Changes in immune status of circulating NK cells in patients with latent tuberculosis infection.

Introduction: The presence of patients with latent tuberculosis infection (LTBI) has fueled the tuberculosis pandemic. We aimed to investigate the immune status of NK cells in LTBI patients. Material and methods: Twenty-one LTBI patients, 25 active pulmonary tuberculosis (APTB) patients and 25 healthy controls (HCs) participated in our research. The markers of NK cells were detected by flow cytometry. Results: The absolute number of circulating CD56bright and CD56dim NK cells in LTBI patients was higher than that of APTB patients, but the frequency of HLA-DR+ CD56bright NK cells was significantly lower than that of HCs and APTB patients. Also, LTBI patients with CD56bright NK cells had intracellular levels of granzyme B that were as significantly elevated as those with APTB patients, but the levels of granzyme A and perforin were reduced. Meanwhile, the frequencies of CXCR3+ NK cells, CXCR3+ CD56bright and CXCR3+ CD56dim NK cells were significantly lower in LTBI patients. Conclusions: Circulating CD56bright NK cells exerted a significant role in maintaining immune balance in LTBI patients. An elevated frequency of granzyme B+ CD56bright NK cells and a reduced frequency of perforin+ CD56bright NK cells were effective in differentiating LTBI patients from HCs.

The Influence of Different Knowledge-Driven Methods on Landslide Susceptibility Mapping: A Case Study in the Changbai Mountain Area, Northeast China.

Landslides are one of the most frequent geomorphic hazards, and they often result in the loss of property and human life in the Changbai Mountain area (CMA), Northeast China. The objective of this study was to produce and compare landslide susceptibility maps for the CMA using an information content model (ICM) with three knowledge-driven methods (the artificial hierarchy process with the ICM (AHP-ICM), the entropy weight method with the ICM (EWM-ICM), and the rough set with the ICM (RS-ICM)) and to explore the influence of different knowledge-driven methods for a series of parameters on the accuracy of landslide susceptibility mapping (LSM). In this research, the landslide inventory data (145 landslides) were randomly divided into a training dataset: 70% (81 landslides) were used for training the models and 30% (35 landslides) were used for validation. In addition, 13 layers of landslide conditioning factors, namely, altitude, slope gradient, slope aspect, lithology, distance to faults, distance to roads, distance to rivers, annual precipitation, land type, normalized difference vegetation index (NDVI), topographic wetness index (TWI), plan curvature, and profile curvature, were taken as independent, causal predictors. Landslide susceptibility maps were developed using the ICM, RS-ICM, AHP-ICM, and EWM-ICM, in which weights were assigned to every conditioning factor. The resultant susceptibility was validated using the area under the ROC curve (AUC) method. The success accuracies of the landslide susceptibility maps produced by the ICM, RS-ICM, AHP-ICM, and EWM-ICM methods were 0.931, 0.939, 0.912, and 0.883, respectively, with prediction accuracy rates of 0.926, 0.927, 0.917, and 0.878 for the ICM, RS-ICM, AHP-ICM, and EWM-ICM, respectively. Hence, it can be concluded that the four models used in this study gave close results, with the RS-ICM exhibiting the best performance in landslide susceptibility mapping.

Comparison of Third-Generation Sequencing Technology and Traditional Microbiological Detection in Pathogen Diagnosis of Lower Respiratory Tract Infection.

BACKGROUND: It is common to obtain a low detection rate and unsatisfactory detection results in complex infection or rare pathogen detection. This retrospective study aimed to illustrate the application value and prospect of the third-generation sequencing technology in lower respiratory tract infection disease. METHODS: This study recruited 70 patients with lower respiratory tract infection (LRTI). Pathogen detection of bronchoalveolar lavage fluid (BALF) from all patients was performed using nanopore metagenomic sequencing technology and traditional culture. BALF culture combined with quantitiative PCR (qPCR) was used as a reference standard to analyze the sensitivity and specificity of nanopore sequencing technology. The current study also collected the examination results of enrolled samples using technical methods sputum culture, tuberculosis DNA (TB-DNA), and Xpert MTB/RIF and analyzed the detection efficiency of nanopore sequencing for Mycobacterium tuberculosis. RESULTS: The positive rates of pathogens in 70 BALF samples detected by conventional culture and nanopore sequencing were 25.71% and 84.29%, respectively. Among the 59 positive BALF cases using nanopore sequencing, a total of 31 pathogens were identified, of which the proportions of bacteria, fungi, viruses, and other pathogens were 50%, 17%, 32%, and 1%, respectively. Using the results combined with culture and qPCR detection methods as the standard, the pathogen detection of BALF using nanopore sequencing had a sensitivity of 70% and a specificity of 91.7%. Additionally, the positive rate of the detection of M. tuberculosis using nanopore sequencing was 33.3% (6/18). The clinical medication plans of 74.3% (52/70) of the patients were referred to the nanopore sequencing results, of which 31 cases changed their treatment strategy, 21 supported the previous treatment plans, and 90% (47/52) of the patients finally had clinical improvement. CONCLUSIONS: BALF detection using nanopore sequencing technology improves the process of detecting pathogens in patients with LRTI, especially for M. tuberculosis, fungi, and viruses, by reducing the report time from three days to six hours. The clinical application prospect of nanopore sequencing technology is promising in the pathogen diagnosis of LRTI.

High Expression of ROMO1 Aggravates the Malignancy of Hepatoblastoma.

Hepatoblastoma (HB) is a kind of tumor that occurs frequently in children and is highly malignant. Here, the function of ROS modulator 1 (ROMO1) was identified in the development of HB. In this study, the mRNA expression of ROMO1 was measured by RT-qPCR. Colony formation assay, MTT assay, and flow cytometric analysis were applied to detect cell viability. The cell migrative and invasive ability was measured by wound healing and transwell assays. Tumor xenografts were performed to examine tumor growth. The results showed that upregulation of ROMO1 was identified in liver hepatocellular carcinoma (LIHC) tissues and predicted poor prognosis in LIHC patients. And ROMO1 expression was also increased in HB tissues and cells. Functionally, ROMO1 knockdown restrained cell viability, migration, and invasion in HB. In addition, knockdown of ROMO1 was found to suppress tumor formation in vivo. In conclusion, upregulation of ROMO1 promotes tumor growth and cell aggressiveness in HB.