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Long-term Result of Lupus Nephritis: A Single Centre Examine.
In recent years, many studies have focused on the host immune system and its relationship with tumor progression in a variety of solid tumors, including breast cancer. This study investigates recent trends of immunotherapy research in breast cancer and compares the contributions of research from different regions, institutions, and authors. A search of breast cancer and immunotherapy studies that were published between 2010 and 2019-with different keyword combinations-was performed in the Web of Science database. Bibliometric data were collected for analysis. VOSviewer software was used to generate a figure for the keyword's co-occurrence network, so as to implement network visualization analysis. A total of 1,041 publications were identified. The United States and China contributed to approximately 50% of the publications, 336 and 208, respectively. Both countries drove the increase in publications after 2015. A paper entitled "Pembrolizumab in patients with advanced triple-negative breast cancer Phase IB KEYNOTE-012 Study" that was published in the Journal of Clinical Oncology by Nanda et al. was the most cited (715 citations). The keywords found in this research were grouped into four clusters "mechanism," "vaccination," "PD-L1," and "chemotherapy." The terms "tumor-infiltrating lymphocytes" and "PD-1/PD-L1" are among the latest hotspots, which mostly appeared in 2017. Author keyword analysis revealed that recent trends in breast cancer immunotherapy focus on the triple-negative breast cancer subtype and PD-1/PD-L1 immune checkpoint pathway and inhibitors. This study analyzed global trends in immunotherapy research on breast cancer over the past 10 years and provided insight into the features and research hotspots of the articles in this issue.
We aimed to explore the effects of Bupleuri Radix (BR) on the recurrence of resected colonic polyp (CP) by measuring angiogenin-2-induced protein kinase B (Ang PKB)/Akt signaling.

The main ingredients of BR were extracted by using ethanol and measured by HPLC. One hundred twenty patients with CP >10 mm who underwent resected surgery were randomly allocated to an aspirin (AG) or a BR medicine (BG) group. The allocation ratio was 1  1 and the intervention duration was one year. The recurrence rate of resected CP was investigated and the plasma levels of Ang PKB/Akt and inflammatory cytokines were measured using ELISA kits. After one-year surgery, side effects were recorded. The relationship between the serum levels of the main compounds of BR and plasma levels of Ang PKB/Akt was analyzed.

The main ingredients of CP are paeoniflorin, baicalin, saikosaponin A, and bupleurum saponin B2. Recurrence of resected CP was found in 17 patients from the AG group and eight patients from the BG group after one-year follow-up (
< 0.05). read more The levels of angiogenin-2 II and PKB/Akt in the AG group were higher than those in the BG group (
< 0.05). Meanwhile, BR treatment reduced the plasma levels of TNF-
, IL-1
and IL-6, and increased the level of IL-10(
< 0.05). Inflammatory cytokines are important factors that affect the recurrence of resected CP. Serum paeoniflorin, baicalin, saikosaponin A, and bupleurum saponin B2 in BR had a strong negative relationship with the plasma levels of Ang PKB/Akt.

BR significantly reduces the recurrence risk of resected CP by affecting Ang PKB/Akt signaling.
BR significantly reduces the recurrence risk of resected CP by affecting Ang PKB/Akt signaling.Artificial intelligence techniques have been positioned in the resolution of problems in various areas of healthcare. Clinical decision support systems developed from this technology have optimized the healthcare of patients with chronic diseases through mobile applications. In this study, several models based on this methodology have been developed to calculate the basal insulin dose in patients with type I diabetes using subcutaneous insulin infusion pumps. Methods. A pilot experimental study was performed with data from 56 patients with type 1 diabetes who used insulin infusion pumps and underwent continuous glucose monitoring. Several models based on artificial intelligence techniques were developed to analyze glycemic patterns based on continuous glucose monitoring and clinical variables in order to estimate the basal insulin dose. We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). We then evaluated the agreement between predicted and actual values using several statistical error measurements mean absolute error (MAE), mean square error (MSE), root-mean-square error (RMSE), Pearson's correlation coefficient (R), and determination coefficient (R2). Results. Twenty-four different models were obtained, one for each hour of the day, with each chosen technique. Correlation coefficients obtained with RF, SVMs, NNs, and BNs were 0.9999, 0.9921, 0.0303, and 0.7754, respectively. The error increased between 0600 and 0700 and between 1300 and 1700. Conclusions. The performance of the RF technique was excellent and got very close to the actual values. Intelligence techniques could be used to predict basal insulin dose. However, it is necessary to explore the validity of the results and select the target population. Models that allow for more accurate levels of prediction should be further explored.
Aromatase inhibitors in women with breast cancer have been associated with cancer treatment-induced bone loss (CTIBL), increased fracture risk, and impairment of glucose metabolism. Denosumab (Dmab), a monoclonal antibody against RANKL, which is a key regulator of the osteoclast activity, is effective as an antiresorptive agent in the treatment of CTIBL. Since RANKL/RANK pathway may contribute to the pathogenesis of glucometabolic disorders, it has been suggested that Dmab may improve glucose homeostasis. Our pilot study evaluated the effect of a single administration of 60 mg Dmab on glucose metabolism in a cohort of women with breast cancer treated with aromatase inhibitors.

Fifteen postmenopausal nondiabetic women were prospectively enrolled. Oral glucose tolerance test (OGTT) and metabolic parameters, including FGF21, were assessed at baseline and one month after Dmab injection. Midterm glucose control was evaluated by measuring glycated haemoglobin (HbA1c) levels 5 months after Dmab.

Parameters of glucose metabolism were not different one month after Dmab but circulating FGF21 levels significantly decreased (128.
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