Table_1_A visualized model for identifying optimal candidates for aggressive locoregional surgical treatment in patients with bone metastases from breast cancer.docx

BackgroundThe impact of surgical resection of primary (PTR) on the survival of breast cancer (BC) patients with bone metastasis (BM) has been preliminarily investigated, but it remains unclear which patients are suitable for this procedure. Finally, this study aims to develop a predictive model to screen BC patients with BM who would benefit from local surgery.MethodsBC patients with BM were identified using the Surveillance, Epidemiology, and End Results (SEER) database (2010 and 2015), and 39 patients were obtained for external validation from an Asian medical center. According to the status of local surgery, patients were divided into Surgery and Non-surgery groups. Propensity score matching (PSM) analysis was performed to reduce selection bias. Kaplan-Meier (K-M) survival and Cox regression analyses were conducted before and after PSM to study the survival difference between the two groups. The survival outcome and treatment modality were also investigated in patients with different metastatic patterns. The logistic regression analyses were utilized to determine significant surgery-benefit-related predictors, develop a screening nomogram and its online version, and quantify the beneficial probability of local surgery for BC patients with BM. Receiver operating characteristic (ROC) curves, the area under the curves (AUC), and calibration curves were plotted to evaluate the predictive performance and calibration of this model, whereas decision curve analysis (DCA) was used to assess its clinical usefulness.ResultsThis study included 5,625 eligible patients, of whom 2,133 (37.92%) received surgical resection of primary lesions. K-M survival analysis and Cox regression analysis demonstrated that local surgery was independently associated with better survival. Surgery provided significant survival benefits in most subgroups and metastatic patterns. After PSM, patients who received surgery had a longer survival time (OS: 46 months vs. 32 months, p ConclusionOur study further confirmed the significance of local surgery in BC patients with BM and proposed a novel tool to identify optimal surgical candidates.</p

Fast Photoconductive Responses in Organometal Halide Perovskite Photodetectors

Inorganic semiconductor-based photodetectors have been suffering from slow response speeds, which are caused by the persistent photoconductivity of semiconductor materials. For realizing high speed optoelectronic devices, the organometal halide perovskite thin films were applied onto the interdigitated (IDT) patterned Au electrodes, and symmetrical structured photoconductive detectors were achieved. The detectors were sensitive to the incident light signals, and the photocurrents of the devices were 2–3 orders of magnitude higher than dark currents. The responsivities of the devices could reach up to 55 mA W^1–. Most importantly, the detectors have a fast response time of less than 20 μs. The light and bias induced dipole rearrangement in organometal perovskite thin films has resulted in the instability of photocurrents, and Ag nanowires could quicken the process of dipole alignment and stabilize the photocurrents of the devices

Interfacial Emission Adjustment in ZnO Quantum Dots/p-GaN Heterojunction Light-Emitting Diodes

Ultraviolet (UV) light-emitting diodes (LEDs) were made by using ZnO quantum dots (QDs) as the emission layer. ZnO QDs with the diameter of 5 nm were fabricated by using a simple sintering method. By using p-GaN as the hole injection layer, a ZnO QDs/p-GaN heterojunction LED was constructed. Trap-controlled SCLC behavior of QDs led the LED to emit light mainly from the QDs layer, and the direct physical contact between ZnO QDs and GaN could effectively reduce the interfacial emission. As the result, a UV LED with the electroluminescence wavelength of 382 nm has been achieved

Table_3_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.xlsx

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.</p

DataSheet_1_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.zip

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.</p

Table_2_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.xlsx

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.</p

Image_1_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.jpeg

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.</p

Table_1_Significance of monocyte infiltration in patients with gastric cancer: A combined study based on single cell sequencing and TCGA.xlsx

BackgroundGastric cancer is still one of the most lethal tumor diseases in the world. Despite some improvements, the prognosis of patients with gastric cancer is still not accurately predicted.MethodsBased on single cell sequencing data, we conducted a detailed analysis of gastric cancer patients and normal tissues to determine the role of monocytes in the progression of gastric cancer. WCGA facilitated our search for Grade-related genes in TCGA. Then, according to the marker genes and cell differentiation genes of monocytes, we determined the cancer-promoting genes of monocytes. Based on LASSO regression, we established a prognostic model using TCGA database. The accuracy of the model was verified by PCA, ROC curve, survival analysis and prognostic analysis. Finally, we evaluated the significance of the model in clinical diagnosis and treatment by observing drug sensitivity, immune microenvironment and immune checkpoint expression in patients with different risk groups.ResultsMonocytes were poorly differentiated in tumor microenvironment. It mainly played a role in promoting cancer in two ways. One was to promote tumor progression indirectly by interacting with other tumor stromal cells. The other was to directly connect with tumor cells through the MIF and TNF pathway to play a tumor-promoting role. The former was more important in these two ways. A total of 292 monocyte tumor-promoting genes were obtained, and 12 genes were finally included in the construction of the prognosis model. A variety of validation methods showed that our model had an accurate prediction ability. Drug sensitivity analysis could provide guidance for clinical medication of patients. The results of immune microenvironment and immune checkpoint also indicated the reasons for poor prognosis of high-risk patients.ConclusionIn conclusion, we provided a 12-gene risk score formula and nomogram for gastric cancer patients to assist clinical drug therapy and prognosis prediction. This model had good accuracy and clinical significance.</p

Solar-Blind Avalanche Photodetector Based On Single ZnO–Ga₂O₃ Core–Shell Microwire

High-performance solar-blind (200–280 nm) avalanche photodetectors (APDs) were fabricated based on highly crystallized ZnO–Ga₂O₃ core–shell microwires. The responsivity can reach up to 1.3 × 10³ A/W under −6 V bias. Moreover, the corresponding detectivity was as high as 9.91 × 10¹⁴ cm·Hz^1/2/W. The device also showed a fast response, with a rise time shorter than 20 μs and a decay time of 42 μs. The quality of the detectors in solar-blind waveband is comparable to or even higher than that of commercial Si APD (APD120A2 from Thorlabs Inc.), with a responsivity ∼8 A/W, detectivity ∼10¹² cm·Hz^1/2/W, and response time ∼20 ns. The high performance of this APD make it highly suitable for practical applications as solar-blind photodetectors, and this core–shell microstructure heterojunction design method would provide a new approach for realizing an APD device