Phosphorylation-amplified synchronized droplet microfluidics sensitizes bacterial growth kinetic real-time monitoring.

The necessity for rapid and accurate bacterial growth monitoring is imperative across various domains, including healthcare and environmental safety. We introduce the self-synchronized droplet-amplified electrical screening cytometry (SYNC) system, a novel meld of droplet microfluidics and electrochemical amplification tailored for precise bacterial growth kinetic monitoring. SYNC encapsulates single bacteria in picolitre droplets, enabling real-time, fluorescence-free electrochemical monitoring. A specially devised phosphorylation-amplified culture medium translates bacterial metabolic activity into discernible electrical impedance changes. The dual-channel design and a rail-based structure in SYNC facilitate parallel screening and self-synchronization of droplets, addressing the limitations of conventional impedance cytometry. SYNC showcases a 5-fold enhancement in detection sensitivity and reduces 50% of the detection time compared to traditional approaches. Notably, SYNC is pioneering in providing exact initial bacterial concentrations, achieve to 104 bacteria/ml, a capability unmatched by existing real-time techniques measuring electrochemical variations. Along with its robust performance, this earmarks SYNC as a powerful tool for applications such as antibiotic susceptibility testing, food quality monitoring, and real-time water bacteria monitoring, paving the way for enhanced microbial process management and infection control.

Ultrahigh Passive Cooling Power in Hydrogel with Rationally Designed Optofluidic Properties.

The cooling power of a radiative cooler is more than halved in the tropics, e.g., Singapore, because of its harsh weather conditions including high humidity (84% on average), strong downward atmospheric radiation (∼40% higher than elsewhere), abundant rainfall, and intense solar radiation (up to 1200 W/m2 with ∼58% higher UV irradiation). So far, there has been no report of daytime radiative cooling that well achieves effective subambient cooling. Herein, through integrated passive cooling strategies in a hydrogel with desirable optofluidic properties, we demonstrate stable subambient (4-8 °C) cooling even under the strongest solar radiation in Singapore. The integrated passive cooler achieves an ultrahigh cooling power of ∼350 W/m2, 6-10 times higher than a radiative cooler in a tropical climate. An in situ study of radiative cooling with various hydration levels and ambient humidity is conducted to understand the interaction between radiation and evaporative cooling. This work provides insights for the design of an integrated cooler for various climates.

Rapid and Accurate Antimicrobial Susceptibility Testing Using Label-Free Electrical Impedance-Based Microfluidic Platform.

Antimicrobial resistance has become a serious threat to the global public health. Accurate and rapid antimicrobial susceptibility testing (AST) allows evidence-based prescribing of antibiotics to improve patient care and clinical outcomes. Current culture-based AST assays are inherently limited by the doubling time of bacterial reproduction, which require at least 24 h to have a decisive result. Herein, a label-free electrical impedance-based microfluidic platform designed to expedite and streamline AST procedure for clinical practice is presented. Following a 30-min exposure of bacterial samples to antibiotics, the presented high-throughput, single-bacterium level impedance characterization platform enables a rapid 2-min AST assay. The platform facilitates accurate analysis of individual bacterial viability, as indicated by changes in electrical characteristics, thereby enabling the determination of antimicrobial resistance. Moreover, the potential clinical applicability of this platform is demonstrated by testing different E. coli strains against five antibiotics, yielding 100% categorical agreements compared to standard culture methods.

Label-free multidimensional bacterial characterization with an ultrawide detectable concentration range by microfluidic impedance cytometry.

Rapid and accurate identification of bacteria is of great importance to public health in various fields, including medical diagnostics, food safety, and environmental monitoring. However, most existing bacterial detection methods have very narrow detectable concentration ranges and limited detection information, which easily leads to wrong diagnosis and treatment. This work presents a novel high-throughput microfluidic electrical impedance-based multidimensional single-bacterium profiling system for ultrawide concentration range detection and accurate differentiation of viability and Gram types of bacteria. The electrical impedance-based microfluidic cytometry is capable of multi-frequency impedance quantification, which allows profiling of the bacteria size, concentration, and membrane impedance as an indicator of bacterial viability and Gram properties in a single flow-through interrogation. It has been demonstrated that this novel impedance cytometry has an ultrawide bacterial counting range (102-108 cells per mL), and exhibits a rapid and accurate discrimination of viability and Gram types of bacteria in a label-free manner. Escherichia coli (E. coli) has been used as an analog species for the accuracy assessment of the electrical impedance-based bacterial detection system in an authentic complex beverage matrix within 24 hours. The impedance-based quantifications of viable bacteria are consistent with those obtained by the classical bacterial colony counting method (R2 = 0.996). This work could pave the way for providing a novel microfluidic cytometry system for rapid and multidimensional bacterial detection in diverse areas.

A power quality disturbances classification method based on multi-modal parallel feature extraction.

Power quality disturbance (PQD) is an important problem affecting the safe and stable operation of power system. Traditional single modal methods not only have a large number of parameters, but also usually focus on only one type of feature, resulting in incomplete information about the extracted features, and it is difficult to identify complex and diverse PQD types in modern power systems. In this regard, this paper proposes a multi-modal parallel feature extraction and classification model. The model pays attention to both temporal and spatial features of PQD, which effectively improves classification accuracy. And a lightweight approach is adopted to reduce the number of parameters of the model. The model uses Long Short Term Memory Neural Network (LSTM) to extract the temporal features of one-dimensional temporal modes of PQD. At the same time, a lightweight residual network (LResNet) is designed to extract the spatial features of the two-dimensional image modality of PQD. Then, the two types of features are fused into multi-modal spatio-temporal features (MSTF). Finally, MSTF is input to a Support Vector Machine (SVM) for classification. Simulation results of 20 PQD signals show that the classification accuracy of the multi-modal model proposed in this paper reaches 99.94%, and the parameter quantity is only 0.08 MB. Compared with ResNet18, the accuracy of the proposed method has been improved by 2.55% and the number of parameters has been reduced by 99.25%.

DUPLETS: Deformability-Assisted Dual-Particle Encapsulation Via Electrically Activated Sorting.

Co-encapsulation of bead carriers and biological cells in microfluidics has become a powerful technique for various biological assays in single-cell genomics and drug screening because of its distinct capability of single-cell confinement. However, current co-encapsulation approaches exist a trade-off between cell/bead pairing rate and probability of multiple cells in individual droplets, significantly limiting the effective throughput of single-paired cell-bead droplets production. Deformability-assisted dUal-Particle encapsuLation via Electrically acTivated Sorting (DUPLETS) system is reported to overcome this problem. The DUPLETS can differentiate the encapsulated content in individual droplets and sort out targeted droplets via a combined screening of mechanical and electrical characteristics of single droplets in label-free manners and with the highest effective throughput in comparison to current commercial platforms. The DUPLETS has been demonstrated to enrich single-paired cell-bead droplets to over 80% (above eightfold higher than current co-encapsulation techniques). It eliminates multicell droplets to 0.1% whereas up to ≈24% in 10× Chromium. It is believed that merging DUPLETS into the current co-encapsulation platforms can meaningfully elevate sample quality in terms of high purity of single-paired cell-bead droplets, low fraction of multicell droplets, and high cell viability, which can benefit a multitude of biological assay applications.

Selectable encapsulated cell quantity in droplets via label-free electrical screening and impedance-activated sorting.

Single-cell encapsulation in droplets has become a powerful tool in immunotherapy, medicine discovery, and single-cell analysis, thanks to its capability for cell confinement in picoliter volumes. However, the purity and throughput of single-cell droplets are limited by random encapsulation process, which resuts in a majority of empty and multi-cells droplets. Herein we introduce the first label-free selectable cell quantity encapsulation in droplets sorting system to overcome this problem. The system utilizes a simple and reliable electrical impedance based screening (98.9% of accuracy) integrated with biocompatible acoustic sorting to select single-cell droplets, achieving 90.3% of efficiency and up to 200 â€‹Hz of throughput, by removing multi-cells (∼60% of rejection) and empty droplets (∼90% of rejection). We demonstrate the use of the droplet sorting to improve the throughput of single-cell encapsulation by ∼9-fold compared to the conventional random encapsulation process.

Machine learning empowered multi-stress level electromechanical phenotyping for high-dimensional single cell analysis.

Microfluidics provides a powerful platform for biological analysis by harnessing the ability to precisely manipulate fluids and microparticles with integrated microsensors. Here, we introduce an imaging and impedance cell analyzer (IM2Cell), which implements single cell level impedance analysis and hydrodynamic mechanical phenotyping simultaneously. For the first time, IM2Cell demonstrates the capability of multi-stress level mechanical phenotyping. Specifically, IM2Cell is capable of characterizing cell diameter, three deformability responses, and four electrical properties. It presents high-dimensional information to give insight into subcellular components such as cell membrane, cytoplasm, cytoskeleton, and nucleus. In this work, we first validate imaging and impedance-based cell analyses separately. Then, the two techniques are combined to obtain both imaging and impedance data analyzed by machine learning method, exhibiting an improved prediction accuracy from 83.1% to 95.4% between fixed and living MDA-MB-231 breast cancer cells. Next, IM2Cell demonstrates 91.2% classification accuracy in a mixture of unlabeled MCF-10A, MCF-7, and MDA-MB-231 cell lines. Finally, an application demonstrates the potential of IM2Cell for the deformability studies of peripheral blood mononuclear cells (PBMCs) subpopulations without cumbersome isolation or labeling steps.

A Systematic Study of Size Correlation and Young's Modulus Sensitivity for Cellular Mechanical Phenotyping by Microfluidic Approaches.

Cellular mechanical properties are a class of intrinsic biophysical markers for cell state and health. Microfluidic mechanical phenotyping methods have emerged as promising tools to overcome the challenges of low throughput and high demand for manual skills in conventional approaches. In this work, two types of microfluidic cellular mechanical phenotyping methods, contactless hydro-stretching deformability cytometry (lh-DC) and contact constriction deformability cytometry (cc-DC) are comprehensively studied and compared. Polymerized hydrogel beads with defined sizes are used to characterize a strong negative correlation between size and deformability in cc-DC (r = -0.95), while lh-DC presents a weak positive correlation (r = 0.13). Young's modulus sensitivity in cc-DC is size-dependent while it is a constant in lh-DC. Moreover, the deformability assessment for human breast cell line mixture suggests the lh-DC exhibits better differentiation capability of cells with different size distributions, while cc-DC provides higher sensitivity to identify cellular mechanical changes within a single cell line. This work is the first to present a quantitative study and comparison of size correlation and Young's modulus sensitivity of contactless and contact microfluidic mechanical phenotyping methods, which provides guidance to choose the most suitable cellular mechanical phenotyping platform for specific cell analysis applications.

Submicron-precision particle characterization in microfluidic impedance cytometry with double differential electrodes.

Submicron-precision particle characterization is crucial for counting, sizing and identifying a variety of biological particles, such as bacteria and apoptotic bodies. Microfluidic impedance cytometry has been attractive in current research for microparticle characterization due to its advantages of label-free detection, ease of miniaturization and affordability. However, conventional electrode configurations of three electrodes and floating electrodes have not yet demonstrated the capability of probing submicron particles or microparticles with a submicron size difference. In this study, we present a label-free high-throughput (∼800 particles per second) impedance-based microfluidic flow cytometry system integrated with a novel design of a double differential electrode configuration, enabling submicron particle detection (down to 0.4 µm) with a minimum size resolution of 200 nm. The signal-to-noise ratio has been boosted from 13.98 dB to 32.64 dB compared to a typical three-electrode configuration. With the proposed microfluidic impedance cytometry, we have shown results of sizing microparticles that accurately correlate with manufacturers' datasheets (R2 = 0.99938). It also shows that population ratios of differently sized beads in mixture samples are consistent with the results given by commercial fluorescence-based flow cytometry (within ∼1% difference). This work provides a label-free approach with submicron precision for sizing and counting microscale and submicron particles, and a new avenue of designing electrode configurations with a feature of suppressing the electrical noise for accomplishing a high signal-to-noise ratio in a wide range of frequencies. This novel double differential impedance sensing system paves a new pathway for real-time analysis and accurate particle screening in pathological and pharmacological research.

Single-Cell Stretching in Viscoelastic Fluids with Electronically Triggered Imaging for Cellular Mechanical Phenotyping.

Cellular mechanical phenotypes in connection to physiological and pathological states of cells have become a promising intrinsic biomarker for label-free cell analysis in various biological research and medical diagnostics. In this work, we present a microfluidic system capable of high-throughput cellular mechanical phenotyping based on a rapid single-cell hydrodynamic stretching in a continuous viscoelastic fluid flow. Randomly introduced single cells are first aligned into a single streamline in viscoelastic fluids before being guided to a flow splitting junction for consistent hydrodynamic stretching. The arrival of individual cells prior to the flow splitting junction can be detected by an electrical sensing unit, which produces a triggering signal to activate a high-speed camera for on-demand imaging of the cell motion and deformation through the flow splitting junction. Cellular mechanical phenotypes, including cell size and cell deformability, are extracted from the analysis of these captured single-cell images. We have evaluated the sensitivity of the developed microfluidic mechanical phenotyping system by measuring the synthesized hydrogel microbeads with known Young's modulus. With this microfluidic cellular mechanical phenotyping system, we have revealed the statistical difference in the deformability of microfilament disrupted, normal, and fixed NIH 3T3 fibroblast cells. Furthermore, with the implementation of a machine-learning-based classification of MCF-10A and MDA-MB-231 mixtures, our label-free cellular phenotyping system has achieved a comparable cell analysis accuracy (0.9:1, 5.03:1) with respect to the fluorescence-based flow cytometry results (0.97:1, 5.33:1). The presented microfluidic mechanical phenotyping technique will open new avenues for high-throughput and label-free single-cell analysis in diverse biomedical applications.

Multi-frequency single cell electrical impedance measurement for label-free cell viability analysis.

Cell viability is a physiological status connected to cell membrane integrity and cytoplasmic topography, which is profoundly important for fundamental biological research and practical biomedical applications. A conventional method for assessing cell viability is through cell staining analysis. However, cell staining involves laborious and complicated processing procedures and is normally cytotoxic. Intrinsic cellular phenotypes thus provide new avenues for measuring cell viability in a stain-free and non-toxic manner. In this work, we present a label-free non-destructive impedance-based approach for cell viability assessment by simultaneously characterizing multiple electrical cellular phenotypes in a high-throughput manner (>1000 cells per min). A novel concept called the complex opacity spectrum is introduced for improving the discrimination of live and dead cells. The analysis of the complex opacity spectrum leads to the discovery of two frequency ranges that are optimized for characterizing membranous and cytoplasmic electrical phenotypes. The present impedance-based approach has successfully discriminated between living and dead cells in two different experimental scenarios, including mixed living and dead cells in both homogenous and heterogeneous cell samples. This impedance-based single cell phenotyping technique provides highly accurate and consistent cell viability analysis, which has been validated by commercial fluorescence-based flow cytometry (∼1% difference) using heterogeneous cell samples. This label-free high-throughput cell viability analysis strategy will have broad applications in the field of biology and medicine.

Fine-mapping qFS07.1 controlling fiber strength in upland cotton (Gossypium hirsutum L.).

KEY MESSAGE: qFS07.1 controlling fiber strength was fine-mapped to a 62.6-kb region containing four annotated genes. RT-qPCR and sequence of candidate genes identified an LRR RLK gene as the most likely candidate. Fiber strength is an important component of cotton fiber quality and is associated with other properties, such as fiber maturity, fineness, and length. Stable QTL qFS07.1, controlling fiber strength, had been identified on chromosome 7 in an upland cotton recombinant inbred line (RIL) population from a cross (CCRI35 × Yumian1) described in our previous studies. To fine-map qFS07.1, an F2 population with 2484 individual plants from a cross between recombinant line RIL014 and CCRI35 was established. A total of 1518 SSR primer pairs, including 1062, designed from chromosome 1 of the Gossypium raimondii genome and 456 from chromosome 1 of the G. arboreum genome (corresponding to the QTL region) were used to fine-map qFS07.1, and qFS07.1 was mapped into a 62.6-kb genome region which contained four annotated genes on chromosome A07 of G. hirsutum. RT-qPCR and comparative analysis of candidate genes revealed a leucine-rich repeat protein kinase (LRR RLK) family protein to be a promising candidate gene for qFS07.1. Fine mapping and identification of the candidate gene for qFS07.1 will play a vital role in marker-assisted selection (MAS) and the study of mechanism of cotton fiber development.

Fine mapping and RNA-Seq unravels candidate genes for a major QTL controlling multiple fiber quality traits at the T1 region in upland cotton.

BACKGROUND: Improving fiber quality is a major challenge in cotton breeding, since the molecular basis of fiber quality traits is poorly understood. Fine mapping and candidate gene prediction of quantitative trait loci (QTL) controlling cotton fiber quality traits can help to elucidate the molecular basis of fiber quality. In our previous studies, one major QTL controlling multiple fiber quality traits was identified near the T1 locus on chromosome 6 in Upland cotton. RESULTS: To finely map this major QTL, the F2 population with 6975 individuals was established from a cross between Yumian 1 and a recombinant inbred line (RIL118) selected from a recombinant inbred line population (T586 × Yumian 1). The QTL was mapped to a 0.28-cM interval between markers HAU2119 and SWU2302. The QTL explained 54.7 % (LOD = 222.3), 40.5 % (LOD = 145.0), 50.0 % (LOD = 194.3) and 30.1 % (LOD = 100.4) of phenotypic variation with additive effects of 2.78, -0.43, 2.92 and 1.90 units for fiber length, micronaire, strength and uniformity, respectively. The QTL region corresponded to a 2.7-Mb interval on chromosome 10 in the G. raimondii genome sequence and a 5.3-Mb interval on chromosome A06 in G. hirsutum. The fiber of Yumian 1 was much longer than that of RIL118 from 3 DPA to 7 DPA. RNA-Seq of ovules at 0 DPA and fibers at 5 DPA from Yumian 1 and RIL118 showed four genes in the QTL region of the G. raimondii genome to be extremely differentially expressed. RT-PCR analysis showed three genes in the QTL region of the G. hirsutum genome to behave similarly. CONCLUSIONS: This study mapped a major QTL influencing four fiber quality traits to a 0.28-cM interval and identified three candidate genes by RNA-Seq and RT-PCR analysis. Integration of fine mapping and RNA-Seq is a powerful strategy to uncover candidates for QTL in large genomes.

Practice size, financial sharing and quality of care.

BACKGROUND: Although we are observing a general move towards larger primary care practices, surprisingly little is known about the influence of key components of practice organization on primary care. We aimed to determine the relationships between practice size, and revenue sharing agreements, and quality of care. METHODS: As part of a large cross sectional study, group practices were randomly selected from different primary care service delivery models in Ontario. Patient surveys and chart reviews were used to assess quality of care. Multilevel regressions controlled for patient, provider and practice characteristics. RESULTS: Positive statistically significant associations were found between the logarithm of group size and access, comprehensiveness, and disease prevention. Negative significant associations were found between logarithm group size and continuity. No differences were found for chronic disease management and health promotion. Practices that shared revenues were found to deliver superior health promotion compared to those who did not. Interacting group size with the presence of a revenue-sharing arrangement had a negative impact on health promotion. CONCLUSIONS: Despite the limitations of our study, our findings have provided preliminary evidence of the tradeoffs inherent with increasing practice size. Larger group size is associated with better access and comprehensiveness but worse continuity of care. Revenue sharing in group practices was associated with higher health promotion compared to sharing only common costs. Further work is required to better inform policy makers and practitioners as to whether the pattern revealed in larger practices mitigates any of the previously reported benefits of continuity of primary care. We found few benefits of revenue sharing--even then the effect of revenue sharing on health promotion seemed diminished in larger practices.

A cost-consequences analysis of a primary care librarian question and answering service.

BACKGROUND: Cost consequences analysis was completed from randomized controlled trial (RCT) data for the Just-in-time (JIT) librarian consultation service in primary care that ran from October 2005 to April 2006. The service was aimed at providing answers to clinical questions arising during the clinical encounter while the patient waits. Cost saving and cost avoidance were also analyzed. The data comes from eighty-eight primary care providers in the Ottawa area working in Family Health Networks (FHNs) and Family Health Groups (FHGs). METHODS: We conducted a cost consequences analysis based on data from the JIT project. We also estimated the potential economic benefit of JIT librarian consultation service to the health care system. RESULTS: The results show that the cost per question for the JIT service was $38.20. The cost could be as low as $5.70 per question for a regular service. Nationally, if this service was implemented and if family physicians saw additional patients when the JIT service saved them time, up to 61,100 extra patients could be seen annually. A conservative estimate of the cost savings and cost avoidance per question for JIT was $11.55. CONCLUSIONS: The cost per question, if the librarian service was used at full capacity, is quite low. Financial savings to the health care system might exceed the cost of the service. Saving physician's time during their day could potentially lead to better access to family physicians by patients. Implementing a librarian consultation service can happen quickly as the time required to train professional librarians to do this service is short.

The cost of integrating a physical activity counselor in the primary health care team.

OBJECTIVE: This article assesses direct costs of integrating a physical activity counselor (PAC) into primary health care teams to improve physical activity levels of inactive patients. METHODS: A monthly cost analysis was conducted using data from 120 inactive patients, aged 18 to 69 years, who were recruited from a community-based family medicine practice. Relevant cost items for the intensive counseling group included (1) office expenses; (2) equipment purchases; (3) operating costs; (4) costs of training the PAC; and (5) labor costs. Physical and human capital were amortized over a 5-year horizon at a discount rate of 5%. RESULTS: Integrating a PAC into the primary health care team incurred an estimated one-time cost of CA$91.43 per participant per month. Results were very sensitive to the number of patients counseled. CONCLUSIONS: The costs associated with the intervention are lower than many other intervention studies attempting to improve population physical activity levels. Demonstrating this competitive cost base should encourage additional research to assess the effectiveness of integrating a PAC into primary health care teams to promote active living among patients who do not meet recommended physical activity levels.