Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment. Oral squamous cell carcinoma (OSCC), a representative hypoxic tumor, has a heterogeneous internal metabolic environment. To clarify the relationship between different metabolic regions and the tumor immune microenvironment (TME) in OSCC, Single cell (SC) and spatial transcriptomics (ST) sequencing of OSCC tissues were performed. The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data. The metabolic activity of each spot was calculated using scMetabolism, and k-means clustering was used to classify all spots into hyper-, normal-, or hypometabolic regions. CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others. Through CellPhoneDB and NicheNet cell-cell communication analysis, it was found that in the hypermetabolic region, fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts (iCAFs), and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12. The secretion of CXCL12 recruits regulatory T cells (Tregs), leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment. This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC, ST and TCGA bulk data, and highlights potential targets for therapy.
Humans ; Carcinoma, Squamous Cell/metabolism* ; Squamous Cell Carcinoma of Head and Neck ; Mouth Neoplasms/metabolism* ; Immunosuppression Therapy ; Transforming Growth Factor beta ; Head and Neck Neoplasms ; Gene Expression Profiling ; Tumor Microenvironment

Currently, clinically used drugs for the treatment of gout inflammation, such as colchicine, nonsteroidal anti-inflammatory drugs, and glucocorticoids, can only relieve the pain of joint inflammation and have severe hepatorenal toxicity and multiple organ adverse reactions. The NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome is a key complex that induces the onset of gout inflammation and has become a crucial target in the development of anti-gout drugs. This article reviews the research progress of anti-gout small molecules targeting the NLRP3 inflammasome and their bioactivity evaluation methods in the past five years, in order to provide information for the development of specific drugs for the treatment of gout inflammation.

Objective To explore the occurrence of adverse reactions to vaccination in children with special health status in Kunming and the corresponding countermeasures.Methods The information data of 952 children with special health conditions who were vaccinated at the Child Healthcare Department of the Kunming Children's Hospital from October 2021 to February 2023 were collected,and descriptive methods were used for epidemiological analysis.Results The detection rate of adverse reactions in children with special health conditions in Kunming was 10.92%(104/952),all of which were mild adverse reactions.The top three vaccines with the highest detection rates of adverse reactions were adsorbed acellular pertussis-diphtheria-tetanus vaccine(Pertussis-Diphtheria-Tetanus),measles-mumps-rubella attenuated live vaccine(Measles-Mumps-Rubella),and meningococcal polysaccharide vaccine group A and C(Meningococcal A+C),with detection rates of 7.00%,4.14%,and 3.08%,respectively.The detection rate of adverse reactions in children with premature birth,allergy,and anemia after vaccination was higher,with detection rates of 13.87%,11.03%,and 10.05%,respectively.The detection rate of adverse reactions after more than two vaccinations was 73.08%,which was higher than the first vaccination detection rate of 26.92%.The clinical manifestations of vaccine adverse reactions were mainly fever,redness,and induration,with detection rates of 39.42%,21.15%,and 18.27%,respectively.The detection rate of adverse reactions in children with special health conditions under the age of two was higher,accounting for 75.00%.The detection rate of adverse reactions within 24 hours after vaccination was higher,accounting for 62.50%.After timely symptomatic treatment and follow-up observation,all adverse reactions in children with special health conditions after vaccination recovered within 7 days.Conclusion Adverse reactions after vaccination in children with special health conditions in Kunming are predominantly mild.The detection rate of adverse reactions post-vaccination for pertussis,measles,mumps,and meningococcal A+C is notably high.Children under 2 years old with premature birth,allergy,and anemia are more likely to have adverse reactions after vaccination.These adverse reactions typically manifest within 24 hours post-vaccination and resolve within 7 days.

BACKGROUND:Compared with traditional two-dimensional culture,three-dimensional microtissue culture can show greater advantages.However,more favorable cultivation methods in three-dimensional culture still need to be further explored. OBJECTIVE:To evaluate the cell behavior of microtissue and its ability to promote cartilage formation under two three-dimensional culture methods. METHODS:Cartilage-derived microcarriers were prepared by chemical decellularization and tissue crushing.DNA quantification and nuclear staining were used to verify the success of decellularization,and histological staining was used to observe the matrix retention before and after decellularization.The microcarriers were characterized by scanning electron microscopy and CCK-8 assay.Cartilage-derived microtissues were constructed by combining cartilage-derived microcarriers with human adipose mesenchymal stem cells through three-dimensional static culture and three-dimensional dynamic culture methods.The cell viability and chondrogenic ability of the two groups of microtissues were detected by scanning electron microscopy,live and dead staining,and RT-qPCR. RESULTS AND CONCLUSION:(1)Cartilage-derived microcarriers were successfully prepared.Compared with before decellularization,the DNA content significantly decreased after decellularization(P<0.001).Scanning electron microscope observation showed that the surface of the microcarrier was surrounded by collagen,maintaining the characteristics of the natural extracellular matrix of cartilage cells.CCK-8 assay indicated that microcarriers had no cytotoxicity and could promote cell proliferation.(2)Scanning electron microscopy and live and dead staining results showed that compared with the three-dimensional static group,the three-dimensional dynamic group had a more extended morphology of microtissue cells,and extensive connections between cells and cells,between cells and matrix,and between matrix.(3)The results of RT-qPCR showed that the expressions of SOX9,proteoglycan,and type Ⅱ collagen in microtissues of both groups were increased at 7 or 14 days.The relative expression levels of each gene in the three-dimensional dynamic group were significantly higher than those in the three-dimensional static group at 14 days(P<0.05).At 21 days,the three-dimensional static group had significantly higher gene expression compared with the three-diomensional dynamic group(P<0.001).(4)The results showed that compared with three-dimensional static culture microtissue,three-dimensional dynamic culture microtissue could achieve higher expression of chondrogen-related genes in a shorter time,showing better cell viability and chondrogenic ability.

Objective     To construct a radiomics model for identifying clinical high-risk carotid plaques. Methods     A retrospective analysis was conducted on patients with carotid artery stenosis in China-Japan Friendship Hospital from December 2016 to June 2022. The patients were classified as a clinical high-risk carotid plaque group and a clinical low-risk carotid plaque group according to the occurrence of stroke, transient ischemic attack and other cerebrovascular clinical symptoms within six months. Six machine learning models including eXtreme Gradient Boosting, support vector machine, Gaussian Naive Bayesian, logical regression, K-nearest neighbors and artificial neural network were established. We also constructed a joint predictive model combined with logistic regression analysis of clinical risk factors. Results    Finally 652 patients were collected, including 427 males and 225 females, with an average age of 68.2 years. The results showed that the prediction ability of eXtreme Gradient Boosting was the best among the six machine learning models, and the area under the curve (AUC) in validation dataset was 0.751. At the same time, the AUC of eXtreme Gradient Boosting joint prediction model established by clinical data and carotid artery imaging data validation dataset was 0.823. Conclusion     Radiomics features combined with clinical feature model can effectively identify clinical high-risk carotid plaques.

The occurrence of benign prostate hyperplasia(BPH)was related to disrupted sex steroid hormones,and metformin(Met)had a clinical response to sex steroid hormone-related gynaecological disease.How-ever,whether Met exerts an antiproliferative effect on BPH via sex steroid hormones remains unclear.Here,our clinical study showed that along with prostatic epithelial cell(PEC)proliferation,sex steroid hormones were dysregulated in the serum and prostate of BPH patients.As the major contributor to dysregulated sex steroid hormones,elevated dihydrotestosterone(DHT)had a significant positive rela-tionship with the clinical characteristics of BPH patients.Activation of adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK)by Met restored dysregulated sex steroid hormone homeostasis and exerted antiproliferative effects against DHT-induced proliferation by inhibiting the formation of androgen receptor(AR)-mediated Yes-associated protein(YAP1)-TEA domain transcription factor(TEAD4)heterodimers.Met's anti-proliferative effects were blocked by AMPK inhibitor or YAP1 over-expression in DHT-cultured BPH-1 cells.Our findings indicated that Met would be a promising clinical therapeutic approach for BPH by inhibiting dysregulated steroid hormone-induced PEC proliferation.

ObjectiveThe scale of microalgae farming industry is huge. During farming, it is easy for microalgae to be affected by miscellaneous bacteria and other contaminants. Because of that, periodic test is necessary to ensure the growth of microalgae. Present microscopy imaging and spectral analysis methods have higher requirements for experiment personnel, equipment and sites, for which it is unable to achieve real-time portable detection. For the purpose of real-time portable microalgae detection, a real-time microalgae detection system of low detection requirement and fast detection speed is needed. MethodsThis study has developed a microalgae detection system based on deep learning. A microscopy imaging device based on bright field was constructed. With imaged captured from the device, a neural network based on YOLOv3 was trained and deployed on microcomputer, thus realizing real-time portable microalgae detection. This study has also improved the feature extraction network by introducing cross-region residual connection and attention mechanism and replacing optimizer with Adam optimizer using multistage and multimethod strategy. ResultsWith cross-region residual connection, the mAP value reached 0.92. Compared with manual result, the detection error was 2.47%. ConclusionThe system could achieve real-time portable microalgae detection and provide relatively accurate detection result, so it can be applied to periodic test in microalgae farming.

Pancreatic cancer is among the most malignant cancers,and thus early intervention is the key to better survival outcomes.However,no methods have been derived that can reliably identify early precursors of development into malignancy.Therefore,it is urgent to discover early molecular changes during pancreatic tumorigenesis.As aberrant glycosylation is closely associated with cancer progression,numerous efforts have been made to mine glycosylation changes as biomarkers for diagnosis;however,detailed glycoproteomic information,especially site-specific N-glycosylation changes in pancreatic cancer with and without drug treatment,needs to be further explored.Herein,we used comprehensive solid-phase chemoenzymatic glycoproteomics to analyze glycans,glycosites,and intact glycopeptides in pancreatic cancer cells and patient sera.The profiling of N-glycans in cancer cells revealed an increase in the secreted glycoproteins from the primary tumor of MIA PaCa-2 cells,whereas human sera,which contain many secreted glycoproteins,had significant changes of glycans at their specific glycosites.These results indicated the potential role for tumor-specific glycosylation as disease biomarkers.We also found that AMG-510,a small molecule inhibitor against Kirsten rat sarcoma viral oncogene homolog(KRAS)G12C mutation,profoundly reduced the glycosylation level in MIA PaCa-2 cells,suggesting that KRAS plays a role in the cellular glycosylation process,and thus glycosylation inhibition contributes to the anti-tumor effect of AMG-510.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.

Tumor progression is closely related to tumor tissue metabolism and reshaping of the microenvironment.Oral squamous cell carcinoma(OSCC),a representative hypoxic tumor,has a heterogeneous internal metabolic environment.To clarify the relationship between different metabolic regions and the tumor immune microenvironment(TME)in OSCC,Single cell(SC)and spatial transcriptomics(ST)sequencing of OSCC tissues were performed.The proportion of TME in the ST data was obtained through SPOTlight deconvolution using SC and GSE103322 data.The metabolic activity of each spot was calculated using scMetabolism,and k-means clustering was used to classify all spots into hyper-,normal-,or hypometabolic regions.CD4T cell infiltration and TGF-β expression is higher in the hypermetabolic regions than in the others.Through CellPhoneDB and NicheNet cell-cell communication analysis,it was found that in the hypermetabolic region,fibroblasts can utilize the lactate produced by glycolysis of epithelial cells to transform into inflammatory cancer-associated fibroblasts(iCAFs),and the increased expression of HIF1A in iCAFs promotes the transcriptional expression of CXCL12.The secretion of CXCL12 recruits regulatory T cells(Tregs),leading to Treg infiltration and increased TGF-β secretion in the microenvironment and promotes the formation of a tumor immunosuppressive microenvironment.This study delineates the coordinate work axis of epithelial cells-iCAFs-Tregs in OSCC using SC,ST and TCGA bulk data,and highlights potential targets for therapy.