Recent Approaches to Design and Analysis of Electrical Impedance Systems for Single Cells Using Machine Learning.

Individual cells have many unique properties that can be quantified to develop a holistic understanding of a population. This can include understanding population characteristics, identifying subpopulations, or elucidating outlier characteristics that may be indicators of disease. Electrical impedance measurements are rapid and label-free for the monitoring of single cells and generate large datasets of many cells at single or multiple frequencies. To increase the accuracy and sensitivity of measurements and define the relationships between impedance and biological features, many electrical measurement systems have incorporated machine learning (ML) paradigms for control and analysis. Considering the difficulty capturing complex relationships using traditional modelling and statistical methods due to population heterogeneity, ML offers an exciting approach to the systemic collection and analysis of electrical properties in a data-driven way. In this work, we discuss incorporation of ML to improve the field of electrical single cell analysis by addressing the design challenges to manipulate single cells and sophisticated analysis of electrical properties that distinguish cellular changes. Looking forward, we emphasize the opportunity to build on integrated systems to address common challenges in data quality and generalizability to save time and resources at every step in electrical measurement of single cells.

Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning.

Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.

Broadband Electrical Spectroscopy to Distinguish Single-Cell Ca2+ Changes Due to Ionomycin Treatment in a Skeletal Muscle Cell Line.

Many skeletal muscle diseases such as muscular dystrophy, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and sarcopenia share the dysregulation of calcium (Ca2+) as a key mechanism of disease at a cellular level. Cytosolic concentrations of Ca2+ can signal dysregulation in organelles including the mitochondria, nucleus, and sarcoplasmic reticulum in skeletal muscle. In this work, a treatment is applied to mimic the Ca2+ increase associated with these atrophy-related disease states, and broadband impedance measurements are taken for single cells with and without this treatment using a microfluidic device. The resulting impedance measurements are fitted using a single-shell circuit simulation to show calculated electrical dielectric property contributions based on these Ca2+ changes. From this, similar distributions were seen in the Ca2+ from fluorescence measurements and the distribution of the S-parameter at a single frequency, identifying Ca2+ as the main contributor to the electrical differences being identified. Extracted dielectric parameters also showed different distribution patterns between the untreated and ionomycin-treated groups; however, the overall electrical parameters suggest the impact of Ca2+-induced changes at a wider range of frequencies.

Local practices and production confer resilience to rural Pacific food systems during the COVID-19 pandemic.

Resilience of food systems is key to ensuring food security through crisis. The COVID-19 pandemic presents an unprecedented shock that reveals varying levels of resilience of increasingly interconnected food systems across the globe. We contribute to the ongoing debate about whether increased connectivity reduces or enhances resilience in the context of rural Pacific food systems, while examining how communities have adapted to the global shocks associated with the pandemic to ensure food security. We conducted 609 interviews across 199 coastal villages from May to October 2020 in Federated States of Micronesia, Fiji, Palau, Papua New Guinea, Solomon Islands, Tonga, and Tuvalu to understand community-level impacts and adaptations during the first 5-10 months of the COVID-19 crisis. We found that local food production practices and food sharing conferred resilience, and that imported foods could aid or inhibit resilience. Communities in countries more reliant on imports were almost twice as likely to report food insecurity compared to those least reliant. However, in places dealing with a concurrent cyclone, local food systems were impaired, and imported foods proved critical. Our findings suggest that policy in the Pacific should bolster sustainable local food production and practices. Pacific states should avoid becoming overly reliant on food imports, while having measures in place to support food security after disasters, supplementing locally produced and preserved foods with imported foods when necessary. Developing policies that promote resilient food systems can help prepare communities for future shocks, including those anticipated with climate change.

Immunosuppression for progressive membranous nephropathy: a UK randomised controlled trial.

BACKGROUND: Membranous nephropathy leads to end-stage renal disease in more than 20% of patients. Although immunosuppressive therapy benefits some patients, trial evidence for the subset of patients with declining renal function is not available. We aimed to assess whether immunosuppression preserves renal function in patients with idiopathic membranous nephropathy with declining renal function. METHODS: This randomised controlled trial was undertaken in 37 renal units across the UK. We recruited patients (18-75 years) with biopsy-proven idiopathic membranous nephropathy, a plasma creatinine concentration of less than 300 µmol/L, and at least a 20% decline in excretory renal function measured in the 2 years before study entry, based on at least three measurements over a period of 3 months or longer. Patients were randomly assigned (1:1:1) by a random number table to receive supportive treatment only, supportive treatment plus 6 months of alternating cycles of prednisolone and chlorambucil, or supportive treatment plus 12 months of ciclosporin. The primary outcome was a further 20% decline in renal function from baseline, analysed by intention to treat. The trial is registered as an International Standard Randomised Controlled Trial, number 99959692. FINDINGS: We randomly assigned 108 patients, 33 of whom received prednisolone and chlorambucil, 37 ciclosporin, and 38 supportive therapy alone. Two patients (one who received ciclosporin and one who received supportive therapy) were ineligible, so were not included in the intention-to-treat analysis, and 45 patients deviated from protocol before study end, mostly as a result of minor dose adjustments. Follow up was until primary endpoint or for minimum of 3 years if primary endpoint was not reached. Risk of further 20% decline in renal function was significantly lower in the prednisolone and chlorambucil group than in the supportive care group (19 [58%] of 33 patients reached endpoint vs 31 [84%] of 37, hazard ratio [HR] 0·44 [95% CI 0·24-0·78]; p=0·0042); risk did not differ between the ciclosporin (29 [81%] of 36) and supportive treatment only groups (HR 1·17 [0·70-1·95]; p=0·54), but did differ significantly across all three groups (p=0·003). Serious adverse events were frequent in all three groups but were higher in the prednisolone and chlorambucil group than in the supportive care only group (56 events vs 24 events; p=0·048). INTERPRETATION: For the subset of patients with idiopathic membranous nephropathy and deteriorating excretory renal function, 6 months' therapy with prednisolone and chlorambucil is the treatment approach best supported by our evidence. Ciclosporin should be avoided in this subset. FUNDING: Medical Research Council, Novartis, Renal Association, Kidney Research UK.

Broadband electrical impedance as a novel characterization of oxidative stress in single L6 skeletal muscle cells.

Oxidative stress (OS) is one of the leading causes of cytotoxicity and is linked to many human physio-pathological conditions. In particular, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) induced by OS is debilitating to quality of life, while no clear biological markers have been identified for diagnostic measures. Recently, impedance measurements of peripheral blood cells of ME/CFS patients have been shown as a promising approach to diagnose the disease. Inspired by this study and aiming to interrogate muscle cells directly, we investigated if broadband measurements of single muscle cells could differentiate normal and oxidatively stressed cell populations. We first optimized a protocol through H2O2 treatment to introduce oxidative stress to cultured rat L6 skeletal muscle cells. The treated cells were further characterized through broadband impedance spectroscopy of single cells using a microfluidic lab-on-a-chip system. The resulting dielectric properties of cytoplasm permittivity and conductivity are electrically distinct from normally cultured cells. The reflection and transmission coefficients, ΔS11 and ΔS21, of the normal cells are tightly clustered and closely resemble those of the cell-free solution across the frequency range of 9 kHz to 9 GHz. On the other hand, dielectric properties of the oxidized cells have a wide distribution in the GHz range, deviating both in the positive and negative directions from the normally cultured cells. Simulation results guide our hypothesis that the dielectric differences could be linked to ion alterations, while calcium imaging directly supports the contribution of calcium flux to the observed deviation of S parameters. The unique electrical profile associated with oxidized cells in the GHz frequencies provide a framework for future development of technologies to diagnose oxidative-stress related diseases such as ME/CFS.

Harnessing the diversity of small-scale actors is key to the future of aquatic food systems.

Small-scale fisheries and aquaculture (SSFA) provide livelihoods for over 100 million people and sustenance for ~1 billion people, particularly in the Global South. Aquatic foods are distributed through diverse supply chains, with the potential to be highly adaptable to stresses and shocks, but face a growing range of threats and adaptive challenges. Contemporary governance assumes homogeneity in SSFA despite the diverse nature of this sector. Here we use SSFA actor profiles to capture the key dimensions and dynamism of SSFA diversity, reviewing contemporary threats and exploring opportunities for the SSFA sector. The heuristic framework can inform adaptive governance actions supporting the diversity and vital roles of SSFA in food systems, and in the health and livelihoods of nutritionally vulnerable people-supporting their viability through appropriate policies whilst fostering equitable and sustainable food systems.

Predicting 30-minute postdialysis blood urea concentrations using the stop dialysate flow method.

The stop dialysate flow (SDF) method has been the recommended method of postdialysis urea sampling by the Scottish Renal Association since November 1998. However, this method does not lend itself to calculation of Kt/V using currently favored formulas, which require either a 30-minute postdialysis sample or a 20-second "slow flow" sample. We, therefore, derived a formula that uses a 5-minute postdialysis urea sample using the SDF method to estimate the urea concentration at 30 minutes. Blood samples were obtained from 70 hemodialysis patients immediately before dialysis and at 0, 5, and 30 minutes postdialysis. Half of the patients from each unit were randomly selected to form the linear regression equation: Estimated 30-minute urea concentration = 1.06 x (5-minute urea concentration) + 0.22. This equation was validated using the data from the remaining 35 patients. This showed a very close correlation between measured and estimated urea concentration at 30 minutes (R2 = 0.97), and a Bland-Altman plot confirmed this close relationship. The sensitivity, specificity, positive, and negative predictive values of this equation were high when used to estimate 30-minute urea reduction ratio (URR) greater than 65% (100%, 85.7%, 97%, and 100%, respectively) and 30-minute Kt/V greater than 1. 2 (96.7%, 100%, 100%, and 80%, respectively). The coupling of the SDF method with the above formula combines the advantages of simple and reproducible postdialysis blood sampling with an accurate estimation of the 30-minute postdialysis blood urea concentration, URR, and Kt/V. This method should be a useful tool for comparative audit of hemodialysis adequacy.