (95% CI, 90.37%-91.93%), and 99.08% (95% CI, 99.07%-99.09%), respectively. In comparison, IRIDS showed promising results compared to ophthalmologists, demonstrating an average accuracy, precision, recall, F1, kappa, and AUC of 96.45% (95% CI, 96.37%-96.53%), 95.86% (95% CI, 94.56%-97.16%), 94.37% (95% CI, 93.95%-94.79%), 95.03% (95% CI, 94.45%-95.61%), 94.43% (95% CI, 93.96%-94.90%), and 99.51% (95% CI, 99.51%-99.51%), respectively, in multi-label classification on the test dataset, utilizing the Res-18 and MaxViT models. These results suggest that, particularly in terms of AUC, IRIDS achieved performance that warrants further investigation for the detection of retinal abnormalities. Conclusions: IRIDS identifies nine infantile fundus diseases and conditions accurately. It may aid non-ophthalmologist personnel in underserved areas in infantile fundus disease screening. Thus, preventing severe complications. The IRIDS serves as an example of artificial intelligence integration into ophthalmology to achieve better outcomes in predictive, preventive, and personalized medicine (PPPM / 3PM) in the treatment of infantile fundus diseases. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00350-y.

Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors.

BACKGROUND: Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) play a pivotal role in maintaining lifelong hematopoiesis. The distinction between stem cells and other progenitors, as well as the assessment of their functions, has long been a central focus in stem cell research. In recent years, deep learning has emerged as a powerful tool for cell image analysis and classification/prediction. METHODS: In this study, we explored the feasibility of employing deep learning techniques to differentiate murine HSCs and MPPs based solely on their morphology, as observed through light microscopy (DIC) images. RESULTS: After rigorous training and validation using extensive image datasets, we successfully developed a three-class classifier, referred to as the LSM model, capable of reliably distinguishing long-term HSCs, short-term HSCs, and MPPs. The LSM model extracts intrinsic morphological features unique to different cell types, irrespective of the methods used for cell identification and isolation, such as surface markers or intracellular GFP markers. Furthermore, employing the same deep learning framework, we created a two-class classifier that effectively discriminates between aged HSCs and young HSCs. This discovery is particularly significant as both cell types share identical surface markers yet serve distinct functions. This classifier holds the potential to offer a novel, rapid, and efficient means of assessing the functional states of HSCs, thus obviating the need for time-consuming transplantation experiments. CONCLUSION: Our study represents the pioneering use of deep learning to differentiate HSCs and MPPs under steady-state conditions. This novel and robust deep learning-based platform will provide a basis for the future development of a new generation stem cell identification and separation system. It may also provide new insight into the molecular mechanisms underlying stem cell self-renewal.

Comprehensive pan-cancer analysis reveals SIRT5 is a predictive biomarker for prognosis and immunotherapy response.

BACKGROUND: Sirtuin 5 (SIRT5) is a promising therapeutic target involved in regulating multiple metabolic pathways in cells and organisms. The role of SIRT5 in cancer is currently unclear, and a comprehensive systematic pan-cancer analysis is required to explore its value in diagnosis, prognosis, and immune function. METHODS: We investigated the role of SIRT5 in tumorigenesis, diagnosis, prognosis, metabolic pathways, the immune microenvironment, and pan-cancer therapeutic response. Moreover, we explored chemicals affecting the expression of SIRT5 and computed the relationship between SIRT5 and drug sensitivity. Finally, the role of SIRT5 in melanoma was analyzed using a series of experiments in vitro and in vivo. RESULTS: We found that SIRT5 is differentially expressed and shows early diagnostic value in various tumors and that somatic cell copy number alterations and DNA methylation contribute to its aberrant expression. SIRT5 expression correlates with clinical features. Besides, it is negatively (positively) correlated with several metabolic pathways and positively (negatively) correlated with several important metastasis-related and immune-related pathways. High SIRT5 expression predicts poor (or good) prognosis in various tumors and can affect drug sensitivity. We also demonstrated that SIRT5 expression significantly correlates with immunomodulator-associated molecules, lymphocyte subpopulation infiltration, and immunotherapeutic response biomarkers. In addition, we showed that SIRT5 is differentially expressed in immunotherapy cohorts. In addition, we explored various chemicals that may affect SIRT5 expression. In conclusion, we demonstrated that SIRT5 is a key pathogenic gene that promotes melanoma progression. CONCLUSION: Our study provides a systematic analysis of SIRT5 and its regulatory genes. SIRT5 has excellent diagnostic and prognostic capabilities for many cancers. This may remodel the tumor microenvironment. The potential of SIRT5-based cancer therapies is emphasized and helps predict the response to immunotherapy.

ß-Galactosidase-Activated and Red Light-Induced RNA Modification Strategy for Prolonged NIR Fluorescence/PET Bimodality Imaging.

Improving the retention of small-molecule-based therapeutic agents in tumors is crucial to achieve precise diagnosis and effective therapy of cancer. Herein, we propose a ß-galactosidase (ß-Gal)-activated and red light-induced RNA modification (GALIRM) strategy for prolonged tumor imaging. A ß-Gal-activatable near-infrared (NIR) fluorescence (FL) and positron emission tomography (PET) bimodal probe 68Ga-NOTA-FCG consists of a triaaza triacetic acid chelator NOTA for 68Ga-labeling, a ß-Gal-activated photosensitizer CyGal, and a singlet oxygen (1O2)-susceptible furan group for RNA modification. Studies have demonstrated that the probe emits an activated NIR FL signal upon cleavage by endogenous ß-Gal overexpressed in the lysosomes, which is combined with the PET imaging signal of 68Ga allowing for highly sensitive imaging of ovarian cancer. Moreover, the capability of 68Ga-NOTA-FCG generating 1O2 under 690 nm illumination could be simultaneously unlocked, which can trigger the covalent cross-linking between furan and nucleotides of cytoplasmic RNAs. The formation of the probe-RNA conjugate can effectively prevent exocytosis and prolong retention of the probe in tumors. We thus believe that this GALIRM strategy may provide entirely new insights into long-term tumor imaging and efficient tumor treatment.

[WITHDRAWN] MIML: Multiplex Image Machine Learning for High Precision Cell Classification via Mechanical Traits within Microfluidic Systems.

This paper has been withdrawn by Khayrul Islam.

Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors.

Background: Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) play a pivotal role in maintaining lifelong hematopoiesis. The distinction between stem cells and other progenitors, as well as the assessment of their functions, has long been a central focus in stem cell research. In recent years, deep learning has emerged as a powerful tool for cell image analysis and classification/prediction. Methods: In this study, we explored the feasibility of employing deep learning techniques to differentiate murine HSCs and MPPs based solely on their morphology, as observed through light microscopy (DIC) images. Results: After rigorous training and validation using extensive image datasets, we successfully developed a three-class classifier, referred to as the LSM model, capable of reliably distinguishing long-term HSCs (LT-HSCs), short-term HSCs (ST-HSCs), and MPPs. The LSM model extracts intrinsic morphological features unique to different cell types, irrespective of the methods used for cell identification and isolation, such as surface markers or intracellular GFP markers. Furthermore, employing the same deep learning framework, we created a two-class classifier that effectively discriminates between aged HSCs and young HSCs. This discovery is particularly significant as both cell types share identical surface markers yet serve distinct functions. This classifier holds the potential to offer a novel, rapid, and efficient means of assessing the functional states of HSCs, thus obviating the need for time-consuming transplantation experiments. Conclusion: Our study represents the pioneering use of deep learning to differentiate HSCs and MPPs under steady-state conditions. With ongoing advancements in model algorithms and their integration into various imaging systems, deep learning stands poised to become an invaluable tool, significantly impacting stem cell research.

Gamma-glutamyl transpeptidase and indirect bilirubin may participate in systemic inflammation of patients with psoriatic arthritis.

BACKGROUND: Previous studies have suggested that systemic metabolic abnormalities are closely related to psoriatic arthritis (PsA). Gamma-glutamyl transpeptidase (GGT) and indirect bilirubin (IBIL), two essential active substances in hepatic metabolism that have been demonstrated as an oxidative and anti-oxidative factor respectively, have been proved to be involved in oxidative stress damage and inflammation in several human diseases. However, their role in PsA remains unclear. METHODS: In this retrospective comparative cohort study, a case group of 68 PsA patients and a control group of 73 healthy volunteers from the Third Hospital of Hebei Medical University were enrolled. Serum GGT, IBIL, GGT/IBIL ratio and C-reactive protein (CRP), a well applied bio-marker of systemic inflammatory in PsA, were compared between the two groups. Furthermore, the relationship of GGT, IBIL and GGT/IBIL with CRP were explored in PsA patients. Finally, the patients were divided into high inflammation group and low inflammation group according to the median value of CRP. Multivariate logistic regression analyses were used for the association of systemic inflammation level with GGT, IBIL and GGT/IBIL. RESULTS: Compared with healthy controls, PsA patients exhibited significantly higher serum GGT, GGT/IBIL, and CRP levels and lower IBIL levels. Serum GGT and GGT/IBIL were positively correlated with CRP, whereas IBIL were negatively correlated with CRP. Binary logistic regression analysis revealed that serum GGT was a risk factor for high CRP in PsA, whereas IBIL was a protective factor. Furthermore, GGT/IBIL was a better indicator of high CRP condition in PsA patients than either GGT or IBIL alone, as determined by the receiver operating characteristic curves. CONCLUSION: GGT and IBIL may participate in the pathogenesis of PsA. Additionally, GGT, IBIL and the balance of the two may reflect systemic inflammation mediated by oxidative stress events related to metabolic abnormalities to a certain extent.

An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) system for the identification of disease status and recommending treatment modalities for retinopathy of prematurity (ROP). METHODS: This retrospective cohort study included a total of 24,495 RetCam images from 1075 eyes of 651 preterm infants who received RetCam examination at the Shenzhen Eye Hospital in Shenzhen, China, from January 2003 to August 2021. Three tasks included ROP identification, severe ROP identification, and treatment modalities identification (retinal laser photocoagulation or intravitreal injections). The AI system was developed to identify the 3 tasks, especially the treatment modalities of ROP. The performance between the AI system and ophthalmologists was compared using extra 200 RetCam images. RESULTS: The AI system exhibited favorable performance in the 3 tasks, including ROP identification [area under the receiver operating characteristic curve (AUC), 0.9531], severe ROP identification (AUC, 0.9132), and treatment modalities identification with laser photocoagulation or intravitreal injections (AUC, 0.9360). The AI system achieved an accuracy of 0.8627, a sensitivity of 0.7059, and a specificity of 0.9412 for identifying the treatment modalities of ROP. External validation results confirmed the good performance of the AI system with an accuracy of 92.0% in all 3 tasks, which was better than 4 experienced ophthalmologists who scored 56%, 65%, 71%, and 76%, respectively. CONCLUSIONS: The described AI system achieved promising outcomes in the automated identification of ROP severity and treatment modalities. Using such algorithmic approaches as accessory tools in the clinic may improve ROP screening in the future.

scAAV9-VEGF alleviates symptoms of amyotrophic lateral sclerosis (ALS) mice through regulating aromatase.

Amyotrophic lateral sclerosis (ALS) is an adult-onset, chronic, progressive, and fatal neurodegenerative disease that leads to progressive atrophy and weakness of the muscles throughout the body. Herein, we found that the intrathecal injection of adeno-associated virus (AAV)-delivered VEGF in SOD1-G93A transgenic mice, as well as ALS mice, could significantly delay disease onset and preserve motor functions and neurological functions, thus prolonging the survival of mice models. Moreover, we found that VEGF treatment could induce the elevated expression of aromatase, which is a key enzyme in estrogen synthesis, in neurons but not in astrocytes. On the other hand, the changes in the expression of oxidative stress-related factors HO-1 and GCLM and autophagy-related proteins p62 and LC3II upon the administration of VEGF revealed the involvement of oxidative stress and autophagy underlying the downstream of the VEGF-induced mitigation of ALS. In conclusion, this study proved the protective effects of VEGF in the onset and development of ALS and revealed the involvement of estrogen, oxidative stress and autophagy in the VEGF-induced alleviation of ALS. Our results highlighted the potential of VEGF as a promising therapeutic agent in the treatment of ALS.

Synthesis and preliminary biological evaluation of a novel 99mTc-labeled small molecule for PD-L1 imaging.

In recent years, PD-1/PD-L1 checkpoint blockade immunotherapy with remarkable efficacy has set off a heat wave. The expression level of PD-L1, which plays a predictive role in anti-PD-1/PD-L1 therapy, could be quantified by noninvasive imaging with radiotracers. Herein, we introduced the synthesis and preliminary biological evaluation of a novel 99mTc-labeled small molecule radiotracer [99mTc]G3C-CBM for PD-L1 imaging. [99mTc]G3C-CBM was achieved with high radiochemical purity (>96 %) and remained good stability in PBS and FBS. In competitive combination experiment, [99mTc]G3C-CBM was displaced by increasing concentrations of unlabeled G3C-CBM, resulting in an IC50 value of 41.25±2.23 nM for G3C-CBM. The uptake of [99mTc]G3C-CBM in A375-hPD-L1 cells (17.51±2.08 %) was approximately 6.47 folds of that in A375 cells (2.71±0.36 %) after co-incubation for 2 h. The biodistribution results showed that the radioactivity uptake in A375-hPD-L1 tumor reached the maximum (0.35±0.01 %ID/g) at 2 h post injection, and the optimum tumor/muscle ratio of 2.94±0.29 occurred at the same time. In addition, [99mTc]G3C-CBM was quickly cleared from the blood with a clearance half-life of just 119.25 min. These results indicate that [99mTc]G3C-CBM is a potential SPECT PD-L1 imaging agent and is worthy of further study.

Complete mitochondrial genome of Agrostis stolonifera: insights into structure, Codon usage, repeats, and RNA editing.

BACKGROUND: Plants possess mitochondrial genomes that are large and complex compared to animals. Despite their size, plant mitochondrial genomes do not contain significantly more genes than their animal counterparts. Studies into the sequence and structure of plant mitochondrial genomes heavily imply that the main mechanism driving replication of plant mtDNA, and offer valuable insights into plant evolution, energy production, and environmental adaptation. RESULTS: This study presents the first comprehensive analysis of Agrostis stolonifera's mitochondrial genome, characterized by a branched structure comprising three contiguous chromosomes, totaling 560,800 bp with a GC content of 44.07%. Annotations reveal 33 unique protein-coding genes (PCGs), 19 tRNA genes, and 3 rRNA genes. The predominant codons for alanine and glutamine are GCU and CAA, respectively, while cysteine and phenylalanine exhibit weaker codon usage biases. The mitogenome contains 73, 34, and 23 simple sequence repeats (SSRs) on chromosomes 1, 2, and 3, respectively. Chromosome 1 exhibits the most frequent A-repeat monomeric SSR, whereas chromosome 2 displays the most common U-repeat monomeric SSR. DNA transformation analysis identifies 48 homologous fragments between the mitogenome and chloroplast genome, representing 3.41% of the mitogenome's total length. The PREP suite detects 460 C-U RNA editing events across 33 mitochondrial PCGs, with the highest count in the ccmFn gene and the lowest in the rps7 gene. Phylogenetic analysis confirms A. stolonifera's placement within the Pooideae subfamily, showing a close relationship to Lolium perenne, consistent with the APG IV classification system. Numerous homologous co-linear blocks are observed in A. stolonifera's mitogenomes and those of related species, while certain regions lack homology. CONCLUSIONS: The unique features and complexities of the A. stolonifera mitochondrial genome, along with its similarities and differences to related species, provide valuable insights into plant evolution, energy production, and environmental adaptation. The findings from this study significantly contribute to the growing body of knowledge on plant mitochondrial genomes and their role in plant biology.

SMC1A facilitates gastric cancer cell proliferation, migration, and invasion via promoting SNAIL activated EMT.

BACKGROUND: Structural maintenance of chromosomes protein 1 A (SMC1A) is a crucial subunit of the cohesion protein complex and plays a vital role in cell cycle regulation, genomic stability maintenance, chromosome dynamics. Recent studies demonstrated that SMC1A participates in tumorigenesis. This reseach aims to explore the role and the underlying mechanisms of SMC1A in gastric cancer (GC). MATERIALS AND METHODS: RT-qPCR and western blot were used to examine the expression levels of SMC1A in GC tissues and cell lines. The role of SMC1A on GC cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) were analyzed. Furthermore,the mechanism of SMC1A action was investigated. RESULTS: SMC1A was highly expressed in GC tissues and cell lines. The high expression of SMC1A indicated the poor overall survival of GC patients from Kaplan-Meier Plotter. Enhancing the expression of SMC1A in AGS cells remarkably promoted cell proliferation in vitro and in vivo, migration and invasion, Conversely, knockdown of SMC1A in HGC27 cells inhibited cell proliferation, migration and invasion. Moreover, it's observed that SMC1A promoted EMT and malignant cell behaviors via regulating SNAIL. CONCLUSION: Our study revealed that SMC1A promotes EMT process by upregulating SNAIL, which contributes to gastric cancer cell proliferation, migration and invasion. Therefore, targeting SMC1A may be a potential strategy to improve GC therapy.

Optimal frequency determination for terahertz technology-based detection of colitis-related cancer in mice.

Colorectal cancer is a prevalent malignancy globally, often linked to chronic colitis. Terahertz technology, with its noninvasive and fingerprint spectroscopic properties, holds promise in disease diagnosis. This study aimed to explore terahertz technology's application in colitis-associated cancer using a mouse model. Mouse colorectal tissues were transformed into paraffin-embedded blocks for histopathological analysis using HE staining. Terahertz transmission spectroscopy was performed on the tissue blocks. By comparing terahertz absorption differences, specific frequency bands were identified as optimal for distinguishing cancerous and normal tissues. The study revealed that terahertz spectroscopy effectively differentiates colitis-related cancers from normal tissues. Remarkably, 1.8 THz emerged as a potential optimal frequency for diagnosing colorectal cancer in mice. This suggests the potential for rapid histopathological diagnosis of colorectal cancer using terahertz technology.

Morusin shows potent antitumor activity for melanoma through apoptosis induction and proliferation inhibition.

BACKGROUND: The discovery of new anti-melanoma drugs with low side effect is urgently required in the clinic. Recent studies showed that morusin, a flavonoid compound isolated from the root bark of Morus Alba, has the potential to treat multiple types of cancers, including breast cancer, gastric cancer, and prostate cancer. However, the anti-cancer effect of morusin on melanoma cells has not been investigated. METHODS: We analyzed the effects of morusin on the proliferation, cell cycle, apoptosis, cell migration and invasion ability of melanoma cells A375 and MV3, and further explored the effects of morusin on tumor formation of melanoma cell. Finally, the effects of morusin on the proliferation, cycle, apoptosis, migration and invasion of A375 cells after knockdown of p53 were detected. RESULTS: Morusin effectively inhibits the proliferation of melanoma cells and induces cell cycle arrest in the G2/M phase. Consistently, CyclinB1 and CDK1 that involved in the G2/M phase transition were down-regulated upon morusin treatment, which may be caused by the up-regulation of p53 and p21. In addition, morusin induces cell apoptosis and inhibits migration of melanoma cells, which correlated with the changes in the expression of the associated molecules including PARP, Caspase3, E-Cadherin and Vimentin. Moreover, morusin inhibits tumor growth in vivo with little side effect on the tumor-burden mice. Finally, p53 knockdown partially reversed morusin-mediated cell proliferation inhibition, cell cycle arrest, apoptosis, and metastasis. CONCLUSION: Collectively, our study expanded the spectrum of the anti-cancer activity of morusin and guaranteed the clinical use of the drug for melanoma treatment.

Integrated bioinformatics analysis for conducting a prognostic model and identifying immunotherapeutic targets in gastric cancer.

BACKGROUND: Gastric cancer is the third leading cause of death from cancer worldwide and has a poor prognosis. Practical risk scores and prognostic models for gastric cancer are lacking. While immunotherapy has succeeded in some cancers, few gastric cancer patients benefit from immunotherapy. Immune genes and the tumor microenvironment (TME) are essential for cancer progression and immunotherapy response. However, the roles of immune genes and the tumor microenvironment in immunotherapy remain unclear. The study aimed to construct a prognostic prediction model and identify immunotherapeutic targets for gastric cancer (GC) patients by exploring immune genes and the tumor microenvironment. RESULTS: An immune-related risk score (IRRS) model, including APOH, RNASE2, F2R, DEFB126, CXCL6, and CXCL3 genes, was constructed for risk stratification. Patients in the low-risk group, which was characterized by elevated tumor mutation burden (TMB) have higher survival rate. The risk level was remarkably correlated with tumor-infiltrating immune cells (TIICs), the immune checkpoint molecule expression, and immunophenoscore (IPS). CXCL3 and CXCL6 were significantly upregulated in gastric cancer tissues compared with normal tissues using the UALCAN database and RT-qPCR. The nomogram showed good calibration and moderate discrimination in predicting overall survival (OS) at 1-, 3-, and 5- year for gastric cancer patients using risk-level and clinical characteristics. CONCLUSION: Our findings provided a risk stratification and prognosis prediction tool for gastric cancer patients and further the research into immunotherapy in gastric cancer.

Morusinol extracted from Morus alba induces cell cycle arrest and apoptosis via inhibition of DNA damage response in melanoma by CHK1 degradation through the ubiquitin-proteasome pathway.

BACKGROUD: Flavonoids have a variety of biological activities, such as anti-inflammation, anti-tumor, anti-thrombosis and so on. Morusinol, as a novel isoprene flavonoid extracted from Morus alba root barks, has the effects of anti-arterial thrombosis and anti-inflammatory in previous studies. However, the anti-cancer mechanism of morusinol remains unclear. PURPOSE: In present study, we mainly studied the anti-tumor effect of morusinol and its mode of action in melanoma. METHODS: The anti-cancer effect of morusinol on melanoma were evaluated by using the MTT, EdU, plate clone formation and soft agar assay. Flow cytometry was used for detecting cell cycle and apoptosis. The É£-H2AX immunofluorescence and the alkaline comet assay were used to detect DNA damage and the Western blotting analysis was used to investigate the expressions of DNA-damage related proteins. Ubiquitination and turnover of CHK1 were also detected by using the immunoprecipitation assay. The cell line-derived xenograft (CDX) mouse models were used in vivo to evaluate the effect of morusinol on tumorigenicity. RESULTS: We demonstrated that morusinol not only had the ability to inhibit cell proliferation, but also induced cell cycle arrest at G0/G1 phase, caspase-dependent apoptosis and DNA damage in human melanoma cells. In addition, morusinol effectively inhibited the growth of melanoma xenografts in vivo. More strikingly, CHK1, which played an important role in maintaining the integrity of cell cycle, genomic stability and cell viability, was down-regulated in a dose- and time-dependent manner after morusinol treatment. Further research showed that CHK1 was degraded by the ubiquitin-proteasome pathway. Whereafter, morusinol-induced cell cycle arrest, apoptosis and DNA damage were partially salvaged by overexpressing CHK1 in melanoma cell lines. Herein, further experiments demonstrated that morusinol increased the sensitivity of dacarbazine (DTIC) to chemotherapy for melanoma in vitro and in vivo. CONCLUSION: Morusinol induces CHK1 degradation through the ubiquitin-proteasome pathway, thereby inducing cell cycle arrest, apoptosis and DNA damage response in melanoma. Our study firstly provided a theoretical basis for morusinol to be a candidate drug for clinical treatment of cancer, such as melanoma, alone or combinated with dacarbazine.

Non-intubated deep paralysis: a new anaesthesia strategy for vocal cord polypectomy.

BACKGROUND: Vocal cord polyp is common otorhinolaryngological disease, traditionally treated by vocal cord polypectomy under a supporting laryngoscope with general anaesthesia. Although it is safe and controllable, it would cause some anaesthesia complications. Moreover, the complex process of general anaesthesia may significantly reduce surgical efficiency. Avoiding these problems remains an important issue. METHODS: All patients were subjected to the standard non-intubated deep paralysis (NIDP) protocol consisting of four phases. An emergency plan was launched when NIDP cannot be implemented successfully. Patient characteristics, blood gas and monitoring data were collected during NIDP. Data concerning satisfaction, complications and duration of anaesthesia and recovery were collected to assess its effectiveness. RESULT: Among 20 enrolled patients, the success rate of NIDP was 95%. Only one patient failed in completing NIDP. Blood gas analysis revealed that the partial pressure of oxygen and carbon dioxide was maintained at safe levels. Monitoring during NIDP revealed fluctuations in mean arterial pressure between 110 and 70 mmHg, and the heart rate was stable at 60-100 beats per minute. The duration of anaesthesia and postoperative recovery were 13.0 ± 2.84 and 5.47 ± 1.97 min, respectively. All patients and surgeons were satisfied with NIDP, and no complications were detected before discharge. CONCLUSION: NIDP can be safely applied to patients and can replace general anaesthesia in vocal cord polypectomy. It can significantly reduce the duration of anaesthesia and postoperative recovery. No anaesthesia complications occurred without intubation, and patients and surgeons were satisfied with NIDP. TRIAL REGISTRATIONS: This single-centre, prospective study was registered on clinicaltrial.gov (NCT04247412) on 30th July 2020.

Microfluidic Droplet-Assisted Fabrication of Vessel-Supported Tumors for Preclinical Drug Discovery.

High-fidelity in vitro tumor models are important for preclinical drug discovery processes. Currently, the most commonly used model for in vitro drug testing remains the two-dimensional (2D) cell monolayer. However, the natural in vivo tumor microenvironment (TME) consists of extracellular matrix (ECM), supporting stromal cells and vasculature. They not only participate in the progression of tumors but also hinder drug delivery and effectiveness on tumor cells. Here, we report an integrated engineering system to generate vessel-supported tumors for preclinical drug screening. First, gelatin-methacryloyl (GelMA) hydrogel was selected to mimic tumor extracellular matrix (ECM). HCT-116 tumor cells were encapsulated into individual micro-GelMA beads with microfluidic droplet technique to mimic tumor-ECM interactions in vitro. Then, normal human lung fibroblasts were mingled with tumor cells to imitate the tumor-stromal interaction. The tumor cells and fibroblasts reconstituted in the individual GelMA microbead and formed a biomimetic heterotypic tumor model with a core-shell structure. Next, the cell-laden beads were consociated into a functional on-chip vessel network platform to restore the tumor-tumor microenvironment (TME) interaction. Afterward, the anticancer drug paclitaxel was tested on the individual and vessel-supported tumor models. It was demonstrated that the blood vessel-associated TME conferred significant additional drug resistance in the drug screening experiment. The reported system is expected to enable the large-scale fabrication of vessel-supported heterotypic tumor models of various cellular compositions. It is believed to be promising for the large-scale fabrication of biomimetic in vitro tumor models and may be valuable for improving the efficiency of preclinical drug discovery processes.