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When large-sized oil pipelines are subjected to skin effect heating under the constraint of limited current, the power supply converter must provide a higher current frequency. However, an inappropriate frequency can lead to increased energy losses and consequently reduce heating efficiency. To achieve higher heating efficiency of large-sized pipelines, this paper proposes a temperature control strategy based on optimal frequency forecast. First, a skin effect heating model is established to illustrate the necessity of frequency forecasting. Then, using the small sample data from the oil field, an optimal frequency forecasting method based on Gradient Boosting Decision Tree (GBDT) is proposed. At the forecasted frequency, a dual closed-loop control strategy for current and temperature, based on a designed three-phase converter, is employed to achieve temperature control under limited current conditions. The feasibility and effectiveness of this approach are demonstrated through a case study involving a 159 mm oil pipeline with a heating current of less than 80A. The experiment shows that with the forecasted frequency, the pipeline temperature reached 40 °C within 14 min, and the energy consumption per unit length of the pipeline is 394 W/m, complying with the standard Q/SY 06022-2016.

Antifungal resistance and antifungal tolerance are two distinct terms that describe different cellular responses to drugs. Antifungal resistance describes the ability of a fungus to grow above the minimal inhibitory concentration (MIC) of a drug. Antifungal tolerance describes the ability of drug susceptible strains to grow slowly at inhibitory drug concentrations. Recent studies indicate antifungal resistance and tolerance have distinct evolutionary trajectories. Superficial candidiasis bothers millions of people yearly. Miconazole has been used for topical treatment of yeast infections for over 40 years. Yet, fungal resistance to miconazole remains relatively low. Here we found different clinical isolates of Candida albicans had different profile of tolerance to miconazole, and the tolerance was modulated by physiological factors including temperature and medium composition. Exposure of non-tolerant strains with different genetic backgrounds to miconazole mainly induced development of tolerance, not resistance, and the tolerance was mainly due to whole chromosomal or segmental amplification of chromosome R. The efflux gene CDR1 was required for maintenance of tolerance in wild type strains but not required for gain of aneuploidy-mediated tolerance. Heat shock protein Hsp90 and calcineurin were essential for maintenance as well as gain of tolerance. Our study indicates development of aneuploidy-mediated tolerance, not resistance, is the predominant mechanism of rapid adaptation to miconazole in C. albicans, and the clinical relevance of tolerance deserves further investigations.

Planning and operational systemwide analyses relying on a deterministic optimal power flow (OPF) are subject to the uncertainties associated with the stochasticity of non-conventional renewables such as solar and wind. In this context, forecasting techniques will be essential for future power grids. An accurate and reliable forecast can complement a conventional time series optimal power flow (TSOPF) formulation by tackling uncertainty via accurate estimates of the intermittent generation resources. By doing so, the need for complex forecasting models is bypassed, and the computational tractability of the TSOPF problem is significantly reduced. Our work introduces a method to produce realistic load profiles, together with solar and wind generation forecasts. The generated data records are then input to a conventional TSOPF problem to determine the impact of an increasing share of non-conventional renewables into the grid over five years; we analyze increased penetration levels of 12%, 20%, 25%, and 30%. Our case study corresponds to an adapted version of the IEEE 39 test case, tailored to match the ISONE region transmission system. Forecasts are made using a data-driven neural network technique that accounts for the weather conditions in distinct locations of the ISONE footprint. Our results show several benefits of increased penetration of renewables, such as reducing line overloading and preventing undervoltage scenarios. However, it also points out potential problems that system planners might have to address by expanding the system or commissioning new equipment in particular locations.

Abstract Exosomal PD-L1 (exoPD-L1) has recently received significant attention as a biomarker predicting immunotherapeutic responses involving the PD1/PD-L1 pathway. However, current technologies for exosomal analysis rely primarily on bulk measurements that do not consider the heterogeneity found within exosomal subpopulations. Here, we present a nanoscale cytometry platform NanoEPIC, enabling phenotypic sorting and exoPD-L1 profiling from blood plasma. We highlight the efficacy of NanoEPIC in monitoring anti-PD-1 immunotherapy through the interrogation of exoPD-L1. NanoEPIC generates signature exoPD-L1 patterns in responders and non-responders. In mice treated with PD1-targeted immunotherapy, exoPD-L1 is correlated with tumor growth, PD-L1 burden in tumors, and the immune suppression of CD8+ tumor-infiltrating lymphocytes. Small extracellular vesicles (sEVs) with different PD-L1 expression levels display distinctive inhibitory effects on CD8 + T cells. NanoEPIC offers robust, high-throughput profiling of exosomal markers, enabling sEV subpopulation analysis. This platform holds the potential for enhanced cancer screening, personalized treatment, and therapeutic response monitoring.

Abstract Approximately 20% of cancer patients experience brain metastases in the advanced stages as circulating tumor cells migrate to and colonize the brain microvasculature. Due to the challenges associated with biopsies, our understanding of the tumor microenvironment and heterogeneity in brain metastases remains limited, hindering the development of systemic approaches for detection and treatment. Emerging evidence suggests that specific brain metastases induce a substantial level of immune activation and infiltration, which provides an opportunity to design specific immunotherapies targeting brain metastases. This perspective aims to summarize recent advancements in molecular profiling of the immune repertoires of brain metastases using biopsy‐based approaches, with an emphasis on tumor‐reactive T cells. Additionally, we discuss the potential of alternative tissues and technologies that offer improved temporal resolution, throughput, and fidelity for tracking tumor dynamics.

The primary goal of a power system is to provide consumers with reliable access to power at the most economical cost. Under the declining costs of renewable energy sources, the increasing cost of natural gas, and growing emissions control policies, investment in variable renewable energy (VRE) sources including wind and solar is accelerating. As a fundamental optimization tool in the operation and planning of electric power systems, the optimal power flow (OPF) is critical for setting the optimal state of control variables by minimizing desired objective while satisfying all related constraints. However, a comprehensive review of the generic OPF framework that includes all categories of objectives, control variables, and constraints will provide a valuable background to many of the integration studies that are necessary to facilitate the transition of energy systems. A comprehensive OPF framework is essential for researchers to identify the most critical challenges to their applications to develop new solution methods to improve computational efficiency and to take advantage of the increasing computing power to reduce the number of approximations in OPF models. In this work, we aim to provide a comprehensive survey and a generic OPF formulation, along with a detailed explanation of the major formulations for conventional OPF objective functions, control variables, and network constraints, in particular those related to the handling of VREs. This article also highlights the modeling and challenges in the distribution system, and potential formulations to incorporate with the significant variability and intermittency of VRE sources. In addition to a discussion of various formulations and foci for the OPF problem, we compare the implications of these decisions on a small case study to highlight differences.

Advancements in single-cell-related technologies have opened new possibilities for analyzing rare cells, such as circulating tumor cells (CTCs) and rare immune cells. Among these techniques, single-cell proteomics, particularly single-cell mass spectrometric analysis (scMS), has gained significant attention due to its ability to directly measure transcripts without the need for specific reagents. However, the success of single-cell proteomics relies heavily on efficient sample preparation, as protein loss in low-concentration samples can profoundly impact the analysis. To address this challenge, an effective handling system for rare cells is essential for single-cell proteomic analysis. Herein, we propose a microfluidics-based method that offers highly efficient isolation, detection, and collection of rare cells (e.g., CTCs). The detailed fabrication process of the micropillar array-based microfluidic device is presented, along with its application for CTC isolation, identification, and collection for subsequent proteomic analysis.

Stem cells hold promise in regenerative medicine due to their ability to proliferate and differentiate into various cell types. However, their self-renewal and multipotency also raise concerns about their tumorigenicity during and post-therapy. Indeed, multiple studies have reported the presence of stem cell-derived tumors in animal models and clinical administrations. Therefore, the assessment of tumorigenicity is crucial in evaluating the safety of stem cell-derived therapeutic products. Ideally, the assessment needs to be performed rapidly, sensitively, cost-effectively, and scalable. This article reviews various approaches for assessing tumorigenicity, including animal models, soft agar culture, PCR, flow cytometry, and microfluidics. Each method has its advantages and limitations. The selection of the assay depends on the specific needs of the study and the stage of development of the stem cell-derived therapeutic product. Combining multiple assays may provide a more comprehensive evaluation of tumorigenicity. Future developments should focus on the optimization and standardization of microfluidics-based methods, as well as the integration of multiple assays into a single platform for efficient and comprehensive evaluation of tumorigenicity.

Rare cells play essential roles in the initiation and progression of diseases and therefore their analysis is of great interest. The micro-magnetofluidic system is one of the emerging platforms that have been proposed for the rapid, sensitive, and cost-effective analysis of rare cells. Given its unprecedented throughput, micro-magnetofluidic systems have attracted substantial research interest in the last decade—multiple designs have been proposed, validated, and even advanced to the stage of clinical trials. This mini review aims to provide a timely summary of the relevant progress in the field thus far. We reviewed the concepts and realizations of micro-magnetofluidic devices based on the interaction between nanoparticles and on-chip micro-magnets. Their real-world applications in rare cell analysis were also highlighted and explained. In addition, we discussed the major challenges in the development and translation of micro-magnetofluidic into the clinic, including multi-marker capability and large-scale manufacturability.

Droplet impact affects water collection, which is the key to investigating the icing process on an aero-engine spinner. Different from a stationary spinner, droplet impact is affected by Coriolis acceleration and centrifugal acceleration on rotating aero-engine spinners, showing different impact dynamics. Based on the Eulerian method, using the rotating coordinate system we numerically investigated droplet impact characteristics on three different shapes of aero-engine spinners using ANSYS Fluent. The results indicate that the impact area covered all the windward surface on the conical spinner, and only covered the windward surface prior to the impingement limit of the elliptical spinner and the coniptical spinner. The sensitivity of water collection to inflow velocity declined in the order of coniptical the spinner, the elliptical spinner, and the conical spinner. In addition, the elliptical region could effectively improve aerodynamic performance, as shown in a lower total pressure loss through the spinner. This work is relevant to the anti-icing system of a rotating aero-engine spinner.

Background: Malignant pleural mesothelioma (MPM) is an aggressive cancer related to asbestos exposure. Early diagnosis is challenging due to generic symptoms and a lack of biomarkers. We previously demonstrated that mesothelial precursor cells (MPC) characterized by mesothelin (MSLN)+CD90+CD34+ could be implicated in the development of mesothelioma after asbestos exposure. Here, we aimed to determine the clinical significance of detecting MPC in blood for early-stage diagnosis and prognosis of mesothelioma. Methods: Due to the rarity of MPC in blood, it is challenging to identify this cell population using conventional techniques. Hence, we have developed a microfluidic liquid biopsy platform called MesoFind that utilizes an immunomagnetic, mesothelin capture strategy coupled with immunofluorescence to identify rare populations of cells at high sensitivity and precision. To validate our technique, we compared this approach to flow cytometry for the detection of MPC in murine blood and lavage samples. Upon successful validation of the murine samples, we then proceeded to examine circulating MPC in 23 patients with MPM, 23 asbestos-exposed individuals (ASB), and 10 healthy donors (HD) to evaluate their prognostic and diagnostic value. Finding: MPC were successfully detected in the blood of murine samples using MesoFind but were undetectable with flow cytometry. Circulating MPC were significantly higher in patients with epithelioid MPM compared to HD and ASB. The MPC subpopulation, MSLN+ and CD90+, were upregulated in ASB compared to HD suggesting an early role in pleural damage from asbestos. The MPC subpopulation, MSLN+ and CD34+, in contrast, were detected in advanced MPM and associated with markers of poor prognosis, suggesting a predominant role during cancer progression. Interpretation: The identification of circulating MPC presents an attractive solution for screening and early diagnosis of epithelioid mesothelioma. The presence of different subtypes of MPC have a prognostic value that could be of assistance with clinical decisions in patients with MPM. Funding: Princess Margaret Hospital Foundation Mesothelioma Research Fund, Toronto General & Western Hospital Foundation.

Endometritis is a common and important reproductive disease of domestic animals. The principal factors responsible for the disease are infection with Gram-negative bacteria, the release of Lipopolysaccharides (LPS) and activation of the TLR4/NF-κB signaling pathway. However, we do not fully understand the interaction between endometrial immunity and bacterial infection in the disease etiology. The ubiquitin-like protein ISG15 can regulate the TLR4/NF-κB signaling pathway via the ISGylation modification system, modulating the inflammatory response. In the present study, we found that ISG15 protein was expressed mainly in the cytoplasm of goat endometrial epithelial cells (gEECs) and that the expression of key genes and proteins of ISGylation increased in LPS-induced gEECs. Overexpression and silencing of the ISG15 gene demonstrated that ISGylation inhibited an LPS-induced inflammatory response via the TLR4/NF-κB signaling pathway in gEECs. Here, we provide the experimental basis for further exploration of the role of the ISGylation modification system in the inflammatory response of endometrium and a potential method for the treatment of endometritis.

Renewable energy sources including wind farms and solar sites, have been rapidly integrated within power systems for economic and environmental reasons. Unfortunately, many renewable energy sources suffer from variability and uncertainty, which may jeopardize security and stability of the power system. To face this challenge, it is necessary to develop new methods to manage increasing supply-side uncertainty within operational strategies. In modern power system operations, the optimal power flow (OPF) is essential to all stages of the system operational horizon; underlying both day-ahead scheduling and real-time dispatch decisions. The dispatch levels determined are then implemented for the duration of the dispatch interval, with the expectation that frequency response and balancing reserves are sufficient to manage intra-interval deviations. To achieve more accurate generation schedules and better reliability with increasing renewable resources, the OPF must be solved faster and with better accuracy within continuous time intervals, in both day-ahead scheduling and real-time dispatch. To this end, we formulate a multi-period dispatch framework, that is, progressive period optimal power flow (PPOPF), which builds on an interval optimal power flow (IOPF), which leverages median and endpoints on the interval to develop coherent coordinations between day-ahead and real-time period optimal power flow (POPF). Simulation case studies on a practical PEGASE 13,659-bus transmission system in Europe have demonstrated implementation of the proposed PPOPF within multi-stage power system operations, resulting in zero dispatch error and violation compared with traditional OPF.

With the dramatic increment of complexity, more microfluidic devices require 3D structures, such as multi-depth and -layer channels. The traditional multi-step photolithography is time-consuming and labor-intensive and also requires precise alignment during the fabrication of microfluidic devices. Here, we present an inexpensive, single-step, and rapid fabrication method for multi-depth microfluidic devices using a high-resolution liquid crystal display (LCD) stereolithographic (SLA) three-dimensional (3D) printing system. With the pixel size down to 47.25 μm, the feature resolutions in the horizontal and vertical directions are 150 μm and 50 μm, respectively. The multi-depth molds were successfully printed at the same time and the multi-depth features were transferred properly to the polydimethylsiloxane (PDMS) having multi-depth channels via soft lithography. A flow-focusing droplet generator with a multi-depth channel was fabricated using the presented 3D printing method. Experimental results show that the multi-depth channel could manipulate the morphology and size of droplets, which is desired for many engineering applications. Taken together, LCD SLA 3D printing is an excellent alternative method to the multi-step photolithography for the fabrication of multi-depth microfluidic devices. Taking the advantages of its controllability, cost-effectiveness, and acceptable resolution, LCD SLA 3D printing can have a great potential to fabricate 3D microfluidic devices.

Over the past decade, synthesized nanomaterials, such as carbon nanotube, nanoparticle, quantum dot, and nanowire, have already made breakthroughs in various fields, including biomedical sensors. Enormous surface area-to-volume ratio of the nanomaterials increases sensitivity dramatically compared with macro-sized material. Herein we present a comprehensive review about the working principle and fabrication process of nanowire sensor. Moreover, its applications for the detection of biomarker, virus, and DNA, as well as for drug discovery, are reviewed. Recent advances including self-powering, reusability, sensitivity in high ionic strength solvent, and long-term stability are surveyed and highlighted as well. Nanowire is expected to lead significant improvement of biomedical sensor in the near future.

Adipose-derived stem cells (ASCs) are a mesenchymal stem cell source with properties of self-renewal and multipotential differentiation. Compared to bone marrow-derived stem cells (BMSCs), ASCs can be derived from more sources and are harvested more easily. Three-dimensional (3D) tissue engineering scaffolds are better able to mimic the in vivo cellular microenvironment, which benefits the localization, attachment, proliferation, and differentiation of ASCs. Therefore, tissue-engineered ASCs are recognized as an attractive substitute for tissue and organ transplantation. In this paper, we review the characteristics of ASCs, as well as the biomaterials and tissue engineering methods used to proliferate and differentiate ASCs in a 3D environment. Clinical applications of tissue-engineered ASCs are also discussed to reveal the potential and feasibility of using tissue-engineered ASCs in regenerative medicine.

Genome-wide CRISPR screens have provided a systematic way to identify essential genetic regulators of a phenotype of interest with single-cell resolution. However, most screens use live/dead readout of viability to identify factors of interest. Here, we describe an approach that converts cell proliferation into the degree of magnetization, enabling downstream microfluidic magnetic sorting to be performed. We performed a head-to-head comparison and verified that the magnetic workflow can identify the same hits from a traditional screen while reducing the screening period from 4 weeks to 1 week. Taking advantage of parallelization and performance, we screened multiple mesenchymal cancer cell lines for their dependency on cell proliferation. We found and validated pan-and cell-specific potential therapeutic targets. The method presented provides a nanoparticle-enabled approach means to increase the breadth of data collected in CRISPR screens, enabling the rapid discovery of drug targets for treatment. [ABSTRACT FROM AUTHOR]