Meixiu Sun

Exhaled volatile organic compounds (VOCs) have been investigated in some diseases, including cognitive impairment, in pilot studies. The present study aimed to explore the role of exhaled VOCs in identifying and differentiating patients with Alzheimer's disease (AD). The identification cohort included 241 participants: 99 AD patients (dementia=74, mild cognitive impairment (MCI) = 25), 59 non-AD dementia patients, and 83 cognitively unimpaired controls (CUCs). Proton transfer reaction time-of-flight mass spectrometry (PTR-TOFMS) was employed to detect exhaled VOCs. The differences in VOCs between the AD and CUC groups and between the AD dementia and non-AD dementia groups were compared separately. Furthermore, machine learning models for discriminating AD from CUC as well as AD dementia from non-AD dementia were established. The AD diagnostic model was further validated in an independent cohort of 44 AD patients (dementia=33, MCI = 11) and 35 CUCs. Moreover, we explored the possible metabolic pathways of AD-specific exhaled VOCs with the Human Metabolome Database (HMDB). We detected 60 different VOCs between the AD and CUC groups, among which the top ten were C₄H₁₀S, C₂H₆N₂O₂, C₃H₆O₃, C₄H₇F₂NO, C₆H₅NO₂, C₈H₆N₂, C₃HN, C₉H₂₁N, C₁₅H₂₄, and C₈H₁₂ (P < 0.001). The AD diagnostic model had an accuracy of 0.93 in the identification cohort according to internal validation and 0.75 in the validation cohort for external validation. The model for discriminating AD dementia patients from non-AD dementia patients had an accuracy of 0.90. Fourteen of the 60 AD-specific VOCs were retrieved from the HMDB, from which the three most significant metabolic pathways were identified, namely, butyrate metabolism, pyruvate metabolism, and glycolysis/gluconeogenesis. These results indicate that exhaled VOC measurement may be a promising approach for diagnosing and differentiating AD, but further validation is needed.

In this work, a facile preparation method was proposed to reduce natural organics fouling of hydrophobic membrane via UV grafting polymerization with methacrylic acid (MAAc) and methyl acrylamide (MAAm) as hydrophilic monomers, followed by multihydrogen bond self-assembly. The resulting poly(vinylidene fluoride)-membranes were characterized with respect to monomer ratio, chemical structure and morphology, surface potential, and water contact angle, as well as water flux and organic foulants ultrafiltration property. The results indicated that the optimal membrane modified with a poly(MAAc-co-MAAm) polymer gel layer derived from a 1:1 monomer ratio exhibited superior hydrophilicity and excellent gel layer stability, even after ultrasonic treatment or soaking in acid or alkaline aqueous solution. The initial water contact angle of modified membranes was only 36.6° ± 2.9, and dropped to 0° within 13 s. Moreover, flux recovery rates (FRR) of modified membranes tested by bovine serum albumin (BSA), humic acid (HA), and sodium alginate (SA) solution, respectively, were all above 90% after one-cycle filtration (2 h), significantly higher than that of the pure membrane (70–76%). The total fouling rates (R_t) of the pure membrane for three foulants were as high as 47.8–56.2%, while the R_t values for modified membranes were less than 30.8%. Where R_t of BSA dynamic filtration was merely 10.7%. The membrane designed through grafting a thin-layer hydrophilic hydrogel possessed a robust antifouling property and stability, which offers new insights for applications in pure water treatment or protein purification.

Breath analysis has been considered a suitable tool to evaluate diseases of the respiratory system and those that involve metabolic changes, such as diabetes. Breath acetone has long been known as a biomarker for diabetes. However, the results from published data by far have been inconclusive regarding whether breath acetone is a reliable index of diabetic screening. Large variations exist among the results of different studies because there has been no “best-practice method” for breath-acetone measurements as a result of technical problems of sampling and analysis. In this mini-review, we update the current status of our development of a laser-based breath acetone analyzer toward real-time, one-line diabetic screening and a point-of-care instrument for diabetic management. An integrated standalone breath acetone analyzer based on the cavity ringdown spectroscopy technique has been developed. The instrument was validated by using the certificated gas chromatography-mass spectrometry. The linear fittings suggest that the obtained acetone concentrations via both methods are consistent. Breath samples from each individual subject under various conditions in total, 1257 breath samples were taken from 22 Type 1 diabetic (T1D) patients, 312 Type 2 diabetic (T2D) patients, which is one of the largest numbers of T2D subjects ever used in a single study, and 52 non-diabetic healthy subjects. Simultaneous blood glucose (BG) levels were also tested using a standard diabetic management BG meter. The mean breath acetone concentrations were determined to be 4.9 ± 16 ppm (22 T1D), and 1.5 ± 1.3 ppm (312 T2D), which are about 4.5 and 1.4 times of the one in the 42 non-diabetic healthy subjects, 1.1 ± 0.5 ppm, respectively. A preliminary quantitative correlation (R = 0.56, p < 0.05) between the mean individual breath acetone concentration and the mean individual BG levels does exist in 20 T1D subjects with no ketoacidosis. No direct correlation is observed in T1D subjects, T2D subjects, and healthy subjects. The results from a relatively large number of subjects tested indicate that an elevated mean breath acetone concentration exists in diabetic patients in general. Although many physiological parameters affect breath acetone, under a specifically controlled condition fast (<1 min) and portable breath acetone measurement can be used for screening abnormal metabolic status including diabetes, for point-of-care monitoring status of ketone bodies which have the signature smell of breath acetone, and for breath acetone related clinical studies requiring a large number of tests.

In order to further improve the noninvasive measurement precision of human blood components and achieve clinical requirements, we propose a new measurement method based on the dynamic dual wavelength time-resolved transmittance measurement, combined with the advanced time gate technology and Laplasse transform to detect human blood components noninvasively in the blocked blood flow conditions. Simulation results show that when p>0, emphasizing the importance of early arriving photons contribution can enhance the detection sensitivity of human body blood parameters.