Differential Diagnosis of COVID-19 Pneumonia From Influenza A (H1N1) Pneumonia Using a Model Based on Clinicoradiologic Features.

Objectives: Both coronavirus disease 2019 (COVID-19) pneumonia and influenza A (H1N1) pneumonia are highly contagious diseases. We aimed to characterize initial computed tomography (CT) and clinical features and to develop a model for differentiating COVID-19 pneumonia from H1N1 pneumonia. Methods: In total, we enrolled 291 patients with COVID-19 pneumonia from January 20 to February 13, 2020, and 97 patients with H1N1 pneumonia from May 24, 2009, to January 29, 2010 from two hospitals. Patients were randomly grouped into a primary cohort and a validation cohort using a seven-to-three ratio, and their clinicoradiologic data on admission were compared. The clinicoradiologic features were optimized by the least absolute shrinkage and selection operator (LASSO) logistic regression analysis to generate a model for differential diagnosis. Receiver operating characteristic (ROC) curves were plotted for assessing the performance of the model in the primary and validation cohorts. Results: The COVID-19 pneumonia mainly presented a peripheral distribution pattern (262/291, 90.0%); in contrast, H1N1 pneumonia most commonly presented a peribronchovascular distribution pattern (52/97, 53.6%). In LASSO logistic regression, peripheral distribution patterns, older age, low-grade fever, and slightly elevated aspartate aminotransferase (AST) were associated with COVID-19 pneumonia, whereas, a peribronchovascular distribution pattern, centrilobular nodule or tree-in-bud sign, consolidation, bronchial wall thickening or bronchiectasis, younger age, hyperpyrexia, and a higher level of AST were associated with H1N1 pneumonia. For the primary and validation cohorts, the LASSO model containing above eight clinicoradiologic features yielded an area under curve (AUC) of 0.963 and 0.943, with sensitivity of 89.7 and 86.2%, specificity of 89.7 and 89.7%, and accuracy of 89.7 and 87.1%, respectively. Conclusions: Combination of distribution pattern and category of pulmonary opacity on chest CT with clinical features facilitates the differentiation of COVID-19 pneumonia from H1N1 pneumonia.

[Feasibility of washing as a remediation technology for the heavy metals-polluted soils left by chemical plant].

Laboratory simulation tests were conducted to examine the effects of different washing reagents (distilled water, HCl, H3PO4, oxalic acid, and CaCl2) in extracting the heavy metals from contaminated soils left by a chemical plant. The effects of reagent concentration, reaction time, and washing time on the washing efficiency were investigated, and the form variation of test heavy metals was determined before and after HCl washing. Distilled water, H3PO4, and CaCl2 could remove less than 1% of most heavy metals, and the highest removal rate was only 3.58%; while 2 mol HCl x L(-1) could obtain the highest washing efficiency under the optimal conditions, i. e., soil:liquid ratio was 1:3, reaction time was 1 hour, and the soils were washed twice by HCl solution. The removal rates of Cr, Pb, Zn, Cu, and Cd from test soils were 80.75%, 88.69%, 98.00%, 79.33%, and 95.52%, respectively. Among the washing reagents, HCl could effectively remove all forms of heavy metals.

[Persisters and their effects on microbial biofilm tolerance: a review].

Persisters are a group of special subpopulation of bacteria, only occupying < 0.1% of the whole population but having the characteristics different from the ordinary bacteria and resistant mutants. They have complex formation mechanism, and are difficult to isolate and culture. The persisters can adapt to the adverse environment via "dormancy-growth-proliferation" to maintain their survival and cell structure stability, and play a vital role in the multi-drug and multi-metal tolerance of microbial biofilm, being of great significance in maintaining the stability of microbial community structure. This paper reviewed the research progress on the characteristics of persisters, their gene regulation mechanisms, and their effects on the multi-drug and multi-metal tolerance of microbial biofilm. The related research directions in the future were also prospected.