[Malaria control knowledge and behaviors and their influencing factors among residents in Banlao Township, Cangyuan County, Yunnan Province]

OBJECTIVE

To investigate the awareness of malaria-related knowledge, the use of mosquito nets and their influencing factors among residents in Banlao Township, Cangyuan County, Yunnan Province.

METHODS

In August 2020, 19 settlement sites in Banlao Township, Cangyuan County, Lincang City, Yunnan Province were selected as study areas, and permanent residents at ages of 10 years and older were enrolled for a questionnaire survey, including residents' demographics, family economic status, malaria control knowledge and use of mosquito nets. In addition, the factors affecting the use of mosquito nets in the night prior to the survey were identified using multivariate logistic regression analysis.

RESULTS

A total of 320 questionnaires were allocated, and all were recovered (a 100% recovery rate). There were 316 valid questionnaires, with an effective recovery rate of 98.75%. The 316 respondents included 152 men and 164 women and 250 Chinese respondents and 66 foreign respondents. The awareness of clinical syndromes of malaria was significantly higher among Chinese residents (71.60%) than among foreign residents (50.00%) (χ² = 11.03, P < 0.01), and the proportions of Chinese and foreign residents sleeping under mosquito nets were 46.00% and 69.70% on the night prior to the survey, respectively (χ² = 11.73, P < 0.01). Multivariate logistic regression analysis identified ethnicity group and type of residence as factors affecting the use of mosquito nets in the night prior to the survey.

CONCLUSIONS

The awareness of malaria control knowledge, the coverage and the use of mosquito nets were low among residents in Banlao Township, Cangyuan County, Yunnan Province. Targeted health education is recommended to improve the awareness of malaria control knowledge and self-protection ability. In addition, improving the allocation of long-lasting mosquito nets and health education pertaining to their uses and increasing the proportion of using mosquito nets correctly is needed to prevent re-establishment of imported malaria.

CD11c+ microglia promote white matter repair after ischemic stroke

Ischemic stroke leads to white matter damage and neurological deficits. However, the characteristics of white matter injury and repair after stroke are unclear. Additionally, the precise molecular communications between microglia and white matter repair during the stroke rehabilitation phase remain elusive. In this current study, MRI DTI scan and immunofluorescence staining were performed to trace white matter and microglia in the mouse transient middle cerebral artery occlusion (tMCAO) stroke model. We found that the most serious white matter damage was on Day 7 after the ischemic stroke, then it recovered gradually from Day 7 to Day 30. Parallel to white matter recovery, we observed that microglia centered around the damaged myelin sheath and swallowed myelin debris in the ischemic areas. Then, microglia of the ischemic hemisphere were sorted by flow cytometry for RNA sequencing and subpopulation analysis. We found that CD11c+ microglia increased from Day 7 to Day 30, demonstrating high phagocytotic capabilities, myelin-supportive genes, and lipid metabolism associated genes. CD11c+ microglia population was partly depleted by the stereotactic injecting of rAAV2/6M-taCasp3 (rAAV2/6M-CMV-DIO-taCasp3-TEVp) into CD11c-cre mice. Selective depletion of CD11c+ microglia disrupted white matter repair, oligodendrocyte maturation, and functional recovery after stroke by Rotarod test, Adhesive Removal test, and Morris Water Maze test. These findings suggest that spontaneous white matter repair occurs after ischemic stroke, while CD11c+ microglia play critical roles in this white matter restorative progress.

[Changes in percentage of GATA3+ regulatory T cells and their pathogenic roles in allergic rhinitis]

OBJECTIVE

To investigate the changes in percentage of GATA3⁺ regulatory T (Treg) cells in patients with allergic rhinitis (AR) and mouse models.

METHODS

The nasal mucosa specimens were obtained from 6 AR patients and 6 control patients for detection of nasal mucosal inflammation. Peripheral blood mononuclear cells (PBMC) were collected from 12 AP patients and 12 control patients to determine the percentages of Treg cells and GATA3⁺ Treg cells. In a C57BL/6 mouse model of AR, the AR symptom score, peripheral blood OVA-sIgE level, and nasal mucosal inflammation were assessed, and the spleen of mice was collected for detecting the percentages of Treg cells and GATA3⁺ Treg cells and the expressions of Th2 cytokines.

RESULTS

Compared with the control patients, AR patients showed significantly increased eosinophil infiltration and goblet cell proliferation in the nasal mucosa (P < 0.01) and decreased percentages of Treg cells and GATA3⁺ Treg cells (P < 0.05). The mouse models of AR also had more obvious allergic symptoms, significantly increased OVA-sIgE level in peripheral blood, eosinophil infiltration and goblet cell hyperplasia (P < 0.01), markedly lowered percentages of Treg cells and GATA3⁺ Treg cells in the spleen (P < 0.01), and increased expressions of IL-4, IL-6 and IL-10 (P < 0.05).

CONCLUSION

The percentage of GATA3⁺ Treg cells is decreased in AR patients and mouse models. GATA3⁺ Treg cells possibly participate in Th2 cell immune response, both of which are involved in the occurrence and progression of AR, suggesting the potential of GATA3⁺ Treg cells as a new therapeutic target for AR.

Negative refraction in hyperbolic hetero-bicrystals

We visualized negative refraction of phonon polaritons, which occurs at the interface between two natural crystals. The polaritons-hybrids of infrared photons and lattice vibrations-form collimated rays that display negative refraction when passing through a planar interface between the two hyperbolic van der Waals materials: molybdenum oxide (MoO₃) and isotopically pure hexagonal boron nitride (h¹¹BN). At a special frequency ω₀, these rays can circulate along closed diamond-shaped trajectories. We have shown that polariton eigenmodes display regions of both positive and negative dispersion interrupted by multiple gaps that result from polaritonic-level repulsion and strong coupling.

Ultra-low-dose CT lung screening with artificial intelligence iterative reconstruction: evaluation via automatic nodule-detection software

AIM

To test the feasibility of ultra-low-dose (ULD) computed tomography (CT) combined with an artificial intelligence iterative reconstruction (AIIR) algorithm for screening pulmonary nodules using computer-assisted diagnosis (CAD).

MATERIALS AND METHODS

A chest phantom with artificial pulmonary nodules was first scanned using the routine protocol and the ULD protocol (3.28 versus 0.18 mSv) to compare the image quality and to test the acceptability of the ULD CT protocol. Next, 147 lung-screening patients were enrolled prospectively, undergoing an additional ULD CT immediately after their routine CT examination for clinical validation. Images were reconstructed with filtered back-projection (FBP), hybrid iterative reconstruction (HIR), the AIIR, and were imported to the CAD software for preliminary nodule detection. Subjective image quality on the phantom was scored using a five-point scale and compared using the Mann-Whitney U-test. Nodule detection using CAD was evaluated for ULD HIR and AIIR images using the routine dose image as reference.

RESULTS

Higher image quality was scored for AIIR than for FBP and HIR at ULD (p<0.001). As reported by CAD, 107 patients were presented with more than five nodules on routine dose images and were chosen to represent the challenging cases at an early stage of pulmonary disease. Among such, the performance of nodule detection by CAD on ULD HIR and AIIR images was 75.2% and 92.2% of the routine dose image, respectively.

CONCLUSION

Combined with AIIR, it was feasible to use an ULD CT protocol with 95% dose reduction for CAD-based screening of pulmonary nodules.

ATP13A2 is a Prognostic Biomarker and Correlates with Immune Infiltrates in Hepatocellular Carcinoma

PURPOSE

To explore the expression and role of ATPase cation transporting 13A2 (ATP13A2) on hepatocellular carcinoma (HCC) progression and prognosis.

METHODS

The level of ATP13A2 in 63 HCC tissues was evaluated by quantitative real-time polymerase chain reaction, Western blot, and immunohistochemistry. Then, the prognostic value of ATP13A2 for HCC was explored. GO and KEGG pathway enrichments were performed to predict ATP13A2-mediated biological functions. Besides, the correlations between ATP13A2 and key regulators involved in cell cycle and metastasis, the status of different tumor-infiltrating immune cells was investigated.

RESULTS

ATP13A2 was frequently upregulated in 63 HCC tissues relatively to matched non-tumor tissues. The level of ATP13A2 significantly correlated with tumor stage and tumor grade. HCC patients with higher levels of ATP13A2 had a worse prognosis. Moreover, multivariate survival analysis supported ATP13A2 to be an independent prognostic factor for HCC. GO and KEGG analysis indicated a potential role of ATP13A2 on regulating cell cycle, metastasis, and immune infiltrates. Especially, the level of ATP13A2 was positively correlated with CCNB1, CCND3, CDC25B, CDK4, Vimentin, MMP9, MMP14, and LMNB2. A positive correlation was noticed between ATP13A2 and infiltration levels of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, dendritic cells, monocytes, M2 macrophages, and exhausted T cells in HCC.

CONCLUSION

Upregulation of ATP13A2 is a common feature as well as an independent prognostic biomarker for HCC. ATP13A2 are associated with key regulators involved in cell cycle, metastasis, and immune infiltrates in HCC, and may act as a potential immunotherapy target for HCC.

Endotyping of nasal polyps in a multiracial Asian population

Background: Chronic rhinosinusitis is a heterogenous disease with variation in the endotypes of nasal polyps, with type 2 inflammation being more prevalent in Caucasian populations whereas Chinese populations are more heterogenous. We aim to describe the variation in endotypes for patients with chronic rhinosinusitis with nasal polyposis in our unique multiracial population. Methodology: Demographic, clinical and structured histopathological data of 66 patients who underwent sinus surgery for nasal polyposis were evaluated retrospectively. Results: 54.6% had eosinophilic disease, and 45.4% had non-eosinophilic disease with no significant demographic differences between the 2 populations. There were significantly higher peripheral eosinophil levels in patients with eosinophil-predominant inflammation on tissue histology (mean absolute eosinophil count 0.59 ± 0.18 x 109) compared with non-eosinophilic disease (mean absolute eosinophil count 0.24 ± 0.11 x 109). Structured histopathological reporting revealed that patients with eosinophilic disease had higher degree of inflammation and eosinophil aggregates. Conclusions: Our population is shown to have a slight preponderance toward eosinophilic disease, however the Chinese majority tended to have non-eosinophilic disease. Serum eosinophilia and the presence of asthma seems to correlate well with tissue eosinophilia, which can potentially be utilised as markers of type 2 inflammatory disease.

The role of N6-methyladenosine methylation in environmental exposure-induced health damage

The health risks caused by environmental pollution have long been of substantial concern. With the development of epigenetics, a large number of studies have demonstrated that N6-methyladenosine (m6A) modification is involved in the regulation of various important life activities associated with various diseases. Recent studies have revealed that m6A plays a key role in health damage caused by environmental exposure by regulating post-transcriptional gene expression. Therefore, our study outlined the effects of environmental pollutant exposure on m6A methylation and its regulator levels. Moreover, we found that m6A methylation modifications were involved in the development of various health damages by regulating important life activities in vivo, such as reactive oxygen species imbalance, apoptosis, epithelial-mesenchymal transition (EMT), and inflammatory processes. More importantly, we delved into the regulatory mechanisms of m6A methylation dysregulation in environmental pollution-induced diseases. Finally, by examining the published literature, we found that methyltransferase-like protein 3 (METTL3) and fat mass- and obesity-associated protein (FTO) were potentially used as biomarkers of health damage induced by particulate matter exposure and heavy metal exposure, respectively. The current studies on regulators of METTL3 and FTO were more promising to bring new perspectives for the treatment of environmental health-related diseases.

Using machine learning models to predict HBeAg seroconversion in CHB patients receiving pegylated interferon-α monotherapy

BACKGROUND AND OBJECTIVE

Though there are many advantages of pegylated interferon-α (PegIFN-α) treatment to chronic hepatitis B (CHB) patients, the response rate of PegIFN-α is only 30 ~ 40%. Therefore, it is important to explore predictors at baseline and establish models to improve the response rate of PegIFN-α.

METHODS

We randomly divided 260 HBeAg-positive CHB patients who were not previously treated and received PegIFN-α monotherapy (180 μg/week) into a training dataset (70%) and testing dataset (30%). The intersect features were extracted from 50 routine laboratory variables using the recursive feature elimination method algorithm, Boruta algorithm, and Least Absolute Shrinkage and Selection Operator Regression algorithm in the training dataset. After that, based on the intersect features, eight machine learning models including Logistic Regression, k-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting, Extreme Gradient Boosting (XGBoost), and Naïve Bayes were applied to evaluate HBeAg seroconversion in HBeAg-positive CHB patients receiving PegIFN-α monotherapy in the training dataset and testing dataset.

RESULTS

XGBoost model showed the best performance, which had largest AUROC (0.900, 95% CI: 0.85-0.95 and 0.910, 95% CI: 0.84-0.98, in training dataset and testing dataset, respectively), and the best calibration curve performance to predict HBeAg seroconversion. The importance of XGBoost model indicated that treatment time contributed greatest to HBeAg seroconversion, followed by HBV DNA(log), HBeAg, HBeAb, HBcAb, ALT, triglyceride, and ALP.

CONCLUSIONS

XGBoost model based on common laboratory variables had good performance in predicting HBeAg seroconversion in HBeAg-positive CHB patients receiving PegIFN-α monotherapy.