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.

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.

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.

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.

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.

Orthostatic Hypotension Promotes the Progression From Mild Cognitive Impairment to Dementia in Type 2 Diabetes Mellitus.

CONTEXT: In type 2 diabetes mellitus (T2DM), orthostatic hypotension (OH) is associated with cognition, but the mechanisms governing the link between OH and cognition are still unclear. OBJECTIVE: We sought to analyze Alzheimer's disease (AD) biomarkers and the part of complement proteins in modulating the association of OH with cognitive impairment and examine whether OH could accelerate the clinical progression of mild cognitive impairment (MCI) to dementia in T2DM. METHODS: We recruited patients with T2DM with MCI and collected general healthy information and blood samples. Complement proteins of astrocyte-derived exosomes were isolated and AD biomarkers of neuronal cell-derived exosomes isolated were quantified by enzyme-linked immunosorbent assay. Cognitive assessments were performed at patient enrollment and follow-up. RESULTS: Mediation analysis showed that the influence of OH on cognition in T2DM was partly mediated by baseline AD biomarkers and complement proteins. Cox proportional-hazards regression proved the OH group had a higher risk of developing dementia compared to the T2DM without OH group. CONCLUSION: In T2DM with MCI patients, AD biomarkers and complement proteins mediate the effects of OH on cognitive impairment and OH may be a risk factor of progression from MCI to dementia in T2DM.

A Dual-Masked Deep Structural Clustering Network With Adaptive Bidirectional Information Delivery.

Structured clustering networks, which alleviate the oversmoothing issue by delivering hidden features from autoencoder (AE) to graph convolutional networks (GCNs), involve two shortcomings for the clustering task. For one thing, they used vanilla structure to learn clustering representations without considering feature and structure corruption; for another thing, they exhibit network degradation and vanishing gradient issues after stacking multilayer GCNs. In this article, we propose a clustering method called dual-masked deep structural clustering network (DMDSC) with adaptive bidirectional information delivery (ABID). Specifically, DMDSC enables generative self-supervised learning to mine deeper interstructure and interfeature correlations by simultaneously reconstructing corrupted structures and features. Furthermore, DMDSC develops an ABID module to establish an information transfer channel between each pairwise layer of AE and GCNs to alleviate the oversmoothing and vanishing gradient problems. Numerous experiments on six benchmark datasets have shown that the proposed DMDSC outperforms the most advanced deep clustering algorithms.

Multi-graph Fusion Graph Convolutional Networks with pseudo-label supervision.

Graph convolutional networks (GCNs) have become a popular tool for learning unstructured graph data due to their powerful learning ability. Many researchers have been interested in fusing topological structures and node features to extract the correlation information for classification tasks. However, it is inadequate to integrate the embedding from topology and feature spaces to gain the most correlated information. At the same time, most GCN-based methods assume that the topology graph or feature graph is compatible with the properties of GCNs, but this is usually not satisfied since meaningless, missing, or even unreal edges are very common in actual graphs. To obtain a more robust and accurate graph structure, we intend to construct an adaptive graph with topology and feature graphs. We propose Multi-graph Fusion Graph Convolutional Networks with pseudo-label supervision (MFGCN), which learn a connected embedding by fusing the multi-graphs and node features. We can obtain the final node embedding for semi-supervised node classification by propagating node features over multi-graphs. Furthermore, to alleviate the problem of labels missing in semi-supervised classification, a pseudo-label generation mechanism is proposed to generate more reliable pseudo-labels based on the similarity of node features. Extensive experiments on six benchmark datasets demonstrate the superiority of MFGCN over state-of-the-art classification methods.

Epidemiology of lean/non-obese nonalcoholic fatty liver disease in China: A systematic review and meta-analysis.

OBJECTIVES: To assess the prevalence and metabolic characteristics of lean/non-obese (L/NO) nonalcoholic fatty liver disease (NAFLD) in China. METHODS: The databses, inlcuding PubMed, Web of Science, EMBASE, as well as Cochrane databases, were retrieved for eligible studies. The prevalence together with clinical features of L/NO-NAFLD in China were analyzed using a random/fixed effects model. Lean or nonobese participants were characterized by the cut-offs of body mass index used in original studies. Heterogeneity was identified using meta-regression and subgroup analyses. RESULTS: We included 25 studies for the final analysis comprising 229091 L/NO Chinese adults and 22641 diagnosed with NAFLD, with the NAFLD prevalence of 8.98% (95% confidence interval [CI]: [5.55-13.13] for L-NAFLD Chinese participants and 13.77% (95% CI: [11.13-16.63]) for NO-NAFLD Chinese participants. This prevalence gradually increased during the past few years. The community and health checkup populations presented similar prevalence (14.19% vs. 13.55%). Meanwhile, L/NO patients with NAFLD showed lower blood pressure (128.86/80.48 vs. 136.09/84.98 mmHg), waist circumference (80.63 vs. 92.73 cm), fasting blood glucose (5.53 vs. 5.69 mmol/L), uric acid (339.14 vs. 365.46 µmol/L), triglyceride levels (1.63 vs. 1.94 mmol/L), alanine transaminase (30.28 vs. 33.12 IU/L), and γ-glutamyl transferase (29.9 vs. 43.68 IU/L), but higher levels of high-density lipoprotein cholesterol (1.33 vs. 1.26 mmol/L) compared to overweight/obese (OW/O) patients with NAFLD. CONCLUSION: Prevalence of NAFLD was slightly lower among the L/NO-NAFLD Chinese population than the global level but has obviously increased recently. In addition, the metabolic profile of L/NO-NAFLD patients was generally better compared to OW/O-NAFLD patients.PROSPERO Reg. No.: CRD42022327240.

Complement proteins in serum astrocyte-derived exosomes are associated with mild cognitive impairment in type 1 diabetes mellitus patients.

BACKGROUND: The complement system plays a crucial role in cognitive impairment. The aim of this study is to investigate the correlation between the complement proteins levels in serum astrocyte-derived exosomes (ADEs) and mild cognitive impairment (MCI) in type 1 diabetes mellitus (T1DM) patients. METHODS: In this cross-sectional study, the patients with immune-mediated T1DM were enrolled. Healthy subjects matched for age and sex with T1DM patients were selected as controls. The cognitive function was evaluated by a Beijing version of the Montreal Cognitive Assessment (MoCA) questionnaire. The complement proteins including C5b-9, C3b and Factor B in serum ADEs were measured by ELISA kits. RESULTS: This study recruited 55 subjects immune-mediated T1DM patients without dementia, including 31 T1DM patients with MCI, 24 T1DM patients without MCI. 33 healthy subjects were enrolled as controls. The results showed higher complement proteins including C5b-9, C3b and Factor B levels in ADEs from T1DM patients with MCI than those in the controls (P < 0.001, P < 0.001, P = 0.006) and T1DM patients without MCI (P = 0.02, P = 0.02, P = 0.03). The C5b-9 levels in ADEs were independently associated with MCI in T1DM patients(OR: 1.20, 95% CI: 1.00-1.44, P = 0.04). The C5b-9 levels in ADEs were significantly correlated with global cognitive scores (ß = -0.360, P＜0.001) and visuo-executive (ß = -0.132, P＜0.001), language(ß = -0.036, P = 0.026) and delayed recall score (ß = -0.090,P = 0.007). There was no correlation between the C5b-9 levels in ADEs and the fasting glucose, HbA1c, fasting c-peptide and GAD65 antibody in T1DM patients. Furthermore, the C5b-9, C3b and Factor B levels in ADEs exhibited a fair combined diagnostic value for MCI, with an area under the curve of 0.76 (95% CI: 0.63-0.88, P = 0.001). CONCLUSION: The elevated C5b-9 levels in ADEswere significantly associated with theMCI in T1DM patients. The C5b-9 in ADEs may be used as a marker of MCI in T1DM patients.

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.

Blood Neuroexosomal Mitochondrial Proteins Predict Alzheimer Disease in Diabetes.

There is accumulating evidence that mitochondrial dysfunction is associated with the contribution of diabetes to Alzheimer disease (AD) progression. Neuronal mitochondrial proteins are found in plasma neuronal-derived exosomes (NDEs) at levels that reflect those in brain neurons. Here, we tested the performance of mitochondrial proteins in plasma NDEs to predict cognitive decline and brain injury in participants with diabetes. The study participants with type 2 diabetes mellitus (T2DM) included 41 cognitively normal control subjects, 97 individuals with mild cognitive impairment (MCI) (68 individuals with stable MCI; 29 individuals with progressive MCI), and 36 patients with AD dementia. Plasma neuroexosomal proteins were measured by ELISA kits. Spearman correlation was used to test associations between plasma neuroexosomal mitochondrial proteins and other core biomarkers of AD. Diagnostic accuracy for progressive MCI and AD was obtained for mitochondrial proteins using receiver operating characteristic curve analyses. The associations of mitochondrial proteins with the conversion from MCI to AD were assessed by Cox proportional hazard regression analysis. Plasma levels of neuroexosomal NADH ubiquinone oxidoreductase core subunit S3 (NDUFS3) and succinate dehydrogenase complex subunit B (SDHB) were significantly lower in patients with T2DM with AD dementia and progressive MCI than in cognitively normal subjects (P < 0.001 for both groups). We also found that plasma neuroexosomal NDUFS3 and SDHB levels were lower in progressive MCI subjects than in stable MCI subjects. Both plasma neuroexosomal NDUFS3 and SDHB offer diagnostic utility for AD. Low plasma neuroexosomal SDHB levels significantly predicted conversion from MCI to AD. In addition, low mitochondrial protein levels were associated with the rate of hippocampal and gray matter atrophy and reduced AD signature cortical thickness in progressive MCI over the follow-up period. These data suggest that both plasma neuroexosomal NDUFS3 and SDHB are already increased at the early clinical stage of AD, and indicate the promise of plasma neuroexosomal mitochondrial proteins as diagnostic and prognostic biomarkers for the earliest symptomatic stage of AD in participants with diabetes.

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.

Cardiovascular Disease Risk Across a Spectrum of Adverse Plasma Lipid Combinations by Gender and Glycemic Status.

High triglycerides (TG), low high-density lipoprotein cholesterol (HDL-C) and high non-HDL-C levels are risk factors for cardiovascular disease (CVD). It is unclear whether the combinations of their adverse changes are related with CVD risk in different gender and diabetes status, particularly in Chinese population. This study aims to evaluate the CVD risk associated with different adverse lipid combinations. A total of 38,989 participants from Chinese Multicenter Longitudinal Health Management Cohorts (mean age 42 years; 62% male) without baseline CVD were followed up for incident CVD from 2007 to 2015. Participants with various combinations of baseline TG, non-HDL-C, and HDL-C levels within- or out of range according to Adult Treatment Panel III were grouped into 8 distinct lipid categories. Cox models estimated the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of different lipid categories for CVD. After multivariable adjustment, a low level of HDL-C combined with either a high level of non-HDL-C alone or TG alone were associated with increased CVD risk with adjusted HRs (95% CIs) of 1.77 (1.36 to 2.30) and 2.08 (1.30 to 3.34) in male participants. Diabetic participants with high non-HDL-C and low HDL-C levels (adjusted HR 2.93, 95% CI 1.15 to 7.46), and non-diabetic participants with high TG and low HDL-C levels (adjusted HR 1.73, 95% CI 1.33 to 2.26) had greater risk of incident CVD. These relations remained significant when limited analysis to participants with normal LDL-C levels of <3.4 mmol/L, indicating the various combinations of out-of-range lipid profiles other than LDL-C are associated with different CVD risk and the associations depend on gender and glycemic status.

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.

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 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.