A case report and literature review on a rare subtype of triple-negative breast cancer in children.

BACKGROUND: Triple-negative breast cancer (TNBC) is a type of breast tumor with a poor prognosis because it lacks or expresses low levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). TNBC is more common in middle-aged and older women, and cases of TNBC in children are rarely reported. This is the only case of childhood SBC in our hospital in more than 70 years, and the disease is extremely rare internationally. We analyzed and studied the disease and TNBC from both clinical and pathological aspects and found that SBC is very different from TNBC. CASE PRESENTATION: We report a case of secretory breast cancer (SBC), a subtype of TNBC, in an 8-year-old girl from our institution. The child presented with a single mass in the left breast only, with no skin rupture and no enlargement of the surrounding lymph nodes. The child underwent two surgeries and was followed up for one year with a good prognosis. CONCLUSIONS: SBC is highly prevalent among the multiple pathological types of pediatric breast cancer. Almost all pediatric SBC patients are characterized by the ETV6-NTRK3 fusion gene, which has a good prognosis and a 10-year survival rate of more than 90% when compared with other TNBC subtypes. According to the patient, we performed local mass resection and a postoperative pathological diagnosis of SBC (a subtype of BL-TNBC). The TNBC case had a good prognosis and differed from basal TNBC in several aspects, including clinical presentation, treatment, and prognosis. It is necessary to exclude SBC from BL-type TNBC, enhance understanding of the disease, and individualize the treatment plan, so as to avoid medical errors.

Classification of metastatic hepatic carcinoma and hepatocellular carcinoma lesions using contrast-enhanced CT based on EI-CNNet.

BACKGROUND: For hepatocellular carcinoma and metastatic hepatic carcinoma, imaging is one of the main diagnostic methods. In clinical practice, diagnosis mainly relied on experienced imaging physicians, which was inefficient and cannot met the demand for rapid and accurate diagnosis. Therefore, how to efficiently and accurately classify the two types of liver cancer based on imaging is an urgent problem to be solved at present. PURPOSE: The purpose of this study was to use the deep learning classification model to help radiologists classify the single metastatic hepatic carcinoma and hepatocellular carcinoma based on the enhanced features of enhanced CT (Computer Tomography) portal phase images of the liver site. METHODS: In this retrospective study, 52 patients with metastatic hepatic carcinoma and 50 patients with hepatocellular carcinoma were among the patients who underwent preoperative enhanced CT examinations from 2017-2020. A total of 565 CT slices from these patients were used to train and validate the classification network (EI-CNNet, training/validation: 452/113). First, the EI block was used to extract edge information from CT slices to enrich fine-grained information and classify them. Then, ROC (Receiver Operating Characteristic) curve was used to evaluate the performance, accuracy, and recall of the EI-CNNet. Finally, the classification results of EI-CNNet were compared with popular classification models. RESULTS: By utilizing 80% data for model training and 20% data for model validation, the average accuracy of this experiment was 98.2% ± 0.62 (mean ± standard deviation (SD)), the recall rate was 97.23% ± 2.77, the precision rate was 98.02% ± 2.07, the network parameters were 11.83 MB, and the validation time was 9.83 s/sample. The classification accuracy was improved by 20.98% compared to the base CNN network and the validation time was 10.38 s/sample. Compared with other classification networks, the InceptionV3 network showed improved classification results, but the number of parameters was increased and the validation time was 33 s/sample, and the classification accuracy was improved by 6.51% using this method. CONCLUSION: EI-CNNet demonstrated promised diagnostic performance and has potential to reduce the workload of radiologists and may help distinguish whether the tumor is primary or metastatic in time; otherwise, it may be missed or misjudged.

[Effects of ultrasound on the physiological characteristics and competitive growth between Microcystis aeruginosa and Chlorella pyrenoidosa]. / è¶ å£°æ³¢å¯¹é“œç»¿å¾®å›Šè—»ä¸Žè›‹ç™½æ ¸å°çƒè—»ç”Ÿç†ç‰¹å¾åŠç«žäº‰ç”Ÿé•¿çš„å½±å“.

Microcystis aeruginosa is a common bloom-forming cyanobacterium, which generally coexists and competes with Chlorella pyrenoidosa in lakes. Sonication can be used for emergency management of algal blooms. Ultrasound influences algal growth and physiological parameters, as well as interspecific competition in algal community. To explore the effects of ultrasonic stress (35 kHz, 0.035 W·cm-3) on physiological characteristics and interspecific competition of algae, M. aeruginosa and C. pyrenoidosa were sonicated in mono- and co-cultures (1:1 mixture, according to cell concentration). Results showed that M. aeruginosa was more sensitive to ultrasonic stress. After the sonication for 600 s, both photosynthetic activity (Fv/Fm) and esterase activity of M. aeruginosa showed significant changes, with Fv/Fm values in mono- and co-cultures being decreased by 51.8% and 64.7%, respectively. In comparison, Fv/Fm values of C. pyrenoidosa changed slightly. M. aeruginosa released more chromophoric dissolved organic matter (CDOM, including tryptophan-, tyrosine-, and fulvic-like substances) than C. pyrenoidosa. The cell concentration of C. pyrenoidosa showed little changes regardless of sonication time, while the cell concentration of M. aeruginosa decreased at different degrees. The cell concentration of M. aeruginosa in co-cultures decreased by 42.6% after sonication for 600 s, which might be responsible for the dominance of C. pyrenoidosa during 8 days after sonication. M. aeruginosa inhibited C. pyrenoidosa in other treatments, but mutual inhibition appeared in the 600 s sonication treatment. After ultrasonic treatment, the activity of M. aeruginosa could recover gradually. The treatment should be conducted again within a week to improve the persistence of algal control.

Correlation Analysis of Gene and Radiomic Features in Colorectal Cancer Liver Metastases.

Colorectal cancer liver metastasis (CRLM) was one of the cancers with high mortality. Clinically, the target point was determined by invasive detection, which increased the suffering of patients and the cost of treatment. If the target point was found through the relationship between early radiomic information and genetic information, it was expected to assist doctors in diagnosing disease, formulating treatment plans, and reducing the pain and burden of patients. In this study, gene coexpression analysis and hub gene mining were first performed on the gene data; secondly, quantitative radiomic features were extracted from CT-enhanced radiomic data to obtain features highly correlated with CRLM; and finally, we analyzed the relationship between gene features and radiomic feature correlations by establishing a link between early radiomic features and gene sequencing and finding highly correlated expressions. This experiment demonstrated that radiomic features could be used to mine gene attributes. Based on the four previously identified genes (NRAS, KRAS, BRAF, and PIK3CA), we identified two novel genes, MAPK1 and STAT1, highly associated with CRLM. There were specific correlations between these 6 genes and radiomic features (shape_elongation, glcm, glszm, firstorder_10percentile, gradient, exponent_firstorder_Range, and gradient_glszm_SmallAreaLowGrayLevel). Therefore, this paper established the correlation between radiomic features and genes, and through radiomic features, we could find the genes associated with them, which was expected to achieve noninvasive prediction of liver metastasis.

The expression of ß-Defensin-2, IL-22, IL-22R1 and IL-10R2 in rat model of Klebsiella pneumonia and their correlation with histological grades.

Backgrounds and Aims:Klebsiella pneumoniae represents the most common opportunistic pathogen contributing to Klebsiella pneumonia in hospital-acquired infections. Klebsiella pneumonia has a rapidly progressive clinical course and multi-drug resistant (MDR). Identification of the effective biochemical markers is crucial for improving early diagnosis and treatment of Klebsiella pneumonia. The aims of our study are to 1) investigate the expression of ß-Defensin-2(rßD2), IL-22, IL-22R1 and IL-10R2 in Klebsiella pneumonia-infected rats and 2) their association with the histological grades of Klebsiella pneumonia.Methods and Materials: Fifty specific pathogen free (SPF) male SD rats were randomly divided into two groups: control group (treated with normal saline) and pneumonia group (treated with K. pneumoniae). All animals were sacrificed 1 h, 12 h, 1 d, 3 d, 5 d post infection. The severity and property of pneumonia was evaluated by histopathologic observation and pathogen identification. The mRNA expression of rßD2, IL-22, IL-22R1 and IL-10R2 was measured by RT-qPCR assay. The expression of rßD2 in rat lung tissue was determined by Western blot analysis, and the level of IL-22 in rat serum was determined by ELISA.Results: Histopathologic examination and bacterial counting of lung tissues confirmed the successful establishment of rat pneumonia model. The gene expression of rßD2, IL-22, IL-22R1 and IL-10R2 in pneumonia rats were significantly higher than those in healthy control mice (P < 0.05). The expression of rßD2 was correlated with histological grades of Klebsiella pneumonia and the level of IL-22. RT-qPCR results showed that the peak expression of IL-22R1 appeared earlier than IL-10R2 in rat pneumonia model.Conclusions: The expression of rßD2 and IL-22 was increased significantly at early stage in rat Klebsiella pneumonia model, suggesting that IL-22 and rßD2 might serve as potential biomarkers for the early diagnosis of Klebsiella pneumonia.

Preparation of 4,4'-bis-(carboxyl phenylazo)-dibenzo-18-crown-6 dye and its application on ratiometric colorimetric recognition to Hg2+.

A multifunctional dye, 4,4'-bis-(carboxyl phenylazo)-dibenzo-18-crown-6 dye (BCADC) was designed and prepared via diazotization and coupling reaction of dibenzo-18-crown-6 with p-amino benzoic acid. The dye, combining crown ether ring, azo and carboxyl group, exhibits well-defined Hg(2+)-selective ratiometric colorimetric behavior, with the maximum absorbance peak changing from 354 nm to 408 nm exclusively. Under the optimum conditions, the recognition to Hg(2+) has a linear range of 2.5-58×10(-7) mol L(-1) with a 0.9978 correlation coefficient. The method was applied to analyse 3 environmental water samples with a detection limit of 2.9×10(-8) mol L(-1) and a relative standard deviation (R.S.D.) lower than 3.7% (n=5). The action mechanism between BCADC and metal ions was discussed by means of Job's plots and theoretical calculations.