[Corrigendum] Downregulation of Notch1 induces apoptosis and inhibits cell proliferation and metastasis in laryngeal squamous cell carcinoma.

Following the publication of this article, a concerned reader drew to the authors' attention that a pair of the 24 h scratch­wound assay data panels in Fig. 4A, and three of the migration and invasion assay data panels in Fig. 4B, exhibited overlapping sections, suggesting that data which were intended to have shown the results from differently performed experiments had originated from the same sources. In addition, the total number of cases for the LSCC sample data in Table II did not reflect the sum of the samples indicated in the 'negative', 'positive' and 'strong positive' categories. After having consulted their original data, the authors have realized that Table II and Fig. 4 contained some inadvertent errors: The authors divided their control group data into two subgroups, namely the non­transfection and negative­shRNA groups, although they overlooked details of the filing system they had devised for saving the data, and mistakenly included images from the non­transfection group in with the negative­shRNA group due to unclear file labeling. Moreover, in Table II, the data value for the 'positive' stained samples should have been written as '43', not '44'. The corrected versions of Table II and Fig. 4, which now shows the corrected data for the 'Negative­shRNA / 24 h' experiment in Fig. 4A and the 'Non­transfection / Invasion' and 'Negative­shRNA / Migration' experiments in Fig. 4B, are shown below and on the next page, respectively. The authors sincerely apologize for the errors that were introduced during the preparation of this table and this figure, thank the Editor of Oncology Reports for granting them the opportunity to publish this corrigendum, and regret any inconvenience that these mistakes may have caused to the readership. [Oncology Reports 34: 3111­3119, 2015; DOI: 10.3892/or.2015.4274].

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVID-19 patients with pulmonary fibrosis, the relationship between the degree of fibrosis and the clinical classification of COVID-19, the characteristics of and risk factors for pulmonary fibrosis, and the evolution of pulmonary fibrosis after discharge. The incidence of pulmonary fibrosis in patients with severe or critical COVID-19 was significantly higher than that in patients with moderate COVID-19. There were significant differences in the degree of pulmonary inflammation and the extent of the affected area among patients with mild, moderate and severe pulmonary fibrosis. The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. Ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing, bronchiectasis and the extent of the affected area were significantly improved 30, 60 and 90 days after discharge compared with at discharge. The more severe the clinical classification of COVID-19, the more severe the residual pulmonary fibrosis was; however, in most patients, pulmonary fibrosis was improved or even resolved within 90 days after discharge.

[Sensitive Bands Extraction and Prediction Model of Tomato Chlorophyll in Glass Greenhouse].

In order to predict the content of chlorophyll in tomato rapidly and accurately, this study, with spectrum technology, focused on the extraction of sensitive spectral bands of tomato chlorophyll in glass greenhouse environment and created an effective estimation model. During the period of cultivating tomatoes, leaf spectra were measured with an ASD FieldSpec HH spectrophotometer and chlorophyll content was measured with Type 752 UV-Vis spectrophotometer. Based on the original spectra, absorbance spectra, first derivative spectra and continuum removal spectra, spectral data was preprocessed, in which the effectiveness of spectral features of chlorophyll content of tomato was highlighted and spectral response characteristics of the absorbance spectra in the visible part was enhanced. It was shown that both the continuum removal spectra and the first derivative spectra have strong blue and red absorption valley and green reflection peak. In this paper, the original spectrum, absorbance spectrum, first derivative spectrum and continuum removal spectrum were analyzed and compared, and then optimal spectral feature parameters were extracted with methods of Inter-Correlation analysis and multivariate collinearity diagnosis. Sensitive bands from original spectrum are 639, 672, 696, 750 and 768 nm. Sensitive bands from absorbance spectrum are 638, 663, 750 and 763 nm. Sensitive bands from first derivative spectrum are 516, 559 and 778 nm. Sensitive bands from continuum removal spectrum are 436, 564, 591, 612, 635, 683 and 760 nm. The stepwise multiple regressions were used to develop the prediction models of the chlorophyll content of tomato leaf. The result showed that the prediction model, which used the values from continuum removal spectrum at 436, 564, 591, 612, 635, 683, 760 nm as input variables, had the best predictive ability. The calibration R-Square was 0.88 and the validation R-Square was 0.82.

Notch 2 signaling contributes to cell growth, anti-apoptosis and metastasis in laryngeal squamous cell carcinoma.

Notch signaling is important during the development of a variety of human tumors. Depending on the context, Notch signaling can be either oncogenic or anti­proliferative, and therefore, its effects in cancer are unpredictable. The aim of the present study was to identify the importance of Notch 2 in the cell growth and metastasis of laryngeal squamous cell carcinoma (LSCC). The current study performed quantum dots­based immunofluorescence histochemistry to determine expression of Notch 2 in 72 LSCC samples without lymph node metastasis, 23 LSCC samples with lymph node metastasis and 31 samples from vocal cord polyps. It was observed that Notch 2 was upregulated in LSCC tissue compared with normal vocal cord polyps. This upregulation was further enhanced in LSCC tissues with lymph node metastasis compared with LSCC tissues without lymph node metastasis. Following knockdown of NOTCH2 expression in LSCC cells, the in vitro tumorigenicity of Hep­2 cells was inhibited, with growth, migration, invasion and proliferation reduced, and apoptosis induced. Additionally, following downregulation of Notch 2 protein expression, the protein expression levels of phospho­mitogen­activated protein kinase 1 (p­ERK), v­myc avian myelocytomatosis viral oncogene homolog and B­cell CLL/lymphoma 2 (Bcl2) were also downregulated, whereas, Bcl2­associated X protein expression was upregulated. There were no changes detected in the protein expression levels of total­ERK, phospho­v­akt murine thymoma viral oncogene homolog 1 (p­Akt) and total­Akt. The results of the present study suggest that Notch 2 is important for the cell growth, anti­apoptosis and metastasis of LSCC. Therefore, Notch 2 inhibitors may have therapeutic potential for the treatment of patients with LSCC via the inhibition of cancer cell growth and metastasis.

Downregulation of Notch1 induces apoptosis and inhibits cell proliferation and metastasis in laryngeal squamous cell carcinoma.

Notch signaling plays a key role in a wide variety of human tumors; it can be an oncogene or a tumor-suppressor gene depending on the tissue context. The functions of Notch1 in laryngeal squamous cell carcinoma (LSCC) are largely unknown. We investigated the role of Notch1 in LSCC cell growth, apoptosis and metastasis. We analyzed Notch1 expression in clinical LSCC samples using quantum dot immunohistochemistry (QD-IHC) and conventional IHC. Human laryngeal carcinoma HEp-2 cells were transfected with Notch1-specific short hairpin RNA (shRNA), and cell proliferation, apoptosis, and migration and invasion were evaluated using the cell counting assay, flow cytometry and wound healing and Transwell assays, respectively; western blotting was used to validate the expression of Notch1 target genes. Compared with normal tissues, Notch1 was upregulated in LSCC tissues; compared with LSCC tissues without metastasis, Notch1 upregulation was enhanced in LSCC tissues with metastasis (P<0.05). Transfection downregulated Notch1 mRNA and protein expression levels in the Notch1 shRNA group. There was a significantly greater decrease in cell proliferation in the Notch1 shRNA group than cell proliferation in the non-transfected (P<0.05) and negative shRNA groups (P<0.05). Furthermore, Notch1 knockdown induced apoptosis in the HEp-2 cells. Additionally, the number of migrated and invasive cells in the Notch1 shRNA group was decreased (P<0.05). Notch1 knockdown in the HEp-2 cells greatly inhibited phosphorylated extracellular signal-related kinase (p-ERK), phosphorylated protein kinase B (p-AKT), c-Myc, Bcl-2, p21, cyclin D1, cyclin-dependent kinase 4 (CDK4) and cyclin E expression levels and increased Bax expression. Altogether, our findings indicate that Notch1 expression is increased in human LSCC and correlates with tumorigenesis and metastasis, while in HEp-2 cells, Notch1 knockdown inhibited cell growth, induced apoptosis and inhibited migration and invasion by regulating Notch1 target genes, suggesting it may be a potential therapeutic target for treating LSCC.

[Prediction of chlorophyll content of greenhouse tomato using wavelet transform combined with NIR spectra].

In quantitative analysis of spectral data, noises and background interference always degrade the accuracy of spectral feature extraction. The wavelet transform is multi-scale decomposition used to reduce the noise and improve the analysis precision. On the other hand, the wavelet transform denoising is often followed by destroying the efficiency information. The present research introduced two indexes to control the scale of decomposition, the smoothness index (SI) and the time shift index (TSI). When the parameters satisfied TSI < 0.01 and SI > 0.100 4, the noise of spectral characteristic was reduced. In the meanwhile, the reflection peaks of biochemical components were reserved. Through analyzing the correlation between denoised spectrum and chlorophyll content, some spectral characteristics parameters reflecting the changing tendency of chlorophyll content were chosen. Finally, the partial least squares regression (PLSR) was used to develop the prediction model of the chlorophyll content of tomato leaf. The result showed that the predictiong model, which used the values of absorbance at 366, 405, 436, 554, 675 and 693 nm as input variables, had higher predictive ability (calibration coefficient was 0. 892 6, and validation coefficient was 0.829 7) and better potential to diagnose tomato growth in greenhouse.