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Single-molecule imaging provides a powerful way to study biochemical processes in live cells, yet it remains challenging to track single molecules while simultaneously detecting their interactions. Here, we describe a novel property of rhodamine dyes, proximity-assisted photoactivation (PAPA), in which one fluorophore (the ‘sender’) can reactivate a second fluorophore (the ‘receiver’) from a dark state. PAPA requires proximity between the two fluorophores, yet it operates at a longer average intermolecular distance than Förster resonance energy transfer (FRET). We show that PAPA can be used in live cells both to detect protein–protein interactions and to highlight a subpopulation of labeled protein complexes in which two different labels are in proximity. In proof-of-concept experiments, PAPA detected the expected correlation between androgen receptor self-association and chromatin binding at the single-cell level. These results establish a new way in which a photophysical property of fluorophores can be harnessed to study molecular interactions in single-molecule imaging of live cells.

How molecules interact governs how they move. Single-molecule tracking (SMT) thus provides a unique window into the dynamic interactions of biomolecules within live cells. Using transcription regulation as a case study, we describe how SMT works, what it can tell us about molecular biology, and how it has changed our perspective on the inner workings of the nucleus. We also describe what SMT cannot yet tell us and how new technical advances seek to overcome its limitations. This ongoing progress will be imperative to address outstanding questions about how dynamic molecular machines function in live cells.

ObjectivesTo identify incident SARS-CoV-2 infections and inform effective mitigation strategies in university settings, we piloted an integrated symptom and exposure monitoring and testing system among a cohort of university students and employees.DesignProspective cohort study.SettingA public university in California from June to August 2020.Participants2180 university students and 738 university employees.Primary outcome measuresAt baseline and endline, we tested participants for active SARS-CoV-2 infection via quantitative PCR (qPCR) test and collected blood samples for antibody testing. Participants received notifications to complete additional qPCR tests throughout the study if they reported symptoms or exposures in daily surveys or were selected for surveillance testing. Viral whole genome sequencing was performed on positive qPCR samples, and phylogenetic trees were constructed with these genomes and external genomes.ResultsOver the study period, 57 students (2.6%) and 3 employees (0.4%) were diagnosed with SARS-CoV-2 infection via qPCR test. Phylogenetic analyses revealed that a super-spreader event among undergraduates in congregate housing accounted for at least 48% of cases among study participants but did not spread beyond campus. Test positivity was higher among participants who self-reported symptoms (incidence rate ratio (IRR) 12.7; 95% CI 7.4 to 21.8) or had household exposures (IRR 10.3; 95% CI 4.8 to 22.0) that triggered notifications to test. Most (91%) participants with newly identified antibodies at endline had been diagnosed with incident infection via qPCR test during the study.ConclusionsOur findings suggest that integrated monitoring systems can successfully identify and link at-risk students to SARS-CoV-2 testing. As the study took place before the evolution of highly transmissible variants and widespread availability of vaccines and rapid antigen tests, further research is necessary to adapt and evaluate similar systems in the present context.

SARS coronavirus 2 (SARS-CoV-2) has caused an ongoing global pandemic with significant mortality and morbidity. At this time, the only FDA-approved therapeutic for COVID-19 is remdesivir, a broad-spectrum antiviral nucleoside analog. Efficacy is only moderate, and improved treatment strategies are urgently needed. To accomplish this goal, we devised a strategy to identify compounds that act synergistically with remdesivir in preventing SARS-CoV-2 replication. We conducted combinatorial high-throughput screening in the presence of submaximal remdesivir concentrations, using a human lung epithelial cell line infected with a clinical isolate of SARS-CoV-2. This identified 20 approved drugs that act synergistically with remdesivir, many with favorable pharmacokinetic and safety profiles. Strongest effects were observed with established antivirals, Hepatitis C virus nonstructural protein 5A (HCV NS5A) inhibitors velpatasvir and elbasvir. Combination with their partner drugs sofosbuvir and grazoprevir further increased efficacy, increasing remdesivir's apparent potency > 25-fold. We report that HCV NS5A inhibitors act on the SARS-CoV-2 exonuclease proofreader, providing a possible explanation for the synergy observed with nucleoside analog remdesivir. FDA-approved Hepatitis C therapeutics Epclusa® (velpatasvir/sofosbuvir) and Zepatier® (elbasvir/grazoprevir) could be further optimized to achieve potency and pharmacokinetic properties that support clinical evaluation in combination with remdesivir.

Single-molecule imaging provides a powerful way to study biochemical processes in live cells, yet it remains challenging to track single molecules while simultaneously detecting their interactions. Here, we describe a novel property of rhodamine dyes, proximity-assisted photoactivation (PAPA), in which one fluorophore (the 'sender') can reactivate a second fluorophore (the 'receiver') from a dark state. PAPA requires proximity between the two fluorophores, yet it operates at a longer average intermolecular distance than Förster resonance energy transfer (FRET). We show that PAPA can be used in live cells both to detect protein-protein interactions and to highlight a subpopulation of labeled protein complexes in which two different labels are in proximity. In proof-of-concept experiments, PAPA detected the expected correlation between androgen receptor self-association and chromatin binding at the single-cell level. These results establish a new way in which a photophysical property of fluorophores can be harnessed to study molecular interactions in single-molecule imaging of live cells.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has emerged as a major global health threat. The COVID-19 pandemic has resulted in over 168 million cases and 3.4 million deaths to date, while the number of cases continues to rise. With limited therapeutic options, the identification of safe and effective therapeutics is urgently needed. The repurposing of known clinical compounds holds the potential for rapid identification of drugs effective against SARS-CoV-2. Here, we utilized a library of FDA-approved and well-studied preclinical and clinical compounds to screen for antivirals against SARS-CoV-2 in human pulmonary epithelial cells. We identified 13 compounds that exhibit potent antiviral activity across multiple orthogonal assays. Hits include known antivirals, compounds with anti-inflammatory activity, and compounds targeting host pathways such as kinases and proteases critical for SARS-CoV-2 replication. We identified seven compounds not previously reported to have activity against SARS-CoV-2, including B02, a human RAD51 inhibitor. We further demonstrated that B02 exhibits synergy with remdesivir, the only antiviral approved by the FDA to treat COVID-19, highlighting the potential for combination therapy. Taken together, our comparative compound screening strategy highlights the potential of drug repurposing screens to identify novel starting points for development of effective antiviral mono- or combination therapies to treat COVID-19.

The most common method for RNA detection involves reverse transcription followed by quantitative polymerase chain reaction (RT-qPCR) analysis. Commercial one-step master mixes-which include both a reverse transcriptase and a thermostable polymerase and thus allow performing both the RT and qPCR steps consecutively in a sealed well-are key reagents for SARS-CoV-2 diagnostic testing; yet, these are typically expensive and have been affected by supply shortages in periods of high demand. As an alternative, we describe here how to express and purify Taq polymerase and M-MLV reverse transcriptase and assemble a homemade one-step RT-qPCR master mix. This mix can be easily assembled from scratch in any laboratory equipped for protein purification. We also describe two simple alternative methods to prepare clinical swab samples for SARS-CoV-2 RNA detection by RT-qPCR: heat-inactivation for direct addition, and concentration of RNA by isopropanol precipitation. Finally, we describe how to perform RT-qPCR using the homemade master mix, how to prepare in vitro-transcribed RNA standards, and how to use a fluorescence imager for endpoint detection of RT-PCR amplification in the absence of a qPCR machine In addition to being useful for diagnostics, these versatile protocols may be adapted for nucleic acid quantification in basic research. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of a one-step RT-qPCR master mix using homemade enzymes Basic Protocol 2: Preparation of swab samples for direct RT-PCR Alternate Protocol 1: Concentration of RNA from swab samples by isopropanol precipitation Basic Protocol 3: One-step RT-qPCR of RNA samples using a real-time thermocycler Support Protocol: Preparation of RNA concentration standards by in vitro transcription Alternate Protocol 2: One-step RT-PCR using endpoint fluorescence detection.

Re-opening of communities in the midst of the ongoing COVID-19 pandemic has ignited new waves of infections in many places around the world. Mitigating the risk of reopening will require widespread SARS-CoV-2 testing, which would be greatly facilitated by simple, rapid, and inexpensive testing methods. This study evaluates several protocols for RNA extraction and RT-qPCR that are simpler and less expensive than prevailing methods. First, isopropanol precipitation is shown to provide an effective means of RNA extraction from nasopharyngeal (NP) swab samples. Second, direct addition of NP swab samples to RT-qPCRs is evaluated without an RNA extraction step. A simple, inexpensive swab collection solution suitable for direct addition is validated using contrived swab samples. Third, an open-source master mix for RT-qPCR is described that permits detection of viral RNA in NP swab samples with a limit of detection of approximately 50 RNA copies per reaction. Quantification cycle (Cq) values for purified RNA from 30 known positive clinical samples showed a strong correlation (r2 = 0.98) between this homemade master mix and commercial TaqPath master mix. Lastly, end-point fluorescence imaging is found to provide an accurate diagnostic readout without requiring a qPCR thermocycler. Adoption of these simple, open-source methods has the potential to reduce the time and expense of COVID-19 testing.

Re-opening of communities in the midst of the ongoing COVID-19 pandemic has ignited a second wave of infections in many places around the world. Mitigating the risk of reopening will require widespread SARS-CoV-2 testing, which would be greatly facilitated by simple, rapid, and inexpensive testing methods. To this end, we evaluated several protocols for RNA extraction and RT-qPCR that are simpler and less expensive than prevailing methods. First, we show that isopropanol precipitation provides an effective means of RNA extraction from nasopharyngeal (NP) swab samples. Second, we evaluate direct addition of NP swab samples to RT-qPCR reactions without an RNA extraction step. We describe a simple, inexpensive swab collection solution suitable for direct addition, which we validate using contrived swab samples. Third, we describe an open-source master mix for RT-qPCR and show that it permits detection of viral RNA in NP swab samples. Lastly, we show that an end-point fluorescence measurement provides an accurate diagnostic readout without requiring a qPCR thermocycler. Adoption of these simple, inexpensive methods has the potential to significantly reduce the time and expense of COVID-19 testing.

Abstract This contribution summarizes the current state of research regarding so‐called sensor‐integrating machine elements as an enabler of digitalization in mechanical engineering and——if available—their application in industry. The focus is on the methodical aspects of the development of these machine elements in general as well as specific sensor‐integrating machine elements that are either already in use or currently under development. Developmental aspects include the robust design of initially evaluated concepts for sensor‐integrating machine elements as well as their modularization. Smart materials with sensory functions are included in the analysis as well as the differentiation with regard to add‐on sensors. The aim of the authors interlinked by a special research program funded by the German Research Foundation (DFG) is to facilitate the exchange with other researchers with the help of the comprehensive overview given in this contribution. The contribution concludes with a brief discussion of open challenges, such as the energy supply and data transfer in rotating systems and also data security.

Abstract This retrospective observational study evaluated racial disparities among Black and White patients with multiple myeloma (MM). We included patients from a longitudinal de-identified EHR-derived database who had ≥2 visits recorded on or after 1/1/2011, documented treatment, and race listed as White or Black. Black patients (n = 1172) were more likely female (54.8%/42.9%) and younger (

Abstract Over the past 13 years, there have been advances in characterizing the patient experience in oncology trials, primarily using patient-reported outcomes (PROs). This review aims to provide details on the PRO measures and analyses used in multiple myeloma (MM) registrational trials. We identified registrational trials supporting MM indications from 2007 to 2020 from FDA databases. Trial protocols, statistical analysis plans, and clinical study reports were reviewed for PRO measures used, collection methods, statistical analyses, baseline and instrument completion definitions, and thresholds for clinical meaningfulness. Twenty-five trials supporting 20 MM indications were identified; 17 (68%) contained submitted PRO data. Of the 17 trials, 14 were randomized controlled trials and the remainder were single-arm trials. All but one trial were open label trials. Seven trials collected data electronically and five in paper format. The majority of trials evaluated at least two PRO measures (82%) with two trials (12%) utilizing four measures. Nine unique PRO measures were used, most commonly the EORTC QLQ-30 (87%), EQ-5D (65%), and QLQ-MY20 (47%). All 17 (100%) trials provided descriptive summaries, 10 (59%) carried out longitudinal mixed model analysis, 9 (53%) conducted responder analysis, and 2 (12%) did a basic inferential test. We noted substantial heterogeneity in terms of PRO collection methods, measures, definitions, and analyses, which may hinder the ability to effectively capture and interpret patient experience in future MM clinical trials. Further research is needed to determine the most appropriate approaches for statistical and analytical methodologies for PRO data in MM trials.

This paper deals with the real-time simulation of a power tool battery pack on a mechatronic powertrain test bench. The ability of an easy-to-use model for quick and iterative test runs mainly depends on the effort of parameterization. For this purpose, an easily parameterizable battery model is required. The battery model used is based on the current state of research and simulates the battery's behavior with an adequate precision. The suggested parameterization allows building the model without the necessity of experimental investigation. Three different procedures for model parameterization were used and compared with the real battery behavior. In conclusion, this paper shows a good tradeoff between precision and an easy way to handle a battery model for testing mechatronic powertrains.

The design of reliable systems is a key challenge in product engineering [...]

Using hydrogen fuel cells for power systems, temperature conditions are important for efficient and reliable operations, especially in low-temperature environments. A heating system with an electrical energy buffer is therefore required for reliable operation. There is a research gap in finding an appropriate control strategy regarding energy efficiency and reliable operations for different environmental conditions. This paper investigates heating strategies for the subfreezing start of a fuel cell for portable applications at an early development stage to enable frontloading in product engineering. The strategies were investigated by simulation and experiment. A prototype for such a system was built and tested for subfreezing start-ups and non-subfreezing start-ups. This was done by heating the fuel cell system with different control strategies to test their efficiency. It was found that operating strategies to heat up the fuel cell system can ensure a more reliable and energy-efficient operation. The heating strategy needs to be adjusted according to the ambient conditions, as this influences the required heating energy, efficiency, and reliable operation of the system. A differentiation in the control strategy between subfreezing and non-subfreezing temperatures is recommended due to reliability reasons.

For the control of dynamic systems such as an Electro-Hydraulic Actuator (EHA), there is a need to optimize the control based on simulations, since a prototype or a physical system is usually not available during system design. In consequence, no system identification can be performed. Therefore, it is unclear how well a simulation model of an EHA can be used for multicriteria optimization of the position control due to the uncertain model quality. To evaluate the suitability for control optimization, the EHA is modeled and parameterized as a grey-box model using existing parameters independent of test bench experiments. A method for multi-objective optimization of a controller is used to optimize the position control of the EHA. Finally, the step responses are compared with the test bench. The evaluation of the step responses for different loads and control parameters shows similar behavior between the simulation model and the physical system on the test bench, although the essential phenomena could not be reproduced. This means that the model quality achieved by modeling is suitable as an indication for the optimization of the control by simulation without a physical system.

Repetitive overhead work with a heavy load increases the risk for work-related shoulder disorders. Occupational exoskeletons supporting arm elevation are potential solutions to reduce that risk by lowering the physical strains on the shoulder. Many studies have reported a reduction in shoulder stress in various overhead tasks by using such exoskeletons. However, the support demand can vary in each phase of motion as well as in each individual task. This paper presents a laboratory study with five participants to evaluate the influence of the support level of an active shoulder exoskeleton in different motion phases (e.g., arm lifting, screw-in, and arm lowering of two overhead tasks) to identify the potential optimization of support at each phase. Results show that the support level of the exoskeleton should be adapted to the motion phase of the two chosen tasks. A higher support force is desired for the screw phase compared to the arm lifting and lowering phases, and the support level needs to be reduced immediately for arm lowering after the screw phase. The time for switching the support levels can be recognized by the electric current of the screwdriver.

Impaired muscle regeneration has repeatedly been described after anterior cruciate ligament reconstruction (ACL-R). The results of recent studies provided some evidence for negative alterations in knee extensor muscles after ACL-R causing persisting strength deficits in spite of the regain of muscle mass. Accordingly, we observed that 12 weeks of concentric/eccentric quadriceps strength training with eccentric overload (CON/ECC+) induced a significantly greater hypertrophy of the atrophied quadriceps muscle after ACL-R than conventional concentric/eccentric quadriceps strength training (CON/ECC). However, strength deficits persisted and there was an unexpected increase in the proportion of slow type I fibers instead of the expected shift towards a faster muscle phenotype after CON/ECC+. In order to shed further light on muscle recovery after ACL-R, the steady-state levels of 84 marker mRNAs were analyzed in biopsies obtained from the vastus lateralis muscle of 31 subjects before and after 12 weeks of CON/ECC+ (n = 18) or CON/ECC strength training (n = 13) during rehabilitation after ACL-R using a custom RT2 Profiler PCR array. Significant (p < 0.05) changes were detected in the expression of 26 mRNAs, several of them involved in muscle wasting/atrophy. A different pattern with regard to the strength training mode was observed for 16 mRNAs, indicating an enhanced hypertrophic stimulus, mechanical sensing or fast contractility after CON/ECC+. The effects of the type of autograft (quadriceps, QUAD, n = 19, or semitendinosus tendon, SEMI, n = 12) were reflected in the lower expression of 6 mRNAs involved in skeletal muscle hypertrophy or contractility in QUAD. In conclusion, the greater hypertrophic stimulus and mechanical stress induced by CON/ECC+ and a beginning shift towards a faster muscle phenotype after CON/ECC+ might be indicated by significant gene expression changes as well as still ongoing muscle wasting processes and a negative impact of QUAD autograft.

Validation is important for a high product quality of drive components. An X-in-the-Loop test bench enables the integration of scaled prototypes through coupling systems and scaling models even before serial parts are available. In the context of X-in-the-loop investigations, it is still unclear whether a scaling model enables the early investigation of geometry variants in powertrain subsystems. In this paper, scaled geometry experiments taking into account the interacting system are considered to evaluate the scaling model in terms of early investigation of geometry variants. The aim of this paper is the functional investigation of geometrically scaled drive components by integrating scaled prototypes in an X-in-the-Loop test bench. Using an overload clutch with detents, component variants of different size levels are investigated in scaled experiments with a scaling model. The results confirm possibilities of X-in-the-Loop integration of scaled prototypes and their investigation on geometrically scaled drive components. The investigations show, therefore, the opportunities of integrating scaled drive components through the scaling model to support the investigation of geometry variants before serial parts are available. Scaled geometry investigations considering the interacting system can, thus, support product development.

Tool forces are a decisive parameter for manual grinding with hand-held power tools, which can be used to determine the productivity, quality of the work result, vibration exposition, and tool lifetime. One approach to tool force determination is the prediction of tool forces via measured operating parameters of a hand-held power tool. The problem is that the accuracy of tool force prediction with consumer-grade sensors remains unclear in manual grinding. Therefore, the accuracy of tool force prediction using Gaussian process regression is examined in a study for two hand-held angle grinders in four different applications in three directions using measurement data from an inertial measurement unit, a current sensor, and a voltage sensor. The prediction of the grinding normal force (rMAE = 11.44% and r = 0.84) and the grinding tangential force (rMAE = 18.21% and r = 0.82) for three tested applications, as well as the radial force for the application cutting with a cut-off wheel (rMAE = 19.67% and r = 0.80) is shown to be feasible. The prediction of the guiding force (rMAE = 87.02% and r = 0.37) for three tested applications is only possible to a limited extent. This study supports data acquisition and evaluation of hand-held power tools using consumer-grade sensors, such as an inertial measurement unit, in real-world applications, resulting in new potentials for product use and product development.

High-performance scientific applications are usually built from software modules written in multiple programming languages. This raises the issue of language interoperability which involves making calls between languages, converting basic types, and bridging disparate programming models. Babel provides a feature-rich, extensible, high-performance solution to the language interoperability problem currently supporting C, C++, FORTRAN 77, Fortran 90/95, Fortran 2003/2008, Python, and Java. Babel supports object-oriented programming features and interface semantics with runtime enforcement. In addition to in-process language interoperability, Babel includes remote method invocation to support hybrid parallel and distributed computing paradigms. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We previously reported significant variations in oxidation status and molecular length among sources and lots of human serum albumin (HSA) commercial preparations intended for clinical use. In this report, we investigated what effect the presence of HSA products have on the immune response in vitro. DESIGN: Laboratory study. SETTING: Trauma research basic science laboratory. SUBJECTS: Activated human peripheral blood mononuclear cells. INTERVENTIONS: Six commercial HSA preparations were tested for their effect on cytokine release from activated human peripheral blood mononuclear cells (PBMCs) and T-lymphocytes. Mass spectrometry analysis of aspartyl-alanyl diketopiperazine (DA-DKP) content of HSA and percentage of HSA having lost its amino terminal dipeptide aspartyl alanyl (HSA-DA) were correlated. MEASUREMENTS AND MAIN RESULTS: Human PBMCs were cultured in the presence of six commercial HSA preparations and activated via the T-cell receptor complex. A cloned T-lymphocyte cell line, activated with specific antigen, was also cultured with both synthetic DA-DKP and small molecular weight extracts from the commercial HSA tested. Supernatants were quantified by enzyme-linked immunosorbent assay for interferon-gamma and tumor necrosis factor-alpha content. DA-DKP was extracted from HSA by centrifugal filters and quantified by anion exchange liquid chromatography coupled to negative electrospray ionization mass spectrometry. HSA species were determined by reverse phase liquid chromatography coupled to positive electrospray ionization, time of flight mass spectrometry. All HSA preparations significantly inhibited the in vitro production of interferon-gamma and tumor necrosis factor-alpha by activated PBMCs. DA-DKP was detected in all HSA sources at concentrations ranging between 42.0 and 79.6 muM. A synthetic form of DA-DKP possessed similar immunosuppressive qualities in a dose-dependent manner on T lymphocytes. CONCLUSIONS: DA-DKP was present in significant concentrations in all HSA sources tested and was partially responsible for the immunosuppressive effects of HSA on activated PBMCs and T-lymphocytes in vitro. In view of these findings, administering HSA to immunocompromised critically ill patients might be reevaluated. [ABSTRACT FROM AUTHOR]

Image analysis tools for cancer, such as automatic nuclei segmentation, are impacted by the inherent variation contained in pathology image data. Convolutional neural networks (CNN), demonstrate success in generalizing to variable data, illustrating great potential as a solution to the problem of data variability. In some CNN-based segmentation works for digital pathology, authors apply color normalization (CN) to reduce color variability of data as a preprocessing step prior to prediction, while others do not. Both approaches achieve reasonable performance and yet, the reasoning for utilizing this step has not been justified. It is therefore important to evaluate the necessity and impact of CN for deep learning frameworks, and its effect on downstream processes. In this paper, we evaluate the effect of popular CN methods on CNN-based nuclei segmentation frameworks.

Abstract Background There are over 700 known arboviruses and at least 80 immunologically distinct types that cause disease in humans. Arboviruses are transmitted among vertebrates by biting insects, chiefly mosquitoes and ticks. These viruses are widely distributed throughout the world, depending on the presence of appropriate hosts (birds, horses, domestic animals, humans) and vectors. Mosquito-borne arboviruses present some of the most important examples of emerging and resurgent diseases of global significance. Methods A strategy has been developed by which host-range mutants of Dengue virus can be constructed by generating deletions in the transmembrane domain (TMD) of the E glycoprotein. The host-range mutants produced and selected favored growth in the insect hosts. Mouse trials were conducted to determine if these mutants could initiate an immune response in an in vivo system. Results The DV2 E protein TMD defined as amino acids 452SWTMKILIGVIITWIG467 was found to contain specific residues which were required for the production of this host-range phenotype. Deletion mutants were found to be stable in vitro for 4 sequential passages in both host cell lines. The host-range mutants elicited neutralizing antibody above that seen for wild-type virus in mice and warrant further testing in primates as potential vaccine candidates. Conclusions Novel host-range mutants of DV2 were created that have preferential growth in insect cells and impaired infectivity in mammalian cells. This method for creating live, attenuated viral mutants that generate safe and effective immunity may be applied to many other insect-borne viral diseases for which no current effective therapies exist.

Type 2 Nuclear Receptors (T2NRs) require heterodimerization with a common partner, the Retinoid X Receptor (RXR), to bind cognate DNA recognition sites in chromatin. Based on previous biochemical and over-expression studies, binding of T2NRs to chromatin is proposed to be regulated by competition for a limiting pool of the core RXR subunit. However, this mechanism has not yet been tested for endogenous proteins in live cells. Using single molecule tracking (SMT) and proximity-assisted photoactivation (PAPA), we monitored interactions between endogenously tagged retinoid X receptor (RXR) and retinoic acid receptor (RAR) in live cells. Unexpectedly, we find that higher expression of RAR, but not RXR increases heterodimerization and chromatin binding in U2OS cells. This surprising finding indicates the limiting factor is not RXR but likely its cadre of obligate dimer binding partners. SMT and PAPA thus provide a direct way to probe which components are functionally limiting within a complex TF interaction network providing new insights into mechanisms of gene regulation in vivo with implications for drug development targeting nuclear receptors.

Psychomotor skill and decision-making efficiency in surgical wire navigation can be objectively evaluated by analysis of intraoperative fluoroscopic image sequences. Prior work suggests that such image-based behavior analysis of operating room (OR) performance can predict performer experience level (R 2  = 0.62) and agree with expert opinion (the current standard) on the quality of a final implant construct (R 2  = 0.59). However, it is unclear how objective image-based evaluation compares with expert assessments for entire technical OR performances. This study examines the relationships between three key variables: (1) objective image-based criteria, (2) expert opinions, and (3) performing surgeon experience level. A paired-comparison survey of seven experts, based upon eight OR fluoroscopic wire navigation image sequences, shows that the experts' preferences are best explained by objective metrics that reflect psychomotor and decision-making behaviors which are counter-productive to successful implant placement, like image count (R 2  = 0.83) and behavior tally (R 2  = 0.74). One such behavior, adjustments away from goal, uniquely correlated well with all three key variables: a fluoroscopic image-based analysis composite score (R 2  = 0.40), expert consensus (R 2  = 0.76), and performer experience (R 2  = 0.41). These results confirm that experts view less efficient technical behavior as indicative of lesser technical proficiency. While expert assessments of technical skill were reliable and consistent, neither individual nor consensus expert opinion appears to correlate with performer experience (R 2  = 0.11)., (© 2023 The Authors. Journal of Orthopaedic Research® published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.)

Background: Antegrade femoral intramedullary nailing (IMN) is a common orthopedic procedure that residents are exposed to early in their training. A key component to this procedure is placing the initial guide wire with fluoroscopic guidance. A simulator was developed to train residents on this key skill, building off an existing simulation platform originally developed for wire navigation during a compression hip screw placement. The objective of this study was to assess the construct validity of the IMN simulator., Methods: Thirty orthopedic surgeons participated in the study: 12 had participated in fewer than 10 hip fracture or IMN related procedures and were categorized as novices; 18 were faculty, categorized as experts. Both cohorts were instructed on the goal of the task, placing a guide wire for an IM nail, and the ideal wire position reference that their wire placement would be graded against. Participants completed 2 assessments with the simulator. Performance was graded on the distance from the ideal starting point, distance from the ideal end point, wire trajectory, duration, fluoroscopy image count, and other elements of surgical decision making. A two-way ANOVA analysis was used to analyze the data looking at experience level and trial number., Results: The expert cohort performed significantly better than the novice cohort on all metrics but one (overuse of fluoroscopy). The expert cohort had a more accurate starting point and completed the task while using fewer images and less overall time., Conclusion: This initial study shows that the IMN application of a wire navigation simulator demonstrates good construct validity. With such a large cohort of expert participants, we can be confident that this study captures the performance of active surgeons today. Implementing a training curriculum on this simulator has the potential to increase the performance of the novice level residents prior to their operating on a vulnerable patient. Level of Evidence: III ., (Copyright © The Iowa Orthopaedic Journal 2023.)