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Ecological drought monitoring is important for regional status assessment and protection of water resources. In this study, we constructed a new ecological drought index, the kernel temperature vegetation drought index (kTVDI), by using the kernel normalized vegetation index (kNDVI) to improve the temperature vegetation drought index (TVDI) in Inner Mongolia. We further analyzed the spatial and temporal distribution of ecological drought in Inner Mongolia during 2000-2022 and the future trend of ecological drought by using segmented linear regression model, Theil-Sen median, Mann-Kendall test, and Hurst index. The results showed that kTVDI performed better in monitoring ecological drought than TVDI. From 2000 to 2022, kTVDI showed a decreasing trend in the growing season in Inner Mongolia, but the change was not significant, and a sudden change occurred in 2016, and the wetting trend after the sudden change was more obvious. During the study period, ecological drought in 23.6% of the areas of Inner Mongolia showed an aggravating trend, and ecological drought was alleviated in 46.5% of the area. In the future, ecological drought would be exacerbated in the eastern part but alleviated in the central and western parts of Inner Mongolia.

Asunto(s)

Cambio Climático , Sequías , Temperatura , Estaciones del Año , China , Predicción , Ecosistema

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PURPOSE: The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 index and GGG of PCa. METHODS: A total of 122 patients with pathologically proven PCa who had undergone preoperative MRI were retrospectively included. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Then, recursive feature elimination (RFE) was applied to remove redundant features. ML models for predicting Ki67 expression and GGG were constructed based on bpMRI and different algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN). The performances of different models were evaluated with receiver operating characteristic (ROC) analysis. In addition, a joint analysis of Ki67 expression and GGG was performed by assessing their Spearman correlation and calculating the diagnostic accuracy for both indices. RESULTS: The ML model based on LR and ADC + T2 (LR_ADC + T2, AUC = 0.8882) performed best in predicting Ki67 expression, and ADC_wavelet-LHH_firstorder_Maximum had the highest feature weighting. The SVM_DWI + T2 (AUC = 0.9248) performed best in predicting GGG, and DWI_wavelet HLL_glcm_SumAverage had the highest feature weighting. The Ki67 and GGG exhibited a weak positive correlation (r = 0.382, p < 0.001), and LR_ADC + DWI had the highest diagnostic accuracy in predicting both (0.6230). CONCLUSION: The proposed ML models are suitable for predicting both Ki67 expression and GGG in PCa. This algorithm could be used to identify indolent or invasive PCa with a noninvasive, repeatable, and accurate diagnostic method.

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The most common cause of hepatocellular carcinoma (HCC) is chronic hepatitis and cirrhosis. It is proposed that precancerous lesions of HCC include all stages of the disease, from dysplastic foci (DF), and dysplastic nodule (DN), to early HCC (eHCC) and progressed HCC (pHCC), which is a complex multi-step process. Accurately identifying precancerous hepatocellular lesions can significantly impact the early detection and treatment of HCC. The changes in high-grade dysplastic nodules (HGDN) were similar to those seen in HCC, and the risk of malignant transformation significantly increased. Nevertheless, it is challenging to diagnose precancerous lesions of HCC. We integrated the literature and combined imaging, pathology, laboratory, and other relevant examinations to improve the accuracy of the diagnosis of precancerous lesions.

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Peritoneal lymphomatosis is extremely rare and associated with poor prognosis. Most practitioners only pay more attention to peritoneal carcinomatosis. However, peritoneal lymphomatosis can be neglected and misdiagnosed. We report a teenager with 10 days of abdominal distension and pain accompanied by computed tomography scan suggesting diffuse thickening of the peritoneum and omentum and abdominopelvic effusion. Tuberculous peritonitis and peritoneal carcinomatosis were initially suspected. However, it was finally confirmed as non-Hodgkin's B-cell lymphoma by omentum biopsies. He achieved complete remission after chemotherapy and autologous stem cell transplantation. But unfortunately, he suffered a relapse and died 10 months after diagnosis. Following a review of the literature, it can be concluded that the discovery of lymphomatosis in peritoneum is a rare finding. Lymphoma should be considered in the differential diagnosis of unexplained peritoneal thickening on computed tomography, and this case emphasizes the importance of early pathological diagnosis to make sure that the right treatment can be started opportunely.

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The present study aimed to investigate the expression and regulation of microRNA-193b (miR-193b) in tissues and cells from esophageal cancer and Barrett's esophagus (BE). Surgical biopsies of esophageal lesions and adjacent normal tissues were obtained, and the miR­193b expression and promoter methylation status were examined. Human BE and esophageal cancer cells were analyzed for miR­193b expression and promoter methylation, with or without treatment with the hypomethylating agent 5­azacytidine. Immunohistochemistry was performed to determine the expression and distribution of Kirsten rat sarcoma viral oncogene homolog (K­Ras), a target of miR­193b. miR­193b expression was significantly downregulated in BE and esophageal cancer tissues compared with corresponding normal tissues. The miR­193b level was significantly reduced in esophageal cancer compared with BE tissue. 5­Azacytidine treatment resulted in a significant upregulation of miR­193b in BE and esophageal cancer cells. Methylation­specific polymerase chain reaction analysis and bisulfite pyrosequencing confirmed hypermethylation of miR­193b promoter regions in esophageal cancer and BE cells, whereas hypermethylation was not observed in normal esophageal squamous epithelial cells. The methylation rate in BE and esophageal cancer tissues was significantly increased compared with the adjacent normal esophageal tissues. BE and esophageal cancer tissues exhibited increased K­Ras protein expression levels compared with the adjacent normal tissues. To the best of our knowledge, this is the first report describing DNA methylation-mediated silencing of miR­193b in esophageal cancer and BE tissues.

Asunto(s)

Adenocarcinoma/genética , Esófago de Barrett/genética , Metilación de ADN , Neoplasias Esofágicas/genética , MicroARNs/genética , Adulto , Anciano , Azacitidina/farmacología , Biomarcadores de Tumor , Línea Celular Tumoral , Regulación hacia Abajo , Femenino , Regulación Neoplásica de la Expresión Génica/efectos de los fármacos , Genes ras , Humanos , Inmunohistoquímica , Masculino , Persona de Mediana Edad , Regiones Promotoras Genéticas