Academic Laboratories Research Articles

Experiments in nuclear physics using inexpensive instruments

<span lang="EN-US">The scarcity of experimental activities is one of the challenges of teaching current physics. This study resolves these issues and suggests three nuclear physics experiments using a <a name="_Hlk144293970"></a>low-cost ion chamber, whose construction is explained: the measurement of <sup>222</sup>Rn progeny collected from the indoor air; the measurement of the range of alpha particles emitted by the <sup>232</sup>Th progeny, present in lantern mantles and in thoriated welding rods, as well as by the air filter containing <sup>222</sup>Rn progeny; and the measurement of 220Rn half-life collected from In this study, the experimental methods and anticipated findings are presented, showing that the experiments could help nuclear physics curricula. These procedures may provide broad access to either academic laboratories in high schools or colleges and the equipment may be used to create novel nuclear physics teaching strategies</span>

A-002 The Prevalence of the High Sensitivity Cardiac Troponin I Outlier and False Positivity Rates on Beckman Coulter Access DxI

Abstract Background The false positive elevation in high sensitivity cardiac troponin I (hsTnI) can be triggered by many factors, for example, fibrin clots, heterophile antibodies, or other sources of troponin interferences. These interferences lead to inaccurate hsTnI results. These inaccurate results described in the literature as the “outliers”. Published studies use statistical tools to identify the outliers based on the discrepancies between the two repeat values. Depending on the instrument platform and the study design, the outlier rate for the conventional troponin I assay was reported from 0.44% to 1.01% (1, 2). In our laboratory, the false positivity rate for the conventional troponin assay on Beckman Coulter DxI platform was determined as 1% (unpublished data). This study aim was to determine both the statistically and clinically significant outliers for hsTnI assay on the Beckman Coulter Access DxI instrument in the academic medical center clinical laboratory setting. Methods A unique test repeat protocol was created. Two parallel hsTnI measurements are conducted in lithium heparin tubes (BD Vacutainer) on Beckman Coulter DXI 800 systems. When the difference between the two results is greater than 30%, a third repeat is automatically ordered and run after additional centrifugation at a higher relative centrifugal force. The outlier determination is based on assessing the difference between the first two values using previously described statistical analysis tools (1). The clinically significant outlier was determined by counting positive results in the first two runs which are not unconfirmed by the third run, i.e., false positive results. Gender specific cutoffs, 14 ng/L for female and 19 ng/L for male, were applied to identify the positive results. Overall, 2935 patients’ results were evaluated during the study. Results Based on the analysis of the first two repeat runs, out of 2935 samples 16 samples, or 0.54%, were identified as the statistical outliers. 2 out of these 16 outliers, or 12.5%, were negative results. Taking into consideration the third repeat data, 13 out of 2935 samples, or 0.44%, were identified as false positive results. Only 9 out of 13 false positive results, or 69.2%, were identified using the statistical approach above. Conclusion The false positivity rate of hsTnI testing has dropped significantly from 1% to 0.44% in a setting of our laboratory. Our refined repeat protocol approach significantly increases the clinician’s confidences in the hsTnI results by capturing potential false positive results. This approach addresses the outliers at an additional expense like reagents, instrument wear and tear, and labor. Therefore, a more robust methodology is still desired by the industry.

Simplicity Hits the Gas: A Robust, DIY Biogas Reactor Holds Potential in Research and Education in Bioeconomy

Biogas is a promising and robust renewable energy that holds potential as clean energy in the context of the current climatic emergency. Biogas has the immense advantage of coupling waste management and clean energy production. In other words, it is not only a renewable energy source, but also a central tool in recycling a vast range of waste products from the agroindustry. Despite its potential, the process is microbiologically complex and is usually carried out in both industrial and pilot laboratories, utilizing a variety of reactors and systems. In this work, we present a very simple, Do It Yourself (DIY) biogas fermenter that we have designed, operated, and characterized. We propose this technology as both an inexpensive proxy for biogas reactors in academic and private laboratories and as an effective dissemination tool to foster the knowledge and potential of biogas as a key technology to contribute to the development of a global bioeconomy.

AI & experimental-based discovery and preclinical IND-enabling studies of selective BMX inhibitors for development of cancer therapeutics

The current work aims to design and provide a preliminary IND-enabling study of selective BMX inhibitors for cancer therapeutics development. BMX is an emerging target, more notably in oncological and immunological diseases. In this work, we have employed a predictive AI-based platform to design the selective inhibitors considering the novelty, IP prior protection, and drug-likeness properties. Furthermore, selected top candidates from the initial iteration of the design were synthesized and chemically characterized utilizing 1H NMR and LC-MS. Employing a panel of biochemical (enzymatic) and cancer cell lines, the selected molecules were tested against these assays. In addition, we used artificial intelligence to predict and evaluate several critical IND-focused physicochemical and pharmacokinetics values of the selected molecules. A secondary objective of the current work was also to validate the sole role of BMX in animal models known to be mediated by BMX. More than 50 molecules were designed in the present study employing five novel discovered scaffolds. Two molecules were nominated for further IND-focused studies. Compound II showed promising in-vitro activity against BMX in both enzymatic assays compared to other kinases and in cancer cell lines with known BMX overexpression. Interestingly, compound II showed very favorable physicochemical and pharmacokinetics properties as predicted by the used platforms. The animal study further confirmed the sole role of BMX in the disease model. The current work provides promising data on a selective BMX inhibitor as a potential lead for therapeutics development, and the asset is currently in the optimization stage. Notably, the current study shows a framework for a combined approach employing both AI and experimentation that can be used by academic labs in their research programs to more streamline programs into IND-focused to be bridged easily for further clinical development with industrial partners.

An experimental approach to determine the gamma radiation interaction mean free path and exposure buildup factor for biomolecules

This experimental approach was designed to understand the gamma interaction parameters for the essential biomolecules, including starch soluble, cholesterol, myristic acid, glucose, oxalic acid, dextrose, salicylic acid, ethyl cellulose and sucrose. The empirical determination of gamma interaction parameters, such as interaction mean-free-path (MFP), buildup factor, and effective atomic number (Zeff) was performed by measuring mass attenuation coefficient (μ/ρ) at energies of 356 keV, 511 keV, 662 keV, 1173 keV, 1275 keV and 1332 keV. This was achieved using weak radioactive sources and a NaI(Tl) scintillation spectrometer with collimated and non-collimated transmission geometry. The experimentally determined values of gamma-ray interaction parameters were obtained non-destructively and precisely agreeing with the expected values from simulations and codes. In addition, the research findings also revealed a novel trend in gamma interaction mean free path as a function of energy and variable buildup factors for the selected biomolecules. These research findings provide valuable insight into the process of gamma radiation interaction. This approach may fulfil the increasing demand of medical, technical and academic research laboratories for a cost-effective and reliable empirical methodology to understand gamma radiation interaction with matter.

Expanding the Clinical Utility of Targeted RNA Sequencing Panels beyond Gene Fusions to Complex, Intragenic Structural Rearrangements.

Gene fusions are a form of structural rearrangement well established as driver events in pediatric and adult cancers. The identification of such events holds clinical significance in the refinement, prognostication, and provision of treatment in cancer. Structural rearrangements also extend beyond fusions to include intragenic rearrangements, such as internal tandem duplications (ITDs) or exon-level deletions. These intragenic events have been increasingly implicated as cancer-promoting events. However, the detection of intragenic rearrangements may be challenging to resolve bioinformatically with short-read sequencing technologies and therefore may not be routinely assessed in panel-based testing. Within an academic clinical laboratory, over three years, a total of 608 disease-involved samples (522 hematologic malignancy, 86 solid tumors) underwent clinical testing using Anchored Multiplex PCR (AMP)-based RNA sequencing. Hematologic malignancies were evaluated using a custom Pan-Heme 154 gene panel, while solid tumors were assessed using a custom Pan-Solid 115 gene panel. Gene fusions, ITDs, and intragenic deletions were assessed for diagnostic, prognostic, or therapeutic significance. When considering gene fusions alone, we report an overall diagnostic yield of 36% (37% hematologic malignancy, 41% solid tumors). When including intragenic structural rearrangements, the overall diagnostic yield increased to 48% (48% hematologic malignancy, 45% solid tumor). We demonstrate the clinical utility of reporting structural rearrangements, including gene fusions and intragenic structural rearrangements, using an AMP-based RNA sequencing panel.

Is Commercialization of Intellectual Property in an Academic Environment Possible?

The question: is Commercialization of Intellectual Property Feasible in an Academic Environment. There are many factors, unique and disparate between Academia and Commercialization and Licensing. There are substantial misalignments of the objectives. A fundamental idea inaugurated in an academic lab follows a complex path to commercialization. Along the way, the PI wears many hats. Here, some of the challenges for an academic PI navigating the path are counterbalanced with investors’ perspectives on commercialization.

(Invited) Commercializing Single Walled Carbon Nanotube-Based Sensors - Enzyme Activity and Beyond

The ECS carbon nanostructures community is well informed on the potential of single walled carbon nanotube (SWCNT)-based sensors and likewise the challenges associated with realizing practical applications outside of an academic laboratory. This talk will discuss our latest efforts in facile separation and sensor preparation methods. It will discuss potential use cases in improving high throughput screening of custom enzymes, with a current focus on recalcitrant substrates such as conventional polymers. This talk will also focus on latest efforts of reducing to practice optical fluorimeters (single, multi-channel, spatial, and temperature controlled) for field use applications. Finally, this talk will detail the on-going adventure of commercialization at Zymosense Inc. which we hope will serve as a practical guide to other groups considering transferring their technology from the lab.

Ammonia Synthesis by Mechanochemistry

AbstractThe design and use of organic, inorganic, and metal‐based catalysts is critical to academic and industrial laboratories all around the world. In this framework, ammonia production embodies the most iconic use of catalysis. This review aims to describe the most recent and exciting developments in the mechanocatalytic preparation of ammonia.

Practices and Challenges of Teachers in Teaching Science Online

Educational disruption brought by this pandemic changed the practices and challenged teachers and students to navigate the new learning landscape. This descriptive research study determined the practices and challenges of science teachers in teaching amidst the COVID-19 pandemic. A total of 54 science teachers in Zambales, Philippines responded to the researcher-made Practices and Challenges of Science Teachers Questionnaire (PCSTQ). Results revealed that science teachers use printed module as a learning delivery modality in their classes. They often employ varied science teaching strategies, utilize assessment strategies and incorporate technology integration in teaching during educational disruption. They often encounter challenges in academic workload, laboratory experimentation, and physical infrastructures, while they sometimes face challenges in terms of digital infrastructure, instructional resources, digital competence, and assessment and supervision. There are significant differences in the teachers’ teaching strategies by trainings, and technology integration practices by trainings and modality used. Furthermore, there are significant differences in the challenges in instructional resources, physical infrastructure, digital competence, and academic workload by years in service; challenges in digital competence by zone; and challenges in academic workload by age. Implications of the study to pedagogy, policy, and practice are discussed in the paper. The study also contributes to the dearth of literature in describing the teachers’ practices and challenges in science teaching in the context of the COVID-19 pandemic.

“I Feel Like I’m in a Box”: Contrasting Virtual Reality “Imaginaries” in the Context of Academic Innovation Labs

ABSTRACT As immersive technology grows in popularity, universities are developing academic innovation labs (AIL) that often introduce students to virtual reality (VR) and other emerging cross reality applications. Although these labs help educate students on emerging technology, a more critical eye is needed to examine user experience (UX). This article reports on a qualitative, multimethod study that employed a talk-aloud UX protocol to gather data on VR users’ experience at the University of Connecticut’s OPIM Research Lab. To fully define and contrast this data, we juxtapose these individual narratives with rhetorical analysis of marketing discourse, as presented by VR platform HTC Vive, Google’s VR application Tilt Brush, and the Research Lab’s promotional material. Based on our findings, we assert that sociotechnical imaginaries as constructed by promotional material often reduce the complexities of immersion in user experience. Such marketing rhetoric creates “top-down” imaginaries that contrast with “bottom-up” imaginaries generated in user experience, reinforcing the complex and fluid definitions of immersion. The resulting study has practical implications for stakeholders across higher education, especially in the context of innovation labs, as well as for technical and professional communication educators and practitioners.

An inexpensive semi-automated sample processing pipeline for cell-free RNA extraction.

Despite advances in automated liquid handling and microfluidics, preparing samples for RNA sequencing at scale generally requires expensive equipment, which is beyond the reach of many academic laboratories. Manual sample preparation remains a slow, expensive and error-prone process. Here, we describe a low-cost, semi-automated pipeline to extract cell-free RNA using one of two commercially available, inexpensive and open-source robotic systems: the Opentrons OT1.0 or OT2.0. Like many RNA isolation protocols, ours can be decomposed into three subparts: RNA extraction, DNA digestion and RNA cleaning and concentration. RT-qPCR data using a synthetic spike-in confirms comparable RNA quality to the gold standard, manual sample processing. The semi-automated pipeline also shows improvement in sample throughput (+12×), time spent (-11×), cost (-3×) and biohazardous waste produced (-4×) compared with its manual counterpart. This protocol enables cell-free RNA extraction from 96 samples simultaneously in 4.5 h; in practice, this dramatically improves the time to results, as we recently demonstrated. Importantly, any laboratory already has most of the parts required (manual pipette and corresponding tips and kits for RNA isolation, cleaning and concentration) to build a semi-automated sample processing pipeline of their own and would only need to purchase or three-dimensionally print a few extra parts (US$5.5 K-12 K in total). This pipeline is also generalizable for many nucleic acid extraction applications, thereby increasing the scale of studies, which can be performed in small research laboratories.

Risk prioritization in a core preparation experiment using fuzzy VIKOR integrated with Shannon entropy method

Accident rates in academic laboratories are increasing rapidly day to day. The incorporation of complex activities with the inclusion of modern technologies and human behavior during experiments often makes it difficult to manage health and safety risks. Failure modes and effect analysis (FMEA) is widely used risk assessment technique that consider (03) risk parameters which include severity (S), occurrence (O), and detection (D), and calculate a risk priority number (R.P.N), which facilitates in failure modes ranking. However, there are some shortcomings associated with this method. This study aims to propose a framework for prioritizing the health and safety risks (failure modes) in an experiment using a widely used Multi-criteria decision-making method, i.e., Fuzzy VIKOR supported by criteria objective weights determined using the Shannon entropy concept. The fuzzy VIKOR method is employed to rank the failure modes based on the maxi group utility and the minimum individual regret. In this study, an experiment related to preparing rock core samples is taken as an example for implementing the proposed technique. Core sample preparation is one of the most common and dangerous experiments in the petroleum industry. The performance of the experiment allows rock sample preparation of desired shape and size to be tested for its hydrocarbon producing potential. The final results indicate that applying the proposed method in a fuzzy environment can efficiently prioritize the experiment’s health and safety risks, which is further considered for the implementation of control measure prioritization. The proposed approach can be applied to other experiments with the same or different domains.

Report on the Workshop on Factorized Databases

The workshop took place in Zurich and online from August 2 to 4, 2022. It was attended by researchers from 17 academic institutions and industry labs, including Microsoft Gray Systems Lab, Omics Data Automation, Oracle Labs Zurich, RelationalAI, and TigerGraph. It featured 18 talks and plenty of opportunities for discussions. The vast majority of participants attended in person.

The success rates of clinical cancer next-generation sequencing based on pathologic diagnosis: Experience from a single academic laboratory.

This article aims to establish the relationship between pathologic diagnosis and the rate of success in cancer next-generation sequencing testing. Clinical next-generation sequencing results performed for solid tumors were reviewed. The rate of success was analyzed in the context of tumor type and accompanying variables. Out of 683 total specimens, 533 (78.0%) underwent successful sequencing. The rate of success was 91.8% for ovarian carcinomas, 87.5% for lung non-small cell carcinomas, 82.0% for colorectal adenocarcinomas, 78.3% for melanomas, 75.9% for breast carcinomas, and 64.7% for pancreatic adenocarcinomas. For specimens that successfully underwent sequencing, pancreatic adenocarcinomas had the lowest median tumor proportion and somatic RAS and TP53 mutation allele fractions compared with other tumor types. Cytology specimens had a 33.3% success rate for pancreatic adenocarcinomas (5 of 15) and a 93.3% success rate for lung carcinomas (14 of 15). Compared with tissue from primary sites, tissue from metastatic sites showed a higher success rate for pancreatic adenocarcinomas and lower success rates for colorectal adenocarcinomas and melanomas. The success rate of cancer next-generation sequencing testing is dependent on pathologic diagnosis, tissue site, and diagnostic procedure. Understanding which specimens are at higher risk for failing molecular testing may help pathologists and clinical care teams optimize tissue acquisition and usage for patient care.

Performance of Indoor 5G 3GPP Systems

Background: The 5G cellular networks are expected to provide high data rates for indoor environments by utilizing the mmWave bands. Due to a lack of general path loss models of these bands, various works have been carried out to find the most appropriate model that can provide accurate values of path loss over distance for different indoor scenarios. This paper focuses on some well-known path loss models, e.g., mixed and OpenOffice models introduced by 3GPP; the dualstripe model was presented by Alcatel-Lucent, picoChip Designs, and Vodafone at the 3GPP meeting; single and dual ABG models were designed by leading academic and industrial labs. Methods: Two network scenarios, e.g., single-cell and 3-cell networks, are utilized in simulation to analyze the effects of path loss models on network performance. Results: The simulation results indicate that the single-slop and dual-slop models can derive a similar performance when only a cell is deployed. However, in a 3-cell network system with intercell interference, the achieved performance in these systems is significantly different. Conclusion: The dual-slop model is better than the single–slope model in terms of path loss modeling since it can capture more characteristics of wireless transmission links, particularly the Light-of- Sight (LoS) and Non-LoS (NLoS) effects.

Anonymous Comparative Assessment by an Academic Core Laboratory of Four Angiography-Derived Fractional Flow Ratio Software in Patients With Pressure Derived iFR and FFR

Anonymous Comparative Assessment by an Academic Core Laboratory of Four Angiography-Derived Fractional Flow Ratio Software in Patients With Pressure Derived iFR and FFR

RAD51 as a biomarker for homologous recombination deficiency in high-grade serous ovarian carcinoma: robustness and interobserver variability of the RAD51 test.

The RAD51 test is emerging as a promising biomarker for the assessment of functional homologous recombination deficiency (HRD). Yet, the robustness and reproducibility of the immunofluorescence-based RAD51 test, in different academic laboratories, have not been systematically investigated. Therefore, we tested the performance of the RAD51 assay in formalin-fixed paraffin-embedded (FFPE) high-grade serous ovarian carcinoma (HGSOC) samples in four European laboratories. Here, we confirm that subtle differences in staining procedures result in low variability of RAD51 and γH2AX scores. However, substantial variability in RAD51 scoring was observed in some samples, likely due to complicating technical and biological features, such as high RAD51 signal-to-noise ratio and RAD51 heterogeneity. These results support the need to identify and perform additional quality control steps and/or automating image analysis. Altogether, resolving technical issues should be a priority, as identifying tumours with functional HRD is urgently needed to guide the individual treatment of HGSOC patients. Follow-up studies are needed to define the key tissue quality requirements to assess HRD by RAD51 in FFPE tumour samples, as this test could help in guiding the individual treatment of HGSOC patients.

Population screening shows risk of inherited cancer and familial hypercholesterolemia in Oregon

The Healthy Oregon Project (HOP) is a statewide effort that aims to build a large research repository and influence the health of Oregonians through providing no-cost genetic screening to participants for a next-generation sequencing 32-gene panel comprising genes related to inherited cancers and familial hypercholesterolemia. This type of unbiased population screening can detect at-risk individuals who may otherwise be missed by conventional medical approaches. However, challenges exist for this type of high-throughput testing in an academic setting, including developing a low-cost high-efficiency test and scaling up the clinical laboratory for processing large numbers of samples. Modifications to our academic clinical laboratory including efficient test design, robotics, and a streamlined analysis approach increased our ability to test more than 1,000 samples per month for HOP using only one dedicated HOP laboratory technologist. Additionally, enrollment using a HIPAA-compliant smartphone app and sample collection using mouthwash increased efficiency and reduced cost. Here, we present our experience three years into HOP and discuss the lessons learned, including our successes, challenges, opportunities, and future directions, as well as the genetic screening results for the first 13,670 participants tested. Overall, we have identified 730 pathogenic/likely pathogenic variants in 710 participants in 24 of the 32 genes on the panel. The carrier rate for pathogenic/likely pathogenic variants in the inherited cancer genes on the panel for an unselected population was 5.0% and for familial hypercholesterolemia was 0.3%. Our laboratory experience described here may provide a useful model for population screening projects in other states.

Pair-Variational Autoencoders for Linking and Cross-Reconstruction of Characterization Data from Complementary Structural Characterization Techniques.

In materials research, structural characterization often requires multiple complementary techniques to obtain a holistic morphological view of a synthesized material. Depending on the availability and accessibility of the different characterization techniques (e.g., scattering, microscopy, spectroscopy), each research facility or academic research lab may have access to high-throughput capability in one technique but face limitations (sample preparation, resolution, access time) with other technique(s). Furthermore, one type of structural characterization data may be easier to interpret than another (e.g., microscopy images are easier to interpret than small-angle scattering profiles). Thus, it is useful to have machine learning models that can be trained on paired structural characterization data from multiple techniques (easy and difficult to interpret, fast and slow in data collection or sample preparation) so that the model can generate one set of characterization data from the other. In this paper we demonstrate one such machine learning workflow, Pair-Variational Autoencoders (PairVAE), that works with data from small-angle X-ray scattering (SAXS) that present information about bulk morphology and images from scanning electron microscopy (SEM) that present two-dimensional local structural information on the sample. Using paired SAXS and SEM data of newly observed block copolymer assembled morphologies [open access data from Doerk G. S.; et al. Sci. Adv.2023, 9 ( (2), ), eadd3687], we train our PairVAE. After successful training, we demonstrate that the PairVAE can generate SEM images of the block copolymer morphology when it takes as input that sample's corresponding SAXS 2D pattern and vice versa. This method can be extended to other soft material morphologies as well and serves as a valuable tool for easy interpretation of 2D SAXS patterns as well as an engine for generating ensembles of similar microscopy images to create a database for other downstream calculations of structure-property relationships.