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Since the outbreak of COVID-19, many COVID-19 research studies have proposed different models for predicting the trend of COVID-19. Among them, the prediction model based on mathematical epidemiology (SIR) is the most widely used, but most of these models are adapted in special situations based on various assumptions. In this study, a general adapted time-window based SIR prediction model is proposed, which is characterized by introducing a time window mechanism for dynamic data analysis and using machine learning method predicts the basic reproduction number and the exponential growth rate of the epidemic. We analyzed COVID-19 data from February to July 2020 in seven countries–––China, South Korea, Italy, Spain, Brazil, Germany and France, and the numerical results showed that the framework can effectively measure the real-time changes of the parameters during the epidemic, and error rate of predicting the number of COVID-19 infections in a single day is within 5%.

Big data clinical research typically involves thousands of patients and there are numerous variables available. Conventionally, these variables can be handled by multivariable regression modeling. In this article, the hierarchical cluster analysis (HCA) is introduced. This method is used to explore similarity between observations and/or clusters. The result can be visualized using heat maps and dendrograms. Sometimes, it would be interesting to add scatter plot and smooth lines into the panels of the heat map. The inherent R package does not provide this function. A series of scatter plots can be created using package, and then background color of each panel is mapped to the regression coefficient by using custom-made panel functions. This is the unique feature of the package. Dendrograms and color keys can be added as the legend elements of the lattice system. The package provides some useful functions for the work.

BackgroundHypervirulent Klebsiella pneumoniae (hvKP) is emerging around the Asian-Pacific region and it is the major cause of the community-acquired pyogenic liver abscesses. Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) isolates were reported in France, China and Taiwan. However, the international-ally agreed definition for hvKP and the virulence level of hvKP are not clear.ResultsIn this study, 56 hvKP isolates were collected from March 2008 to June 2012 and investigated by string test, capsule serotyping, multilocus sequence typing (MLST), virulence gene detection and serum resistance assay. Among the 56 K. pneumoniae isolates, 64.3% had the hypermucoviscosity phenotype, meanwhile, 64.3% were the K1 serotype and 19.6% were the K2 serotype. Within the K1 serotype, 94.4% were ST23, and within the K2 serotype, ST65, ST86 and ST375 accounted for the same percentage 27.3%. The serum resistance showed statistically normal distribution. According to the 50% lethal dose of Galleria. mellonella infection model, hvKP isolates were divided into high virulence level group and moderate virulence level group. The ability of each method evaluating the virulence level of hvKP was assessed using the area under the receiver operating characteristic curve.ConclusionsK1 ST23 K. pneumoniae was the most prevalent clone of the hvKP. However, K1 ST23 K. pneumoniae was the dominant clone in the moderate virulence level group. MLST was a relatively reliable evaluation method to discriminate the virulence level of hvKP in our study.Electronic supplementary materialThe online version of this article (10.1186/s12866-018-1236-2) contains supplementary material, which is available to authorized users.

Cefiderocol-resistant CRKP strains are emerging in bloodstream infections in Chinese patients with hematologic malignancies, although cefiderocol has not been approved for clinical use in China. Our study proved that the resistance of CRKP against cefiderocol is mediated by multiple factors, including the deficiency of CirA, metallo- or serine-β-lactamases, while a high-level cefiderocol resistance could be rendered by the combined effect of NDM expression and CirA deficiency.

The gene encoding the murine calcitonin receptor (mCTR) was isolated, and the exon/intron structure was determined. Analysis of transcripts revealed novel cDNA sequences, new alternative exon splicing in the 5-untranslated region, and three putative promoters (P1, P2, and P3). The longest transcription unit is greater than 67 kilobase pairs, and the location of introns within the coding region of the mCTR gene (exons E3-E14) are identical to those of the porcine and human CTR genes. We have identified novel cDNA sequences that form three new exons as well as others that add 512 base pairs to the 5 side of the previously published cDNA, thereby extending exon E1 to 682 base pairs. Two of these novel exons are upstream of exon E2 and form a tripartite exon E2 (E2a, E2b, and E2c) in which E2a is utilized by promoter P2 with variable splicing of E2b. The third new exon (E3b) lies between E3a and E3b and is utilized by promoter P3. Analysis of mCTR mRNAs has revealed that the three alternative promoters give rise to at least seven mCTR isoforms in the 5 region of the gene and generate 5-untranslated regions of very different lengths. Analysis by reverse transcription-polymerase chain reaction shows that promoters P1 and P2 are utilized in osteoclasts, brain, and kidney, whereas promoter P3 appears to be osteoclast-specific. Using transiently transfected reporter constructs, promoter P2 has activity in both a murine kidney cell line (MDCT209) and a chicken osteoclastlike cell line (HD-11EM), whereas promoter P3 is active only in the osteoclast-like cell line. These transfection data confirm the osteoclast specificity of promoter P3 and provide the first evidence that the CTR gene is regulated in a tissue-specific manner by alternative promoter utilization.

Iron is an essential nutrient for bacterial survival and thus higher iron levels may precipitate bacterial infections. We investigated the association between the serum iron level and prognosis in patients with sepsis by using the single-centre Medical Information Mart for Intensive Care III (MIMIC-III) database. Sepsis patients with iron parameters measured on ICU admission were included and stratified according to quartiles of serum iron levels. A total of 1,891 patients diagnosed with sepsis according to the Sepsis-3 criteria were included in this study, 324 of whom were septic shock. After adjusting for confounding variables, higher iron quartile was associated with an increase in 90-day mortality in the Cox regression analysis. Moreover, a stepwise increase in the risk of 90-day mortality was observed as the quartiles of serum iron levels increased in the patients with sepsis. In conclusion, higher serum iron levels were independently associated with increased 90-day mortality in this large cohort of patients with sepsis.