Portable FRET-Based Biosensor Device for On-Site Lead Detection.

Most methods for measuring environmental lead (Pb) content are time consuming, expensive, hazardous, and restricted to specific analytical systems. To provide a facile, safe tool to detect Pb, we created pMet-lead, a portable fluorescence resonance energy transfer (FRET)-based Pb-biosensor. The pMet-lead device comprises a 3D-printed frame housing a 405-nm laser diode-an excitation source for fluorescence emission images (YFP and CFP)-accompanied by optical filters, a customized sample holder with a Met-lead 1.44 M1 (the most recent version)-embedded biochip, and an optical lens aligned for smartphone compatibility. Measuring the emission ratios (Y/C) of the FRET components enabled Pb detection with a dynamic range of nearly 2 (1.96), a pMet-lead/Pb dissociation constant (Kd) 45.62 nM, and a limit of detection 24 nM (0.474 µg/dL, 4.74 ppb). To mitigate earlier problems with a lack of selectivity for Pb vs. zinc, we preincubated samples with tricine, a low-affinity zinc chelator. We validated the pMet-lead measurements of the characterized laboratory samples and unknown samples from six regions in Taiwan by inductively coupled plasma mass spectrometry (ICP-MS). Notably, two unknown samples had Y/C ratios significantly higher than that of the control (3.48 ± 0.08 and 3.74 ± 0.12 vs. 2.79 ± 0.02), along with Pb concentrations (10.6 ppb and 15.24 ppb) above the WHO-permitted level of 10 ppb in tap water, while the remaining four unknowns showed no detectable Pb upon ICP-MS. These results demonstrate that pMet-lead provides a rapid, sensitive means for on-site Pb detection in water from the environment and in living/drinking supply systems to prevent potential Pb poisoning.

Symptomatic Features of 932 Hospitalized Patients with COVID-19 in Wuhan (preprint)

BackgroundMuch remains unknown about COVID-19 onset and rehabilitation's symptomatic features, especially the long-term health consequences of patients with COVID-19 who have been discharged from the hospital.MethodsIn this cohort study, we collected the first pandemic data of hospitalized patients in Wuhan from February 20 to March 31, 2020. All patients completed a 3-month follow-up after discharge. We carefully analyzed the detailed symptomatic characteristics of severe COVID-19 at illness onset and three months after discharge, compared it with non-severe patients, and used multiple logistic regression to determine potential symptomatic risk factors for severe COVID-19.ResultsA total of 932 hospitalized patients with COVID-19 were enrolled, including 52 severe cases and 880 non-severe cases. Fever (60%), cough (50.8%), and fatigue (36.4%) were the most common symptoms, followed by anorexia (21.8%) and dyspnea (19.2%). The median duration of fever was seven days, which was characterized by persistent low fever. The median duration of cough was 17 days, characterized by dry cough without sputum. Most dyspnea occurred on the fourth day after symptom onset, with a median duration of 16 days. The incidences of taste loss and olfactory disturbance were only 6.2% and 3.1%, respectively. Multivariate logistic regression analysis showed that age over 65 years old (OR 6.52, 95% CI 3.27-13.02, P<0.0001), male sex (3.71, 1.90-7.26, P = 0.0001), fever lasting for more than five days (1.90, 1.00-3.62, P=0.0498), anorexia at onset (2.61, 1.26-5.40, P=0.0096), and modified Medical Research Council level above grade 2 when dyspnea occurred (14.19,7.01-28.71, P<0.0001) were symptomatic risk factors for severe COVID-19. Three months after discharge from the hospital, 6.2% of patients still cough, 7.2% of patients still dyspnea, and 1.8% still fatigue, and 1.5% of patients had olfactory or taste disorders.ConclusionsCOVID-19 caused clusters of symptoms, with multiple systems involved. Specific symptomatic features at the onset of illness have predictive value for severe COVID-19. Persistent legacy symptoms are more frequent in severe COVID-19 patients.