Abstract With the innovation and development of science and technology, the convenience and intelligence of home life has become a trend. This intelligent drying rack system based on the Internet of Things uses the OneNET cloud platform as the information port, and selects the STM32F103C8T6 single-chip microcomputer as the main control chip to read, judge and output the execution signal from the signal collected by the sensor. The smart drying rack can be operated manually and remotely through the touch screen, related hardware circuits and mobile phone APP, which can control the extension and recycling of the clothes drying rod, and the automatic drying and storage of clothes. It is convenient to use and improves the intelligent level of the drying rack. The problem that the drying rack cannot dry the wet clothes and needs to be stored manually is solved.
Abstract Stress‐induced hair loss is a prevalent health concern, with mechanisms that remain unclear, and effective treatment options are not yet available. In this study, we investigated whether stress‐induced hair loss was related to an imbalanced immune microenvironment. Screening the skin‐infiltrated immune cells in a stressed mouse model, we discovered a significant increase in macrophages upon stress induction. Clearance of macrophages rescues mice from stress‐induced hair shedding and depletion of hair follicle stem cells (HFSCs) in the skin, demonstrating the role of macrophages in triggering hair loss in response to stress. Further flow cytometry analysis revealed a significant increase in M1 phenotype macrophages in mice under stressed conditions. In searching for humoral factors mediating stress‐induced macrophage polarization, we found that the hormone Norepinephrine (NE) was elevated in the blood of stressed mice. In addition, in‐vivo and in‐vitro studies confirm that NE can induce macrophage polarization toward M1 through the β‐adrenergic receptor, Adrb2. Transcriptome, enzyme‐linked immunosorbent assay (ELISA), and western blot analyses reveal that the NLRP3/caspase‐1 inflammasome signaling and its downstream effector interleukin 18 (IL‐18) and interleukin 1 beta (IL‐1β) were significantly upregulated in the NE‐treated macrophages. However, inhibition of the NE receptor Adrb2 with ICI118551 reversed the upregulation of NLRP3/caspase‐1, IL‐18, and IL‐1β. Indeed, IL‐18 and IL‐1β treatments lead to apoptosis of HFSCs. More importantly, blocking IL‐18 and IL‐1β signals reversed HFSCs depletion in skin organoid models and attenuated stress‐induced hair shedding in mice. Taken together, this study demonstrates the role of the neural (stress)‐endocrine (NE)‐immune (M1 macrophages) axis in stress‐induced hair shedding and suggestes that IL‐18 or IL‐1β may be promising therapeutic targets.
Background Although many efforts have been devoted to identify biomarkers to predict the responsiveness of immune checkpoint inhibitors, including expression of programmed death-ligand 1 (PD-L1) and major histocompatibility complex (MHC) I, microsatellite instability (MSI), mismatch repair (MMR) defect, tumor mutation burden (TMB), tertiary lymphoid structures (TLSs), and several transcriptional signatures, the sensitivity of these indicators remains to be further improved. Materials and methods Here, we integrated T-cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in MMR-deficient tumors including tumors of Lynch syndrome (LS). Results In both cohorts, MMR-deficient tumors displayed personalized tumor immune signatures, including inflamed, immune excluded, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert tumor exhibited a more malignant phenotype characterized by low differentiation adenocarcinoma, larger tumor sizes, and higher metastasis rate. Moreover, the tumor immune signatures associated with distinct populations of infiltrating immune cells were comparable to TLSs and more sensitive than transcriptional signature gene expression profiles (GEPs) in immunotherapy prediction. Surprisingly, the tumor immune signatures might arise from the somatic mutations. Notably, patients with MMR deficiency had benefited from the typing of immune signatures and later immune checkpoint inhibition. Conclusion Our findings suggest that compared to PD-L1 expression, MMR, TMB, and GEPs, characterization of the tumor immune signatures in MMR-deficient tumors improves the efficiency of predicting the responsiveness of immune checkpoint inhibition.
In the process of epithelial-mesenchymal transition (EMT), epithelial cancer cells transdifferentiate into mesenchymal-like cells with high motility and aggressiveness, resulting in the spread of tumor cells. Immune cells and inflammation in the tumor microenvironment are the driving factors of EMT, but few studies have explored the core targets of the interaction between EMT and tumor immune cells. We analyzed thousands of cases of gastric cancer and gastric tissue specimens of TCGA, CPTAC, GTEx and analyzing QPCR and IHC data of 56 gastric cancer patients in SYSU Gastric Cancer Research Center. It was known that EMT has an important connection with the infiltration of NK cells, and that the expression of vinculin may be the target of the phenomenon. The increased expression of vinculin is closely related to the aggressiveness and distant metastasis of cancer, which affects the survival prognosis of the patient. Moreover, through in vitro experiments under 3D conditions, we found that vinculin, cell invasion and metastasis are clearly linked. VCL can affect EMT and tumor immunity by regulating EPCAM gene expression. The role and mechanism of action of vinculin have been controversial, but this molecule may downregulate EpCAM (epithelial cellular adhesion molecule) and its own role in gastric cancer through DNA methylation, causing NK cells to enrich into tumor cells and kill tumor cells. At the same time, it promotes the occurrence of EMT, which in turn causes tumor metastasis and thus poorer prognosis.
Immunotherapy has shown excellent therapeutic effects on various malignant tumors; however, to date, immunotherapy for osteosarcoma is still suboptimal. In this study, we performed comprehensive bioinformatic analysis of immune-related genes (IRGs) and tumor-infiltrating immune cells (TIICs). Datasets of differentially expressed IRGs were extracted from the GEO database (GSE16088). The functions and prognostic values of these differentially expressed IRGs were systematically investigated using a series of bioinformatics methods. In addition, CCK8 and plate clone formation assays were used to explore the effect of PGF on osteosarcoma cells, and twenty-nine differentially expressed IRGs were identified, of which 95 were upregulated and 34 were downregulated. Next, PPI was established for Identifying Hub genes and biology networks by Cytoscape. Six IRGs (APLNR, TPM2, PGF, CD86, PROCR, and SEMA4D) were used to develop an overall survival (OS) prediction model, and two IRGs (HLA-B and PGF) were used to develop a relapse-free survival (RFS) prediction model. Compared with the low-risk patients in the training cohort (GSE39058) and TARGET validation cohorts, high-risk patients had poorer OS and RFS. Using these identified IRGs, we used OS and RFS prediction nomograms to generate a clinical utility model. The risk scores of the two prediction models were associated with the infiltration proportions of some TIICs, and the activation of memory CD4 T-cells was associated with OS and RFS. CD86 was associated with CTLA4 and CD28 and influenced the infiltration of different TIICs. In vitro experiments showed that the knockdown of PGF inhibited the proliferation and viability of osteosarcoma cells. In conclusion, these findings help us better understand the prognostic roles of IRGs and TIICs in osteosarcoma, and CD86 and PGF may serve as specific immune targets.
Today's society, IT technology has rapid updates, data is growing at an alarming rate of accumulation, the era of big data had come. The intelligent terminals are the main source of data sensor data big data era. Big data to people's lives is brings a lot of convenience, to the enterprise is provide more business opportunities. On the other hand, big data increases the risk of leaks important information, information security technology at this stage cannot meet big data information security needs, how to provide information security protection, strengthen information security, construction-related law is also the attendant problems.
Mucinous appendiceal adenocarcinoma (MAA) is a rare, heterogeneous disease. Patients with unrespectable mucinous appendiceal adenocarcinoma presenting with peritoneal spread are treated by intraperitoneal chemotherapy, hyperthermic intraperitoneal chemotherapy, systemic chemotherapy, or targeted therapy. However, there are no guidelines for efficacious drugs against mucinous appendiceal adenocarcinoma. Therefore, relevant high-fidelity models should be investigated to identify effective drugs for individual therapy.Surgical tumor specimens were obtained from a mucinous appendiceal adenocarcinoma patient. The tissue was digested and organoid culture was established. H&E and immunohistochemistry staining as well as DNA sequencing was performed on tissue and organoid. The pathological characteristics and gene mutations of the organoid were compared to those of the original tumor. Drug sensitivity tests were performed on organoid and the patient clinical responds to chemotherapy and targeted therapy was compared.Organoids were successfully established and stably passaged. Pathological characteristics of organoids including H&E staining and expression of protein markers (CK20, CDX-2, STAB2, CD7, PAX8) were consistent to those of the original tumor. Moreover, the organoids carried the same gene mutations as the primary tumor. Sensitivity of the organoids to chemotherapeutic drugs and tyrosine kinase inhibitors included: 5-FU (IC50 43.95 μM), Oxaliplatin (IC50 23.49 μM), SN38 (IC50 1.02 μM), Apatinib (IC50 0.10 μM), Dasatinib (IC50 2.27 μM), Docetaxel (IC50 5.26 μM), Regorafenib (IC50 18.90 μM), and Everolimus (IC50 9.20 μM). The sensitivities of organoid to these drugs were comparable to those of the patient's clinical responses.The mucinous appendiceal adenocarcinoma organoid model which retained the characteristics of the primary tumor was successfully established. Combined organoid-based drug screening and high throughput sequencing provided a promising way for mucinous appendiceal adenocarcinoma treatment.
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