Glucose Fluctuation Inhibits Nrf2 Signaling Pathway in Hippocampal Tissues and Exacerbates Cognitive Impairment in Streptozotocin-Induced Diabetic Rats.

Background: This research investigated whether glucose fluctuation (GF) can exacerbate cognitive impairment in streptozotocin-induced diabetic rats and explored the related mechanism. Methods: After 4 weeks of feeding with diets containing high fats plus sugar, the rat model of diabetes mellitus (DM) was established by intraperitoneal injection of streptozotocin (STZ). Then, GF was triggered by means of alternating satiety and starvation for 24 h. The weight, blood glucose level, and water intake of the rats were recorded. The Morris water maze (MWM) test was carried out to appraise the cognitive function at the end of week 12. Moreover, the morphological structure of hippocampal neurons was viewed through HE and Nissl staining, and transmission electron microscopy (TEM) was performed for ultrastructure observation. The protein expression levels of Nrf2, HO-1, NQO-1, Bax, Bcl-2, and Caspase-3 in the hippocampal tissues of rats were measured via Western blotting, and the mRNA expressions of Nrf2, HO-1, and NQO-1 were examined using qRT-PCR. Finally, Western blotting and immunohistochemistry were conducted to detect BDNF levels. Results: It was manifested that GF not only aggravated the impairment of spatial memory in rats with STZ-induced type 2 DM but also stimulated the loss, shrinkage, and apoptosis of hippocampal neurons. Regarding the expressions in murine hippocampal tissues, GF depressed Nrf2, HO-1, NQO-1, Bcl-2, and BDNF but boosted Caspase-3 and Bax. Conclusions: GF aggravates cognitive impairment by inhibiting the Nrf2 signaling pathway and inducing oxidative stress and apoptosis in the hippocampal tissues.

A case of hypophysis with HIV negative cryptococcal meningitis. / 垂体功能减退症伴HIV阴性的隐球菌性脑膜炎1例.

The clinical mortality of cryptococcal meningitis (CM) is high. There is no report of hypopituitarism associated with HIV negative CM so far. The patients with hypopituitarism complicated with CM are easy to be misdiagnosed and mistreated. A patient with hypopituitarism and HIV negative CM was admitted to Weihai Municipal Hospital on August 27, 2021. The patient was treated for 18 years after craniopharyngioma with headache for more than 2 months, nausea and vomiting for 4 days. MRI showed abnormal enhancement of the right basal ganglia, edema of surrounding tissue, and multiple striated enhancement of the bilateral cerebellar hemisphere. The smear of cerebrospinal fluid showed a large number of fungi and Cryptococcus. Culture of cerebrospinal fluid showed positive in Cryptococcus. The patient's HIV and syphilis antibodies were negative. The condition of the patient was improved after active antifungal therapy. The clinician should make a definite diagnosis and give early treatment as soon as possible.

Prediction of Tumor Mutation Load in Colorectal Cancer Histopathological Images Based on Deep Learning.

Colorectal cancer (CRC) is one of the most prevalent malignancies, and immunotherapy can be applied to CRC patients of all ages, while its efficacy is uncertain. Tumor mutational burden (TMB) is important for predicting the effect of immunotherapy. Currently, whole-exome sequencing (WES) is a standard method to measure TMB, but it is costly and inefficient. Therefore, it is urgent to explore a method to assess TMB without WES to improve immunotherapy outcomes. In this study, we propose a deep learning method, DeepHE, based on the Residual Network (ResNet) model. On images of tissue, DeepHE can efficiently identify and analyze characteristics of tumor cells in CRC to predict the TMB. In our study, we used ×40 magnification images and grouped them by patients followed by thresholding at the 10th and 20th quantiles, which significantly improves the performance. Also, our model is superior compared with multiple models. In summary, deep learning methods can explore the association between histopathological images and genetic mutations, which will contribute to the precise treatment of CRC patients.

Physiological Functions of FBW7 in Metabolism.

FBW7 is the recognition subunit of the SCF (Skp1-Cullin1-F-box proteins) E3 ubiquitin ligase complex, and it determines the specificity of the SCF substrate. SCFFBW7 is a recognized tumor suppressor because of its ability to degrade many proto-oncogenic substrates. Recent studies have shown that FBW7 plays a key role in metabolism by targeting the degradation of critical regulators involved in cellular metabolism in a ubiquitin-dependent manner. Here, we review recent studies, which highlight the important role of FBW7 in metabolism.

Prediction of Target-Drug Therapy by Identifying Gene Mutations in Lung Cancer With Histopathological Stained Image and Deep Learning Techniques.

Lung cancer is a kind of cancer with high morbidity and mortality which is associated with various gene mutations. Individualized targeted-drug therapy has become the optimized treatment of lung cancer, especially benefit for patients who are not qualified for lung lobectomy. It is crucial to accurately identify mutant genes within tumor region from stained pathological slice. Therefore, we mainly focus on identifying mutant gene of lung cancer by analyzing the pathological images. In this study, we have proposed a method by identifying gene mutations in lung cancer with histopathological stained image and deep learning to predict target-drug therapy, referred to as DeepIMLH. The DeepIMLH algorithm first downloaded 180 hematoxylin-eosin staining (H&E) images of lung cancer from the Cancer Gene Atlas (TCGA). Then deep convolution Gaussian mixture model (DCGMM) was used to perform color normalization. Convolutional neural network (CNN) and residual network (Res-Net) were used to identifying mutated gene from H&E stained imaging and achieved good accuracy. It demonstrated that our method can be used to choose targeted-drug therapy which might be applied to clinical practice. More studies should be conducted though.

Identification and Validation of Efficacy of Immunological Therapy for Lung Cancer From Histopathological Images Based on Deep Learning.

Cancer immunotherapy, as a novel treatment against cancer metastasis and recurrence, has brought a significantly promising and effective therapy for cancer treatments. At present, programmed death 1 (PD-1) and programmed cell death-Ligand 1 (PD-L1) treatment for lung cancer is primarily recognized as an immune checkpoint inhibitor (ICI) to play an anti-tumor effect; however, it remains uncertain regarding of its efficacy though. Thereafter, tumor mutation burden (TMB) was recognized as a high-potential to be a predictive marker for the immune therapy, but it is invasive and costly. Therefore, discovering more immune-related biomarkers that have a guiding role in immunotherapy is a crucial step in the development of immunotherapy. In our study, we proposed a deep convolutional neural network (CNN)-based framework, DeepLRHE, which can efficiently analyze immunological stained pathological images of lung cancer tissues, as well as to identify and explore pathogenesis which can be used for immunological treatment in clinical field. In this study, we used 180 whole slice images (WSIs) of lung cancer downloaded from TCGA which was model training and validation. After two cross-validation used for this model, we compared with the area under the curve (AUC) of multiple mutant genes, TP53 had highest AUC, which reached 0.87, and EGFR, DNMT3A, PBRM1, STK11 also reached ranged from 0.71 to 0.84. The study results showed that the deep learning can used to assist health professionals for target-therapy as well as immunotherapies, therefore to improve the disease prognosis.

Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram.

BACKGROUND: Lung cancer is the most commonly diagnosed cancer worldwide. Its survival rate can be significantly improved by early screening. Biomarkers based on radiomics features have been found to provide important physiological information on tumors and considered as having the potential to be used in the early screening of lung cancer. In this study, we aim to establish a radiomics model and develop a tool to improve the discrimination between benign and malignant pulmonary nodules. METHODS: A retrospective study was conducted on 875 patients with benign or malignant pulmonary nodules who underwent computed tomography (CT) examinations between June 2013 and June 2018. We assigned 612 patients to a training cohort and 263 patients to a validation cohort. Radiomics features were extracted from the CT images of each patient. Least absolute shrinkage and selection operator (LASSO) was used for radiomics feature selection and radiomics score calculation. Multivariate logistic regression analysis was used to develop a classification model and radiomics nomogram. Radiomics score and clinical variables were used to distinguish benign and malignant pulmonary nodules in logistic model. The performance of the radiomics nomogram was evaluated by the area under the curve (AUC), calibration curve and Hosmer-Lemeshow test in both the training and validation cohorts. RESULTS: A radiomics score was built and consisted of 20 features selected by LASSO from 1288 radiomics features in the training cohort. The multivariate logistic model and radiomics nomogram were constructed using the radiomics score and patients' age. Good discrimination of benign and malignant pulmonary nodules was obtained from the training cohort (AUC, 0.836; 95% confidence interval [CI]: 0.793-0.879) and validation cohort (AUC, 0.809; 95% CI: 0.745-0.872). The Hosmer-Lemeshow test also showed good performance for the logistic regression model in the training cohort (P = 0.765) and validation cohort (P = 0.064). Good alignment with the calibration curve indicated the good performance of the nomogram. CONCLUSIONS: The established radiomics nomogram is a noninvasive preoperative prediction tool for malignant pulmonary nodule diagnosis. Validation revealed that this nomogram exhibited excellent discrimination and calibration capacities, suggesting its clinical utility in the early screening of lung cancer.

Body Mass Index Trajectories During Young Adulthood and Incident Hypertension: A Longitudinal Cohort in Chinese Population.

Background This longitudinal study aims to characterize longitudinal body mass index ( BMI ) trajectories during young adulthood (20-40 years) and examine the impact of level-independent BMI trajectories on hypertension risk. Methods and Results The cohort consisted of 3271 participants (1712 males and 1559 females) who had BMI and blood pressure ( BP ) repeatedly measured 4 to 11 times during 2004 to 2015 and information on incident hypertension. Four distinct trajectory groups were identified using latent class growth mixture model: low-stable (n=1497), medium-increasing (n=1421), high-increasing (n=291), sharp-increasing (n=62). Model-estimated levels and linear slopes of BMI at each age point between ages 20 and 40 were calculated in 1-year intervals using the latent class growth mixture model parameters and their first derivatives, respectively. Compared with the low-stable group, the hazard ratios and 95% CI were 2.42 (1.88, 3.11), 4.25 (3.08, 5.87), 11.17 (7.60, 16.41) for the 3 increasing groups, respectively. After adjusting for covariates, the standardized odds ratios and 95% CI of model-estimated BMI level for incident hypertension increased in 20 to 35 years, ranging from 0.80 (0.72-0.90) to 1.59 (1.44-1.75); then decreased gradually to 1.54 (1.42-1.68). The standardized odds ratio s of level-adjusted linear slopes increased from 1.22 (1.09-1.37) to 1.79 (1.59-2.01) at 20 to 24 years; then decreased rapidly to 1.12 (0.95-1.32). Conclusions These results indicate that the level-independent BMI trajectories during young adulthood have significant impact on hypertension risk. Age between 20 and 30 years is a crucial period for incident hypertension, which has implications for early prevention.

Helicobacter pylori with East Asian-type cagPAI genes is more virulent than strains with Western-type in some cagPAI genes

Abstract The severity of Helicobacter pylori-related disease is correlated with the presence and integrity of a cag pathogenicity island (cagPAI). cagPAI genotype may have a modifying effect on the pathogenic potential of the infecting strain. After analyzing the sequences of cagPAI genes, some strains with the East Asian-type cagPAI genes were selected for further analysis to examine the association between the diversity of the cagPAI genes and the virulence of H. pylori. The results showed that gastric mucosal inflammatory cell infiltration was significantly higher in patients with East Asian-type cagPAI genes H. pylori strain compared with mosaicism cagPAI genes H. pylori strain (p < 0.05). H. pylori strains with the East Asian-type cagPAI genes were closely associated with IL-8 secretion in vitro and in vivo compared with H. pylori strains with the mosaicism cagPAI genes (p < 0.01). H. pylori strains with East Asian-type cagPAI genes are able to strongly translocate CagA to host cells. These results suggest that H. pylori strains with East Asian-type cagPAI genes are more virulent than the strains of cagPAI gene/genes that are Western type.

Helicobacter pylori with the Intact dupA Cluster is more Virulent than the Strains with the Incomplete dupA Cluster.

The duodenal ulcer promoting gene (dupA), located in the plasticity region of Helicobacter pylori (H. pylori), is predicted to form a type IV secretory system (T4SS) with vir genes around dupA. In the study, we investigated the association between the dupA cluster status and the virulence of H. pylori in a littoral region of Northeast China. Two hundred and sixty-two H. pylori strains isolated from the chronic gastritis were examined to evaluate the dupA cluster status, cag PAI genes and vacA genotype using PCR and Western blot. Histopathologic evaluations of biopsy specimens were performed to analysis the association between the dupA cluster and the inflammatory response. IL-8 productions in gastric mucosa and from GES-1 cells co-cultured with H. pylori were measured, respectively, to analysis the association between the dupA cluster status and IL-8 production. We found that gastric mucosal inflammatory cell infiltration was significantly higher in patients with dupA-positive H. pylori, including H. pylori with complete dupA cluster (2.71 ± 0.79) and incomplete dupA cluster (2.09 ± 0.61) than in patients with dupA-negative strain (1.73 ± 0.60, p < 0.01), whereas no significant difference in the gastric mucosal atrophy was found according to the status of dupA cluster. Gastric mucosal IL-8 levels were higher in the complete dupA cluster group than in other groups (p < 0.01), and IL-8 production from GES-1 cells was also significantly higher in strains with a complete dupA cluster (1527.9 ± 180.0 pg/ml) than in those with an incomplete dupA cluster (1229.4 ± 75.3 pg/ml, p < 0.01) or those with dupA negative (1201.9 ± 92.3 pg/ml, p < 0.01). In conclusion, the complete dupA cluster in H. pylori is associated with inflammatory cell infiltration and IL-8 secretion, and H. pylori strain with a complete dupA cluster seems to be more virulent than other strains with the incomplete dupA cluster or dupA negative.

Intact long-type DupA protein in Helicobacter pylori is an ATPase involved in multifunctional biological activities.

The function of intact long-type DupA protein in Helicobacter pylori was analyzed using immunoblotting and molecular biology techniques in the study. After cloning, expression and purification, ATPase activity of DupA protein was detected. Antibody was produced for localization and interaction proteins analysis. The dupA-deleted mutant was generated for adhesion and CagA protein translocation assay, susceptibility to different pH, IL-8 secretion assay, cytotoxicity to MKN-45 cells and proteins-involved apoptosis analysis. DupA protein exhibited an ATPase activity (129.5±17.8 U/mgprot) and located in bacterial membrane, while it did not involve the adhesion and CagA protein delivery of H. pylori. DupA protein involved the urease secretion as the interaction proteins. The wild type strain had a stronger growth in low pH than the dupA-deleted mutant (p < 0.001). IL-8 productions from GES-1 cells infected with the wild type strain were significantly higher than from those with the mutant (p < 0.001). The amounts of vital MKN-45 cells were decreased and the numbers of apoptotic cells were increased with the wild type strain, compared to those with the mutant after 12 h (p < 0.05). The increase of cleaved Caspase-3 and Bax was significantly higher and the decrease of Bcl-2 was more obvious in MKN-45 cells exposed to the wild type strain than that exposed to the mutant after 6 h. We demonstrate that intact long-type DupA protein located in membrane as ATPase is a true virulence factor associated with duodenal ulcer development involving the IL-8 induction and urease secretion, while it inhibits gastric cancer cell growth in vitro by activating the mitochondria-mediated apoptotic pathway.