Cryptococcosis in patients with liver cirrhosis: Death risk factors and predictive value of prognostic models

BACKGROUND

Liver cirrhosis is associated with immune deficiency, which causes these patients to be susceptible to various infections, including cryptococcus infection. Mortality in cirrhotic patients with cryptococcosis has increased. The present study was to explore the risk factors of mortality and the predictive ability of different prognostic models.

METHODS

Forty-seven cirrhotic patients with cryptococcosis at a tertiary care hospital were included in this retrospective study. Data on demographics, clinical parameters, laboratory exams, diagnostic methods, medication during hospitalization, severity scores and prognosis were collected and analyzed. Student's t test and Mann-Whitney test were used to compare characteristics of survivors and non-survivors at a 90-day follow-up and cerebrospinal fluid (CSF) manifestations of cryptococcal meningitis. Multivariate Cox regression analysis was used to identify the independent risk factors for mortality. Kaplan-Meier curves were used to analyze patient survival. Receiver operating characteristic (ROC) curves were used to evaluate the different prognostic factors.

RESULTS

The 30- and 90-day survival rates were 93.6% and 80.9%, respectively, in cirrhotic patients with cryptococcosis. Cryptogenic liver diseases [hazard ratio (HR) = 7.567, 95% confidence interval (CI): 1.616-35.428, P = 0.010], activated partial thromboplastin time (APTT) (HR = 1.117, 95% CI: 1.016-1.229, P = 0.022) and Child-Pugh score (HR = 2.146, 95% CI: 1.314-3.504, P = 0.002) were risk factors for 90-day mortality in cirrhotic patients with cryptococcosis. Platelet count (HR = 0.965, 95% CI: 0.940-0.991, P = 0.008) was a protective factor. APTT (HR = 1.120, 95% CI: 1.044-1.202, P = 0.002) and Child-Pugh score (HR = 1.637, 95% CI: 1.086-2.469, P = 0.019) were risk factors for 90-day mortality in cirrhotic patients with cryptococcal meningitis. There was significant difference in the percentage of lymphocytes in CSF between survivors and non-survivors [60.0 (35.0-75.0) vs. 95.0 (83.8-97.2), P < 0.001]. The model of end-stage liver disease-sodium (MELD-Na) score was more accurate for predicting 30-day mortality both in patients with cryptococcosis [area under curve (AUC): 0.826, 95% CI: 0.618-1.000] and those with cryptococcal meningitis (AUC: 0.742, 95% CI: 0.560-0.924); Child-Pugh score was more useful for predicting 90-day mortality in patients with cryptococcosis (AUC: 0.823, 95% CI: 0.646-1.000) and those with cryptococcal meningitis (AUC: 0.815, 95% CI: 0.670-0.960).

CONCLUSIONS

These results showed that cryptogenic liver diseases, APTT and Child-Pugh score were associated with mortality in cirrhotic patients with cryptococcosis and cryptococcal meningitis. MELD-Na score was important for predicting 30-day mortality, and Child-Pugh score was critical for predicting 90-day mortality.

Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis

BACKGROUND

Efforts should be made to develop a deep-learning diagnosis system to distinguish pancreatic cancer from benign tissue due to the high morbidity of pancreatic cancer.

AIM

To identify pancreatic cancer in computed tomography (CT) images automatically by constructing a convolutional neural network (CNN) classifier.

METHODS

A CNN model was constructed using a dataset of 3494 CT images obtained from 222 patients with pathologically confirmed pancreatic cancer and 3751 CT images from 190 patients with normal pancreas from June 2017 to June 2018. We established three datasets from these images according to the image phases, evaluated the approach in terms of binary classification (i.e., cancer or not) and ternary classification (i.e., no cancer, cancer at tail/body, cancer at head/neck of the pancreas) using 10-fold cross validation, and measured the effectiveness of the model with regard to the accuracy, sensitivity, and specificity.

RESULTS

The overall diagnostic accuracy of the trained binary classifier was 95.47%, 95.76%, 95.15% on the plain scan, arterial phase, and venous phase, respectively. The sensitivity was 91.58%, 94.08%, 92.28% on three phases, with no significant differences (χ² = 0.914, P = 0.633). Considering that the plain phase had same sensitivity, easier access, and lower radiation compared with arterial phase and venous phase , it is more sufficient for the binary classifier. Its accuracy on plain scans was 95.47%, sensitivity was 91.58%, and specificity was 98.27%. The CNN and board-certified gastroenterologists achieved higher accuracies than trainees on plain scan diagnosis (χ² = 21.534, P < 0.001; χ² = 9.524, P < 0.05; respectively). However, the difference between CNN and gastroenterologists was not significant (χ² = 0.759, P = 0.384). In the trained ternary classifier, the overall diagnostic accuracy of the ternary classifier CNN was 82.06%, 79.06%, and 78.80% on plain phase, arterial phase, and venous phase, respectively. The sensitivity scores for detecting cancers in the tail were 52.51%, 41.10% and, 36.03%, while sensitivity for cancers in the head was 46.21%, 85.24% and 72.87% on three phases, respectively. Difference in sensitivity for cancers in the head among the three phases was significant (χ² = 16.651, P < 0.001), with arterial phase having the highest sensitivity.

CONCLUSION

We proposed a deep learning-based pancreatic cancer classifier trained on medium-sized datasets of CT images. It was suitable for screening purposes in pancreatic cancer detection.

Role of γδT cells in liver diseases and its relationship with intestinal microbiota

γδT cells are unconventional T lymphocytes that bridge innate and adaptive immunity. Based on the composition of T cell receptor and the cytokines produced, γδT cells can be divided into diverse subsets that may be present at different locations, including the liver, epithelial layer of the gut, the dermis and so on. Many of these cells perform specific functions in liver diseases, such as viral hepatitis, autoimmune liver diseases, non-alcoholic fatty liver disease, liver cirrhosis and liver cancers. In this review, we discuss the distribution, subsets, functions of γδT cells and the relationship between the microbiota and γδT cells in common hepatic diseases. As γδT cells have been used to cure hematological and solid tumors, we are interested in γδT cell-based immunotherapies to treat liver diseases.

SiRNA-mediated serotonin transporter knockdown in the dorsal raphe nucleus rescues single prolonged stress-induced hippocampal autophagy in rats

The neurobiological mechanisms underlying the development of post-traumatic stress disorder (PTSD) remain elusive. One of the hypotheses is the dysfunction of serotonin (5-HT) neurotransmission, which is critically regulated by serotonin transporter (SERT). Therefore, we hypothesized that attenuation of SERT gene expression in the hippocampus could prevent hippocampal autophagy and the development of PTSD-like behavior. To this end, we infused SLC6A4 siRNAs into the dorsal raphe nucleus (DRN) to knockdown SERT gene expression after a single prolonged stress (SPS) treatment in rats. Then, we evaluated the effects of SERT gene knockdown on anxiety-related behaviors and extinction of contextual fear memory. We also examined the histological changes and the expression of Beclin-1, LC3-I, and LC3-II in the hippocampus. We found that SPS treatment did not alter anxiety-related behaviors but prolonged the extinction of contextual fear memory, and such a behavioral phenomenon was correlated with increased hippocampal autophagy, decreased 5-HT level, and increased expression of Beclin-1 and LC3-II/LC3-I ratio in the hippocampus. Furthermore, intra-DRN infusion of SLC6A4 siRNAs promoted the extinction of contextual fear memory, prevented hippocampal autophagy, increased 5-HT level, and decreased expression of Beclin-1 and LC3-II/LC3-I ratio. These results indicated that SERT may play a critical role in the pathogenesis of hippocampal autophagy, and is likely involved in the development of PTSD.

Induction of antitumor immunity with combination of HER2/neu DNA vaccine and interleukin 2 gene-modified tumor vaccine

The therapeutic effects of both cytokine-secreting tumor vaccine and DNA vaccine were studied using mouse MBT-2 bladder cancer cells as a model. Cytokine-secreting MBT-2 cells were obtained by infecting cells with retroviral particles containing interleukin (IL) 2-, IL-4-, or granulocyte-macrophage colony-stimulating factor (GM-CSF)-expression vector. The MBT-2-IL-2 cells were not tumorigenic in syngenic C3H mice at all. Tumor formation decreased significantly for the MBT-2-GM-CSF cells. MBT-2-IL-2, -IL-4, and -GM-CSF cells were killed by irradiation and tested as tumor vaccines. The irradiated MBT2-IL-2 cells could complete protect mice from the growth of the preexisting tumor cells, and the immune memory lasted for 8 months. On the other hand, irradiated MBT-2-IL-4 and MBT-2-GM-CSF cells were less effective. When the loading tumor mass increased, all tumor vaccines lost protective effects. DNA vaccine encoding the tumor antigen neu was additionally tested to improve the therapeutic efficacy. Coinjection of 60 microg pSV-neu DNA was effective in enhancing the antitumor effects of MBT2-IL-2; however, DNA vaccine alone cannot prevent the progression of the preexisting tumor. Immunohistochemical analysis of tumor infiltrate revealed massive increase of CD4+ lymphoid cells in the group of mice treated with both DNA vaccine and IL-2-secreted tumor vaccine. Western blotting demonstrated the presence of anti-neu antibody in the serum from immunized mice. In contrast, combination of DNA vaccine and MBT-2-GM-CSF has no additive effect. The results indicate the combination of DNA vaccine and IL-2-secreting tumor vaccine can additionally improve therapeutic efficacy, and the efficacy is correlated with the increase of CD4+ T lymphocytes and anti-neu antibody.

Continuous deformation versus faulting through the continental lithosphere of new zealand

Seismic anisotropy and P-wave delays in New Zealand imply widespread deformation in the underlying mantle, not slip on a narrow fault zone, which is characteristic of plate boundaries in oceanic regions. Large magnitudes of shear-wave splitting and orientations of fast polarization parallel to the Alpine fault show that pervasive simple shear of the mantle lithosphere has accommodated the cumulative strike-slip plate motion. Variations in P-wave residuals across the Southern Alps rule out underthrusting of one slab of mantle lithosphere beneath another but permit continuous deformation of lithosphere shortened by about 100 kilometers since 6 to 7 million years ago.

Source Parameters for Stick-Slip and for Earthquakes

Source parameters of stick-slip friction events measured in the laboratory show particle and rupture propagation velocities which are similar to those observed for earthquakes and inferred from seismic source theory. This dynamic similarity strongly supports the idea that stick-slip is the mechanism for shallow earthquakes.