Integrated Microfluidic System for Cell-Free DNA Extraction from Plasma for Mutant Gene Detection and Quantification

Ovarian cancer (OvCa) is among the most severe gynecologic cancers, yet individuals may be asymptomatic during its early stages. Routine, early screening for genetic abnormalities associated with OvCa could improve prognoses, and this can be achieved by detecting mutant genes in cell-free DNA (cfDNA). Herein, we developed an integrated microfluidic chip (IMC) that could extract cfDNA from plasma and automatically detect and quantify mutations in the OvCa biomarker BRCA1. The cfDNA extraction module relied on a vortex-type micromixer to mix cfDNA with magnetic beads surface-coated with cfDNA probes and could isolate 76% of molecules from a 200 μL plasma sample in 45 min. The cfDNA quantification module, which comprised a micropump that evenly distributed 4.5 μL of purified cfDNA into the on-chip, allele-specific quantitative polymerase chain reaction (qPCR) zones, was capable of quantifying mutant genes within 90 min. By automating the cfDNA extraction and qPCR processes, this IMC could be used for clinical screening for OvCa-associated mutations

Isolation and Quantification of Methylated Cell-Free DNA in Plasma on an Integrated Microfluidic System

Methylated cell-free DNA (cfDNA) has been deemed a promising biomarker for ovarian cancer (OvCa) prognosis and therapy selection. However, exploring the methylation profiles of tumor suppressor genes in cfDNA remains a challenge due to their extremely low concentrations and complicated protocols, as well as methodological constraints. In this study, an integrated microfluidic system was developed to automatically (1) capture methylated cfDNA in plasma by magnetic beads coated with the methyl-CpG-binding domain and (2) quantify the methylation level of tumor suppressor genes by on-chip quantitative polymerase chain reaction (qPCR). For capturing methylated cfDNA from a very small amount of plasma, samples along with beads were mixed in a new micromixer to enhance the capture rate. With a high capture rate (72%) and a limit of quantification of 0.1 pg/μL (3 orders of magnitude lower than that of the benchtop method), the compact system could detect the methylated cfDNA from only 20 μL of plasma sample in 2 h. Furthermore, the dynamic range, from 0.1 to 2000 pg/μL of methylated cfDNA, spans the physiological range in plasma, signifying that this device has great potential for personalized medicine in OvCa

sj-docx-1-dhj-10.1177_20552076231191055 - Supplemental material for The deep learning algorithm estimates chest radiograph-based sex and age as independent risk factors for future cardiovascular outcomes

Supplemental material, sj-docx-1-dhj-10.1177_20552076231191055 for The deep learning algorithm estimates chest radiograph-based sex and age as independent risk factors for future cardiovascular outcomes by Hao-Chun Liao, Chin Lin, Chih-Hung Wang and Wen-Hui Fang in DIGITAL HEALTH</p

The amount of VC-IP deposited in the skin appeared to be higher in group U than in group C, and significantly so in groups U, U+1.4, U+2.1, and U+3.5.

<p>The amount of VC-IP that had permeated at 32 hours and the residual amount of the initially administered drug remaining in the skin. Data are mean and SD values.</p

Quantification of the penetration depths for pigskin in the various groups.

<p>Asterisk, <i>p <</i> 0.05; data are mean and SD values.</p

Effects of Microbubble Size on Ultrasound-Induced Transdermal Delivery of High-Molecular-Weight Drugs - Fig 2

<p>Microscopy images of the agarose phantoms obtained before (upper row) and after (lower row) MATLAB-based image processing for combining US at 1 W/cm² (A), 2 W/cm² (B), and 3 W/cm² (C) with 1.4-μm, 2.1-μm, and 3.5-μm MBs after the Evans blue solution was allowed to stand for 1 min. (D) Quantification of the penetration depths in the three groups. Asterisk, <i>p <</i> 0.05; data are mean and SD values.</p

Photographs of mouse skin in a completely untreated animal (A), after UVB irradiation (B), and in groups C (C), D (D), U (E), U+1.4, (F), U+2.1 (G), and U+3.5 (H) at week 4.

<p>Photographs of mouse skin in a completely untreated animal (A), after UVB irradiation (B), and in groups C (C), D (D), U (E), U+1.4, (F), U+2.1 (G), and U+3.5 (H) at week 4.</p

VC-IP concentrations in groups C, U+1.4, U+2.1, and U+3.5 for percutaneous penetration over 32 hours as analyzed using the UV/visual spectrophotometer.

<p>Data are mean and SD values.</p

Image_1_Trajectories of Vital Signs and Risk of In-Hospital Cardiac Arrest.TIF

Background: Little is known about the trajectories of vital signs prior to in-hospital cardiac arrest (IHCA), which could explain the heterogeneous processes preceding this event. We aimed to identify clinically relevant subphenotypes at high risk of IHCA in the emergency department (ED).Methods: This retrospective cohort study used electronic clinical warehouse data from a tertiary medical center. We retrieved data from 733,398 ED visits over a 7-year period. We selected one ED visit per person and retrieved patient demographics, triage data, vital signs (systolic blood pressure [SBP], heart rate [HR], body temperature, respiratory rate, oxygen saturation), selected laboratory markers, and IHCA status. Group-based trajectory modeling was performed.Results: There were 37,697 adult ED patients with a total of 1,507,121 data points across all vital-sign categories. Three to four trajectory groups per vital-sign category were identified, and the following five trajectory groups were associated with a higher rate of IHCA: low and fluctuating SBP, high and fluctuating HR, persistent hypothermia, recurring tachypnea, and low and fluctuating oxygen saturation. The IHCA-prone trajectory group was associated with a higher triage level and a higher mortality rate, compared to other trajectory groups. Except for the persistent hypothermia group, the other four trajectory groups were more likely to have higher levels of C-reactive protein, lactic acid, cardiac troponin I, and D-dimer. Multivariable analysis revealed that hypothermia (adjusted odds ratio [aOR], 2.20; 95% confidence interval [95%CI], 1.35–3.57) and recurring tachypnea (aOR 2.44; 95%CI, 1.24–4.79) were independently associated with IHCA.Conclusions: We identified five novel vital-sign sub-phenotypes associated with a higher likelihood of IHCA, with distinct patterns in clinical course and laboratory markers. A better understanding of the pre-IHCA vital-sign trajectories may help with the early identification of deteriorating patients.</p

Table_1_Trajectories of Vital Signs and Risk of In-Hospital Cardiac Arrest.DOCX

Background: Little is known about the trajectories of vital signs prior to in-hospital cardiac arrest (IHCA), which could explain the heterogeneous processes preceding this event. We aimed to identify clinically relevant subphenotypes at high risk of IHCA in the emergency department (ED).Methods: This retrospective cohort study used electronic clinical warehouse data from a tertiary medical center. We retrieved data from 733,398 ED visits over a 7-year period. We selected one ED visit per person and retrieved patient demographics, triage data, vital signs (systolic blood pressure [SBP], heart rate [HR], body temperature, respiratory rate, oxygen saturation), selected laboratory markers, and IHCA status. Group-based trajectory modeling was performed.Results: There were 37,697 adult ED patients with a total of 1,507,121 data points across all vital-sign categories. Three to four trajectory groups per vital-sign category were identified, and the following five trajectory groups were associated with a higher rate of IHCA: low and fluctuating SBP, high and fluctuating HR, persistent hypothermia, recurring tachypnea, and low and fluctuating oxygen saturation. The IHCA-prone trajectory group was associated with a higher triage level and a higher mortality rate, compared to other trajectory groups. Except for the persistent hypothermia group, the other four trajectory groups were more likely to have higher levels of C-reactive protein, lactic acid, cardiac troponin I, and D-dimer. Multivariable analysis revealed that hypothermia (adjusted odds ratio [aOR], 2.20; 95% confidence interval [95%CI], 1.35–3.57) and recurring tachypnea (aOR 2.44; 95%CI, 1.24–4.79) were independently associated with IHCA.Conclusions: We identified five novel vital-sign sub-phenotypes associated with a higher likelihood of IHCA, with distinct patterns in clinical course and laboratory markers. A better understanding of the pre-IHCA vital-sign trajectories may help with the early identification of deteriorating patients.</p