Single Technology Research Articles

HyDesign: a tool for sizing optimization of grid-connected hybrid power plants including wind, solar photovoltaic, and lithium-ion batteries

Abstract. Hybrid renewable power plants consisting of collocated wind, solar photovoltaic (PV), and lithium-ion battery storage connected behind a single grid connection can provide additional value to the owners and society in comparison to individual technology plants, such as those that are only wind or only PV. The hybrid power plants considered in this article are connected to the grid and share electrical infrastructure costs across different generation and storing technologies. In this article, we propose a methodology for sizing hybrid power plants as a nested-optimization problem: with an outer sizing optimization and an internal operation optimization. The outer sizing optimization maximizes the net present values over capital expenditures and compares it with standard designs that minimize the levelized cost of energy. The sizing problem formulation includes turbine selection (in terms of rated power, specific power, and hub height), a wind plant wake loss surrogate, simplified wind and PV degradation models, battery degradation, and operation optimization of an internal energy management system. The problem of outer sizing optimization is solved using a new parallel “efficient global optimization” algorithm. This new algorithm is a surrogate-based optimization method that ensures a minimal number of model evaluations but ensures a global scope in the optimization. The methodology presented in this article is available in an open-source tool called HyDesign. The hybrid sizing algorithm is applied for a peak power plant use case at different locations in India where renewable energy auctions impose a monetary penalty when energy is not supplied at peak hours. We compare the hybrid power plant sizing results when using two different objective functions: the levelized cost of energy (LCoE) or the relative net present value with respect to the total capital expenditure costs (NPV/CH). Battery storage is installed only on NPV/CH-based designs, while the hybrid design, including wind, solar, and battery, only occurs on the site with good wind resources. Wind turbine selection on this site prioritizes cheaper turbines with a lower hub height and lower rated power. The number of batteries replaced changes at the different sites, ranging between two or three units over the lifetime. A significant oversizing of the generation in comparison to the grid connection occurs on all NPV/CH-based designs. As expected LCoE-based designs are a single technology with no batteries.

Liquid induced vibrations of partially liquid-filled elastic cylindrical-conical shells

The main objective of this study to develop efficient numerical techniques based on coupled finite and boundary element methods to estimate natural vibration frequencies in compound reservoirs with liquid. Elastic structures composed of cylindrical and conical shells connected by rings have been examined. The space between the shells is filled with an ideal, incompressible fluid. The advantage of the proposed approach lies in the ability to investigate both free and forced vibrations of empty and liquid-filled shells structures within the framework of the single computer technology. The benchmark test calculations demonstrated the high accuracy and efficiency of the proposed approach. The novelty and practical value of the obtained results lie in the ability to investigate fuel tanks of complex shapes under various conditions.

Single Bale-Bale Technology: Sustainable Utilization of Flying Fish Eggs in the Waters of the Aru Islands, Indonesia

The waters of Eastern Indonesia constitute a potential area for the utilization of flying fish eggs. The capture of fish eggs relies on the behavior of parent fish that deposit their eggs on floating objects at the sea surface. The technology is known by the name drifting FAD or its local name, “bale-bale”. However, the tendency of fishermen is to design double bale-bale for maximum utilization without considering the sustainability of the fishery resources. This research aims to develop single bale-bale technology for sustainable utilization of flying fish eggs in the waters of the Aru Islands, Indonesia. The vertical single bale-bale is an innovative system designed to enhance the efficiency of capturing flying fish eggs, reduce environmental impact, and support sustainable utilization. The research methodology involves the design and implementation of bale-bale, followed by performance evaluation and environmental impact analysis. The results of the study indicate that the vertical single bale-bale is more effective and sustainable compared to horizontal single bale-bale, mixed, or double configurations. Consequently, this research contributes to improving economic and ecological resilience while promoting environmentally friendly fishing practices.

The Role of Immune Cells in DKD: Mechanisms and Targeted Therapies.

Diabetic kidney disease (DKD), is a common microvascular complication and a major cause of death in patients with diabetes. Disorders of immune cells and immune cytokines can accelerate DKD development of in a number of ways. As the kidney is composed of complex and highly differentiated cells, the interactions among different cell types and immune cells play important regulatory roles in disease development. Here, we summarize the latest research into the molecular mechanisms underlying the interactions among various immune and renal cells in DKD. In addition, we discuss the most recent studies related to single cell technology and bioinformatics analysis in the field of DKD. The aims of our review were to explore immune cells as potential therapeutic targets in DKD and provide some guidance for future clinical treatments.

Security Analysis of Differential Chaotic Keying in Optical Communication

Space free optical communication (FSO) has the advantages of wide bandwidth resources, less susceptibility to attacks, strong resistance to interference, and low losses. The FSO system itself has high security, with the realization of single photon detection technology, the stealer can obtain information without blocking the beam propagation. So using chaotic encryption methods can further improve the security performance of communication systems. This article uses a gamma gamma turbulence model and utilizes the differential chaotic shift keying (DCSK) method of communication systems to improve the system’s resistance to attacks. The theoretical expression of the system error rate under this model is derived, and the security performance of the system is further analyzed. Through experimental simulation, it is proved that the system has better resistance to attacks and lower bit error rates.

Building Information Modeling (BIM), Blockchain, and LiDAR Applications in Construction Lifecycle: Bibliometric, and Network Analysis

Investigating Industry 4.0 technologies and studying their impacts on various aspects of the construction industry, including stakeholders and the lifecycle, is vital to enhance novel applications of such technologies in an industry that is known as Construction 4.0. The main objective of the current state-of-the-art review is to provide a comprehensive literature review on three widely used Industry 4.0 technologies, Building Information Modeling (BIM), Blockchain, and LiDAR, which have strong potential to promote and optimize different activities of the project, and also, the integration of them can greatly impact the construction industry in the whole project lifecycle. A bibliometric analysis of keyword co-occurrence and citations revealed a significant number of publications from 2014 to 2023 investigating the selected technologies. Recent trends indicate that the majority of papers have considered the selected technologies in the integration with each other. However, a specific gap exists in the literature regarding the interactions and potential synergies among these technologies. This gap limits the understanding of how these integrations can address challenges unique to the construction industry and hinders the development of comprehensive solutions. The review has been analyzed and discussed in reference to the type of article, single or multi technologies, the lifecycle, and their applications. The study showed that the integration of BIM, Blockchain, and LiDAR, as a recent trend and as a beneficial solution to automate the whole construction process, has considerable capacities to improve the productivity of the construction industry. Finally, some application areas for the integration of these three technologies are concluded and are suggested, and therefore, an advantageous reference has been provided for scholars to plan their future research in this sector.

Prediction of Occult Hemorrhage in the Lower Body Negative Pressure Model: Initial Validation of Machine Learning Approaches.

Detection of occult hemorrhage (OH) before progression to clinically apparent changes in vital signs remains an important clinical problem in managing trauma patients. The resource-intensiveness associated with continuous clinical patient monitoring and rescue from frank shock makes accurate early detection and prediction with noninvasive measurement technology a desirable innovation. Despite significant efforts directed toward the development of innovative noninvasive diagnostics, the implementation and performance of the newest bedside technologies remain inadequate. This poor performance may reflect the limitations of univariate systems based on one sensor in one anatomic location. It is possible that when signals are measured with multiple modalities in multiple locations, the resulting multivariate anatomic and temporal patterns of measured signals may provide additional discriminative power over single technology univariate measurements. We evaluated the potential superiority of multivariate methods over univariate methods. Additionally, we utilized machine learning-based models to compare the performance of noninvasive-only to noninvasive-plus-invasive measurements in predicting the onset of OH. We applied machine learning methods to preexisting datasets derived using the lower body negative pressure human model of simulated hemorrhage. Employing multivariate measured physiological signals, we investigated the extent to which machine learning methods can effectively predict the onset of OH. In particular, we applied 2 ensemble learning methods, namely, random forest and gradient boosting. Analysis of precision, recall, and area under the receiver operating characteristic curve showed a superior performance of multivariate approach to that of the univariate ones. In addition, when using both invasive and noninvasive features, random forest classifier had a recall 95% confidence interval (CI) of 0.81 to 0.86 with a precision 95% CI of 0.65 to 0.72. Interestingly, when only noninvasive features were employed, the results worsened only slightly to a recall 95% CI of 0.80 to 0.85 and a precision 95% CI of 0.61 to 0.73. Multivariate ensemble machine learning-based approaches for the prediction of hemodynamic instability appear to hold promise for the development of effective solutions. In the lower body negative pressure multivariate hemorrhage model, predictions based only on noninvasive measurements performed comparably to those using both invasive and noninvasive measurements.

Abstract 788: Leveraging multi omics approach to examine the potential role of causative viruses in glioblastoma

Abstract Glioblastoma (GB), a grade IV brain cancer, has the lowest survival rate. Despite aggressive and targeted therapies, patients remain to have the worst prognosis. More than 16% of cancer incidence worldwide has been attributed to infectious agents, raising uncertainties about the role of infections in the development of brain cancer. While numerous studies have suggested potential viral involvement in GB pathogenesis, a common limitation is the reliance on a singular technology, such as DNA/RNA sequencing or immunohistochemistry, within each study. This approach may restrict the comprehensive exploration of viral contributions, as different technologies offer distinct insights into the complex mechanisms underlying GB development. Utilizing a combination of techniques could provide a more holistic understanding, enhancing the robustness of findings and potentially uncovering nuanced aspects of viral influence that a single technology might overlook. To clarify the role of viruses in GB pathology, our study employs a comprehensive approach integrating three distinct research methods. We screened 178 publicly accessible raw mass spectrometry (MS) data of GB tumors from three independent publications (PMID: 31331834, 31154438, 36720864) by employing our internally developed data identification pipeline. The pipeline transforms raw MS data for downstream analysis, conducts database searches against the latest viral protein databases and undergoes peptide validation for enhanced robustness. Subsequent analysis filters duplicate hits and consolidates nested peptides. The final protein list includes only those identified with two or more peptides of over eight amino acids. The pipeline concludes by inferring and listing the corresponding viruses, ensuring a comprehensive and refined approach to the identification and analysis of viral proteins in the context of MS data. To enhance this dataset, we incorporated whole-genome metagenomics and MS-based proteomics, examining a preliminary cohort of15 GB tumor tissues. This approach explored a wide range of viral encoded proteins. Our comprehensive analysis, integrating bioinformatics, genomics, and proteomics, identified multiple herpesvirus species across our cohorts. This potential identification of viruses within GB has the capacity to redefine the stratification of tumor types in GB patients, signaling a significant development in our understanding of the disease. Citation Format: Bavani Gunasegaran, Aziz Abdullah A Alnakli, Gilles J. Guillemin4, Seong Beom Ahn, Benjamin Heng. Leveraging multi omics approach to examine the potential role of causative viruses in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 788.

Abstract 7504: Longitudinal multi-omics characterization of circulating tumor cells from ALK positive NSCLC patients

Abstract Introduction: Anaplastic lymphoma kinase positive non-small cell lung cancer (ALK+NSCLC) represents a distinct subtype of NSCLC characterized by oncogenic ALK gene mutations leading to ALK overexpression and activation in tumor cells. ALK+ NSCLC will frequently develop mutations during treatment, leading to nonresponse and eventually cancer relapse. Therefore, there is a critical need for sensitive technologies to monitor ALK+ NSCLC disease status in patients over time. To facilitate longitudinal monitoring, there has been a rapid evolution in diagnostic technologies leveraging circulating tumor cells (CTCs) as a liquid biopsy tool. CTCs can be collected non-invasively at various intervals throughout patient treatment. Moreover, they shed from solid tumors and disseminate into the bloodstream, which makes isolating CTCs a valuable source of genomic, transcriptomic, and proteomic insights pertaining to the primary tumor. In this study, we present a comprehensive workflow for conducting multi-omic analysis on CTCs derived from ALK+ NSCLC patients. Methods: Blood samples were collected from a cohort of ALK+ NSCLC patients, and CTCs were isolated using a high throughput, label free microfluidic device, Labyrinth. Enriched CTCs were immunofluorescently stained for cytokeratin, CD45, DAPI, epithelial cell adhesion molecule (EpCAM), and vimentin markers. Heterogeneous CTC populations with hybrid epithelial/mesenchymal (EM) phenotypes are reported. Fluorescence in situ hybridization (FISH) was performed on enriched CTC samples. DNA was extracted and sequenced using a 523 gene targeted sequencing panel. Single cell RNA-seq technology was performed in parallel on CTC samples to investigate the gene expression throughout treatment. Results: The median concentration of CTCs in the ALK+ NSCLC cohort (n=33) is 137 CTCs per ml of blood, and 64% of CTCs are in an EM hybrid state. In ALK+ NSCLC patients (n=3) with an average of 4.6 visits per sample, we observed a trend of decreasing CTC concentration for patients with partial response to the treatment. The presence of ALK fusion in ALK+ NSCLC patient’s CTC is confirmed by FISH. Oncogenic mutations (JAK1, SPEN, ERBB4, NTRK3) are observed in bulk CTC samples from two NSCLC patients. Single cell RNA sequencing was performed on three ALK+ NSCLC patients; 58, 199, and 700 potential CTCs were detected with positive cytokeratin expression and no white blood cell marker expression. Conclusions: This study examined the feasibility of using CTCs for studying and monitoring the clinical status of the ALK+ NSCLC patients as well as the genomic and transcriptomic signatures within their tumors. More patients will need to be processed in order to validate our workflow and reinforce our conclusions. Citation Format: Yuru Chen, Shamileh Fouladdel, Harrison Ball, Zhaoping Qin, Albert Liu, Xu Cheng, Liwei Bao, Habib Serhan, Bryce Vandenburg, Varun Kathawate, Larua Goo, Peter Ulintz, Nathan Merrill, Aaron Udager, Angel Qin, Sofia D. Merajver, Sunitha Nagrath. Longitudinal multi-omics characterization of circulating tumor cells from ALK positive NSCLC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7504.

Abstract 313: Benchmarking immune repertoire sequencing technologies

Abstract In the past decade, single cell gene expression technologies have transformed basic and translational research and are more frequently found in the toolbox of immunologists alongside the standard bulk B-cell receptor (BCR) sequencing and transcriptome profiling assays. While conventional bulk BCR assays capture the frequency of single chains, single-cell immune profiling reveals the frequency of paired heavy and light chains along with the cells transcriptional profile. Here we present the results of a single-blind benchmarking experiment conducted in collaboration with the U.S. Food and Drug Administration (FDA) that compares the performance of standard bulk DNA and RNA BCR repertoire sequencing assays, with the 10x Genomics Single Cell Immune Profiling solution. The FDA selected nine unambiguously monoclonal BCR-expressing cell lines to generate a reference mixture that was shared with each study participant, without revealing the input proportions. This reference cell line mixture was also diluted to 10% and 1% with B-cells sorted from peripheral blood mononuclear cells (PBMC) to further test the limits of clonotype detection. For each experiment, we targeted ~10,000 cells and in aggregate generated a paired gene expression and V(D)J dataset from ~100,000 cells. BCR clonotypes were detected in 78% of the captured cells across all samples profiled. Each of the 9 top unique clonotypes observed in our dataset corresponded to a cell line in the reference mixture, allowing us to decode the mixing percentages of each BCR-expression cell line. In addition, we were able to identify rare cell line clonotypes to as low as 0.01% in the dilution experiments. Furthermore, the multimodal nature of the single cell data also resolved the transcriptional profile of each cell line into its own cluster thus enabling independent verification of clonotype proportions. In summary, we have generated a resource for the immunology community to evaluate and compare data generated with different repertoire sequencing technologies. Citation Format: Shamoni Maheshwari, Carolyn Morrison, Sarah Taylor, BCR-SEQC consortium. Benchmarking immune repertoire sequencing technologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 313.

Abstract 1151: Reconstruction of the spatial ecosystem of glioblastoma reveals relationships between tumor cell states and microenvironment

Abstract Glioblastoma multiforme (GBM) is the most aggressive form of primary brain tumor, with no curative treatment options. Multiple studies have characterized at single cell resolution the GBM as being composed of transcriptional cell states interconnected with components in the tumor immune microenvironment (TME). Our group proposed and validated the first single cell guided functional classification of GBM in four tumor-intrinsic cell states which informed clinical outcome and delivered therapeutic options. However, single cell technologies are unable to unravel the spatial relationships among the cell states of GBM and between GBM cell states and TME. Spatially resolved transcriptomic technologies are emerging as powerful tools to reconstruct the spatial architecture of a tissue. We performed spatial transcriptomics of multicellular regions of interest (ROI) in 6 primary IDH wild-type GBM and 2 recurrent GBM with both CosMx Spatial Molecular Imager, which analyzes 1,000 RNA probes and 64 proteins at single cell resolution, and GeoMx Digital Spatial Profiler which profiles the whole transcriptome (~18,000 genes) at ROI resolution. The development of computational tools aimed to integrate spatial proximity and CosMx derived single-cell transcriptomics revealed spatial segregation of the tumor cell clones and cellular states and highlighted recurrent patterns of cell states, distinct TME cell types associated with coherent histopathological features across multiple samples. The development of a spatial informed intercellular communication algorithm and the reconstruction of ligand-receptor-target networks will allow the discovery of tumor cell states-TME cross-talks and the biological signaling regulated by these interactions that are driving the heterogeneity of GBM and therefore potentially therapeutically targetable. Analysis of matched regions of interest profiled by GeoMx and spatial proteomics with CosMx further cross-validated the spatial ecosystem of glioblastoma as reconstructed at single-cell resolution. Our studies established a scalable approach to resolve the transcriptional heterogeneity of GBM and reconstruct the architecture of GBM cell states and tumor microenvironment. Citation Format: Bruno Adabbo, Simona Migliozzi, Luciano Garofano, Fulvio D'Angelo, Pedro Davila, Sakir H. Gultekin, Daniel Bilbao Cortes, Benjamin Currall, Sion L. Williams, Marc Sanson, Franck Bielle, Anna Luisa Di Stefano, Michele Ceccarelli, Anna Lasorella, Antonio Iavarone. Reconstruction of the spatial ecosystem of glioblastoma reveals relationships between tumor cell states and microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1151.

Abstract 6934: Integrating deep learning morphology profiling, cell sorting, and scRNASeq reveals sample diversity and enriched sub-populations

Abstract Advances in single cell technologies have ushered in a new multi-omics era that has provided more granular information on cell types and functions at unprecedented resolution. Morpholomics (the information encoded by cell morphology) has traditionally been used as a readout of cell identity, state, and function; but scalability, interpretation, and sorting based on morphology has remained challenging. The Deepcell® platform, REM-I, performs high-dimensional morphology analysis of unlabeled, single cells using deep-learning on high-resolution bright-field images captured in microfluidic flow to profile and sort target cells in real-time and at scale. Morphology analysis of single cells is achieved by a self-supervised deep learning foundation model, ‘Human Foundation Model’ (HFM), which combines deep learning features with morphometrics. HFM determines cell identities using morphological features associated with distinct processes characterized by granules, vesicles, cell size, pigmentation. and others. To demonstrate the ability of HFM modeling to distinguish and characterize a diversity of cell types representative of tumor microenvironments, we processed various sample types on the REM-I platform. Human melanoma, immune cells, stromal cells, and dissociated biopsies were combined to recapitulate heterogeneous tumor samples. HFM analysis enabled morphology-based exploration of the resulting bright-field images, revealing the presence of various morphologically distinct populations within each sample. Tumor cells were morphologically distinct and clustered separately from non-tumor cells. Immune cells exhibited subtle but separable morphologies, including T cells of distinct activation states. To demonstrate the morphology-based sorting capabilities of REM-I, we applied it to a ‘reference sample’ consisting of several fixed cell lines, at proportions ranging from 1% to >90%. Using only brightfield images of single cells analyzed through HFM, we used the platform to enrich each cell line from the ‘reference sample’ with high yield and purity, and identified cell types constituting a small percentage (~1%) of the total population. We next showed that unlabeled cells enriched on REM-I that are characterized as unperturbed and viable are amenable to downstream molecular analyses. These cell populations were sorted and the retrieved live cells were analyzed by scRNA-Seq (10x Chromium), demonstrating enrichment of various cell types of the tumor microenvironment in each cell population relative to the pre-sorted sample. These results illustrate: 1) the ability to perform downstream molecular analyses on sorted cells from REM-I, 2) the platform can be used to parse the tumor microenvironment, and 3) the link between morphology, cell identity, and molecular signatures. Citation Format: Andreja Jovic, Christian Corona, Kiran Saini, Tiffine Pham, Ryan Carelli, Vivian Lu, Senzeyu Zhang, Stephane C. Boutet, Maddison Masaeli. Integrating deep learning morphology profiling, cell sorting, and scRNASeq reveals sample diversity and enriched sub-populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6934.

“Two in one”: A novel DNA cascade amplification strategy for trace detection of dual targets

According to the characteristics of DNA programming, the cascaded nucleic acid amplification technology with larger output can overcome the problem of insufficient sensitivity of single nucleic acid amplification technology, and it combines the advantages of two or even multiple nucleic acid amplification technologies at the same time. In this work, a novel cascade signal amplification strategy with strand displacement amplification (SDA) and cascade hybridization chain reaction (HCR) was proposed for trace detection of hAAG and VEGF165. HAAG-induced SDA produced a large amount of S2 to open H2 on Polystyrene (PS) nanospheres, thereby triggering cascade HCR to form DNA dendritic nanostructures with rich fluorescence (FL) signal probes (565 nm). It could realize the amplification of FL signals for the detection of hAAG. Moreover, many doxorubicin (Dox) were loaded into the GC bases of DNA dendritic nanostructures, and its FL signal was effectively shielded. VEGF165 specifically bound to its aptamer to form G-quadruplex structures, which released Dox to produce a high FL signal (590 nm) for detection of VEGF165. This work developed a unique multifunctional DNA dendritic nanostructure fluorescence probe, and cleverly designed a new “On-off” switch strategy for sensitive trace detection of cancer markers.

Evaluation of neurofilament light chain as a biomarker in dogs with structural and idiopathic epilepsy.

Neurofilament light chain (NfL) is a frequently used biomarker in humans for both diagnostic and therapeutic monitoring purposes in various neurologic diseases. It was hypothesized that dogs with diagnosed structural epilepsy (SE) would have a significantly higher serum NfL concentrations compared to dogs with idiopathic epilepsy (IE). The secondary hypothesis was that dogs would have a significantly higher serum NfL concentrations when measured within 7 days after a seizure compared to being seizure-free for at least 30 days. Fifty client-owned dogs presented to the neurology service for evaluation of seizures were enrolled. Fourteen dogs had SE and 36 dogs had IE. Prospective cohort study performed on 52 serum samples obtained for NfL concentration measurement using single molecule array technology. The median serum concentration of NfL in dogs with SE was significantly higher (109 pg/mL; range, 11.4-741.3 pg/mL) than in dogs with IE (17.7 pg/mL; range, 5.8-188 pg/mL; Wilcoxon rank sum test, P = .001). No significant relationship was found between serum NfL concentration and time of sampling in relation to the most recent seizure in dogs with IE. Serum NfL may serve as an adjunctive biomarker for the differentiation of SE and IE.

Penicillium oxalicum SL2-enhanced nanoscale zero-valent iron effectively reduces Cr(VI) and shifts soil microbiota

Most current researches focus solely on reducing soil chromium availability. It is difficult to reduce soil Cr(VI) concentration below 5.0 mg kg-1 using single remediation technology. This study introduced a sustainable soil Cr(VI) reduction and stabilization system, Penicillium oxalicum SL2–nanoscale zero-valent iron (nZVI), and investigated its effect on Cr(VI) reduction efficiency and microbial ecology. Results showed that P. oxalicum SL2–nZVI effectively reduced soil total Cr(VI) concentration from 187.1 to 3.4 mg kg–1 within 180 d, and remained relatively stable at 360 d. The growth curve of P. oxalicum SL2 and microbial community results indicated that γ-ray irradiation shortened the adaptation time of P. oxalicum SL2 and facilitated its colonization in soil. P. oxalicum SL2 colonization activated nZVI and its derivatives, and increased soil iron bioavailability. After restoration, the negative effect of Cr(VI) on soil microorganisms was markedly alleviated. Cr(VI), Fe(II), bioavailable Cr/Fe, Eh, EC and urease (SUE) were the key environmental factors of soil microbiota. Notably, Penicillium significantly stimulated the growth of urease-positive bacteria, Arthrobacter, Pseudarthrobacter, and Microvirga, synergistically reducing soil chromium availability. The combination of P. oxalicum SL2 and nZVI is expected to form a green, economical and long-lasting Cr(VI) reduction stabilization strategy.

Onward to Better Surgery - the Critical Need for Improved Ex Vivo Testing and Training Methods.

Guided surgery has demonstrated significant improvements in patient outcomes in some disease processes. Interest in this field has led to substantial growth in the technologies under investigation. Most likely no single technology will prove to be "best," and combinations of macro- and microscale guidance-using radiological imaging navigation, probes (activatable, perfusion, and molecular-targeted; large- and small-molecule), autofluorescence, tissue intrinsic optical properties, bioimpedance, and other characteristics-will offer patients and surgeons the greatest opportunity for high-success/low-morbidity medical interventions. Problems are arising, however, from the lack of valid testing formats; surgical training simulators suffer the same problems. Small animal models do not accurately recreate human anatomy, especially in terms of tissue volume. Large animal models are expensive and have difficulty replicating many pathological states, particularly when molecular specificity for individual cancers is required. Furthermore, the sheer number of technologies and the potential for synergistic combination leads to exponential growth of testing requirements that is unrealistic for in vivo testing. Therefore, critical need exists to expand the ex vivo/in vitro testing platforms available to investigators and, once validated, a need to increase the acceptance of these methods for funding and regulatory endpoints. Herein is a review of the available ex vivo/in vitro testing formats for guided surgery, a review of their advantages/disadvantages, and consideration for how our field may safely and more swiftly move forward through stronger adoption of these testing and validation methods.

Serum neurofilament light for detecting disease activity in individual patients in multiple sclerosis: A 48-week prospective single-center study

Background: Serum neurofilament light (sNfL) reflects neuroaxonal damage and is now used as an outcome in treatment trials of relapsing-remitting multiple sclerosis (RRMS). However, the diagnostic properties of sNfL for monitoring disease activity in individual patients warrant further investigations. Method: Patients with suspected relapse and/or contrast-enhancing lesions (CELs) were consecutively included and performed magnetic resonance imaging (MRI) of the brain at baseline and weeks 28 and 48. Serum was obtained at baseline and 2, 4, 8, 16, 24, and 48 weeks. Neurofilament light concentration was measured using Single molecule array technology. Results: We included 44 patients, 40 with RRMS and 4 with clinically isolated syndrome. The median sNfL level peaked at 2 weeks post-baseline (14.6 ng/L, interquartile range (IQR); 9.3–31.6) and reached nadir at 48 weeks (9.1 ng/L, IQR; 5.5–15.0), equivalent to the median sNfL of controls (9.1 ng/L, IQR; 7.4–12). A baseline Z-score of more than 1.1 (area under the curve; 0.78, p < 0.0001) had a sensitivity of 81% and specificity of 70% to detect disease activity. Conclusion: One out of five patients with relapse and/or CELs did not change significantly in post-baseline sNfL levels. The utility of repeated sNfL measurements to monitor disease activity is complementary rather than a substitute for clinical and MRI measures.

Simplifying stable CHO cell line generation with high probability of monoclonality by using microfluidic dispensing as an alternative to fluorescence activated cell sorting.

Single cell cloning is a critical step for cell line development (CLD) for therapeutic protein production, with proof of monoclonality being compulsorily sought in regulatory filings. Among the different single cell deposition technologies, we found that fluorescence activated cell sorting (FACS) offers high probability of monoclonality and can allow selective enrichment of the producer cells. However, FACS instruments are expensive and resource-intensive, have a large footprint, require highly skilled operators and take hours for setup, thereby complicating the cell line generation process. With the aim of finding an easy-to-use alternative to FACS, we identified a flow cytometry-based microfluidic cell dispenser, which presents a single cell sorting solution for biopharmaceutical CLD. The microfluidic cell dispenser is small, budget-friendly, easy-to-use, requires lower-cost consumables, permits flow cytometry-enabled multiparametric target cell enrichment and offers fast and gentle single cell dispensing into multiwell plates. Following comprehensive evaluation, we found that single cell deposition by the microfluidic cell dispenser resulted in >99% probability of monoclonality for production cell lines. Moreover, the clonally derived producer cell lines generated from the microfluidic cell dispenser demonstrated comparable or improved growth profiles and production capability compared to the FACS derived cell lines. Taken together, microfluidic cell dispensing can serve as a cost-effective, efficient and convenient alternative to FACS, simplifying the biopharmaceutical CLD platform with significant reductions in both scientist time and running costs.

The landscape of immune dysregulation in pediatric sepsis at a single-cell resolution

Recognizing immune dysregulation as a hallmark of sepsis pathophysiology, leukocytes have attracted major attention of investigation. While adult and pediatric sepsis are clinically distinct, their immunological delineation remains limited. Single cell technologies facilitated the characterization of immune signatures. We tackled to delineate immunological profiles of pediatric sepsis at a single-cell level by analyzing blood samples from six septic children, at both acute and recovery phases, and four healthy children. 16 single-cell transcriptomic datasets were analyzed and compared to adult sepsis dataset. We showed a unique shift in neutrophil subpopulations and functions between acute and recovery phases, along with the regulatory role of resistin. Neutrophil signatures were comparable between adult and pediatric sepsis. Innate-like CD4 T cells were predominantly and uniquely observed in acute phase of pediatric sepsis. Our study serves as a rich source of information about the phenotypic diversity and trajectory of circulating immune cells during pediatric sepsis.

Pi-seq—A customizable multichannel syringe pump for microfluidics

The advent of single cell technologies resulted in growing demand for microfluidics in the biological sciences. Commercial platforms have remained expensive, inflexible, and non-customizable black boxes. We developed an open source, multichannel, zero-backflow microfluidics device based on syringe pumps controlled by a Raspberry Pi computer. It uses both readily available and 3D-printed parts as well as a custom PCB and is easily serviceable. Moreover, it is fully customizable for various applications. Total cost is under €600. We equipped one channel with a custom Peltier-based temperature controller for precise heating or cooling and a mixer mechanism to prevent sedimentation of the cells within the syringe. Depending on the cells in the sample, heating and cooling can be useful to maintain a beneficial environment or to slow down cellular processes and cell death, respectively. Combined with microfluidics consumables and a microscope, the device is capable of integration into a high quality droplet-based single cell RNA sequencing workflow as shown here. Analysis of a mixture of human and insect cells resulted in a dataset of 17,769 single cells and demonstrates reliable operation and separation.