Klebsiella pneumoniae (K. pneumoniae) is a frequent pathogen causing nosocomial infections and outbreaks. We developed a multiple cross displacement amplification (MCDA) assay for the detection of K. pneumoniae, which can get the positive results within 40 minutes’ isothermal amplification. Gold-nanoparticle lateral flow biosensor (LFB) and colorimetric indicators were used for the rapid readouts of MCDA amplification. The detection limit of this assay was 100 fg per reaction at 65°C, which was confirmed to be the optimal amplification temperature according to the real time turbidimeters. For specificity, all of the 30 clinical-source K. pneumoniae strains were positive for the MCDA, and all of the non-K. pneumoniae strains belonging to 31 different species were negative for this MCDA assay. To evaluate the practical applicability of this method, we assessed its detection limit for K. pneumoniae strains in sputum samples (24 CFU per reaction), and DNA templates of 100 sputum samples further underwent the MCDA-LFB tests. All of the sputum samples being positive for K. pneumoniae (30/100) with the culture method were successfully identified with the MCDA assay, the detection power of which was higher than that of polymerase chain reaction (PCR) (25/100). Thus, the MCDA test for K. pneumoniae combined with the gold nanoparticle LFB as the results readout scheme, are simple, specific, and sensitive methods for the rapid diagnosis of K. pneumoniae in clinical samples.

We aimed to explore novel small metabolites that associated with hypertension risk in a population-based nested case-control study. Among 460 individuals with optimal blood pressure (<120/80 mmHg) at baseline, 55 progressed to hypertension during 5 years of follow-up. Twenty-nine cases of incident hypertension and 29 controls, matched for age, sex, and baseline systolic blood pressure, were included in this study. Serum metabolites were measured by gas chromatography-tandem mass spectrometry. t-test and logistic regression analysis were applied to investigate the association between metabolites and incident hypertension. Among the 241 metabolites identified in this study, baseline levels of 26 metabolites were significantly different between hypertension and control groups. After adjusting for body mass index, smoking, and drinking, 16 out of the 26 metabolites were still associated with hypertension risk including four amino acids. Amino acids were negatively associated with risk of future hypertension, with odds ratio (OR) ranging from 0.33 to 0.53. Two of these amino acids were essential amino acids including threonine and phenylalanine. Higher level of lyxose, a fermentation product of gut microbes, was associated with higher risk of hypertension. Our study identified multiple metabolites that associated with hypertension risk. These findings implied that low amino acid levels and gut microbiome might play an important role in the pathogenesis of hypertension.

The great heterogeneity of patients with chronic critical illness (CCI) leads to difficulty for intensive care unit (ICU) management. Identifying subphenotypes could assist in individualized care, which has not yet been explored. In this study, we aim to identify the subphenotypes of patients with CCI and reveal the heterogeneous treatment effect of fluid balance for them. In this retrospective study, we defined CCI as an ICU length of stay over 14 days and coexists with persistent organ dysfunction (cardiovascular Sequential Organ Failure Assessment (SOFA) score ≥1 or score in any other organ system ≥2) at Day 14. Data from five electronic healthcare record datasets covering geographically distinct populations (the US, Europe, and China) were studied. These five datasets include (1) subset of Derivation (MIMIC-IV v1.0, US) cohort (2008–2019); (2) subset Derivation (MIMIC-III v1.4 ‘CareVue’, US) cohort (2001–2008); (3) Validation I (eICU-CRD, US) cohort (2014–2015); (4) Validation II (AmsterdamUMCdb/AUMC, Euro) cohort (2003–2016); (5) Validation III (Jinling, CN) cohort (2017–2021). Patients who meet the criteria of CCI in their first ICU admission period were included in this study. Patients with age over 89 or under 18 years old were excluded. Three unsupervised clustering algorithms were employed independently for phenotypes derivation and validation. Extreme Gradient Boosting (XGBoost) was used for phenotype classifier construction. A parametric G-formula model was applied to estimate the cumulative risk under different daily fluid management strategies in different subphenotypes of ICU mortality. We identified four subphenotypes as Phenotype A, B, C, and D in a total of 8145 patients from three countries. Phenotype A is the mildest and youngest subgroup; Phenotype B is the most common group, of whom patients showed the oldest age, significant acid-base abnormality, and low white blood cell count; Patients with Phenotype C have hypernatremia, hyperchloremia, and hypercatabolic status; and in Phenotype D, patients accompany with the most severe multiple organ failure. An easy-to-use classifier showed good effectiveness. Phenotype characteristics showed robustness across all cohorts. The beneficial fluid balance threshold intervals of subphenotypes were different. We identified four novel phenotypes that revealed the different patterns and significant heterogeneous treatment effects of fluid therapy within patients with CCI. A prospective study is needed to validate our findings, which could inform clinical practice and guide future research on individualized care. This study was funded by 333 High Level Talents Training Project of 10.13039/501100002949 Jiangsu Province (BRA2019011), General Program of Medical Research from the Jiangsu Commission of Health (M2020052), and Key Research and Development Program of Jiangsu Province (BE2022823).