Collaborative Online International Learning in Physiology: A Case Study.

Internationalisation in higher education is essential, and although active learning methodologies are increasing and allow students to develop transversal skills, most still have a very local scope. In this context, the Collaborative Online International Learning (COIL) methodology is an interesting approach to benefit the students' development. It consists of an online program that involves creating multicultural teams to develop a specific learning project. Although this methodology is expanding, its use in physiology is still scarce. This paper aims to show an example of applying COIL methodology in physiology topics to enhance higher-education students' innovation and business skills. Our example project developed a sports-assessment service concept focused on physiology and biomechanics assessments. The program involved teams from Brazil, Germany, and Spain, comprising undergraduate and master students. Over seven weeks, these teams, mentored by professors and researchers, engaged in workshops covering COIL methodology, business model design, executive summary planning, economic analyses, and communication techniques. Key outcomes included learning new concepts, developing soft skills, building confidence in innovative solution proposals, and experiencing diverse cultures. Challenges faced were language barriers, scheduling, task complexity, and logistical issues. This experience confirms the effectiveness of incorporating programs using COIL methodology into educational curriculums. Doing so exposes physiology students to innovation, entrepreneurship, and business creation while strengthening their professional connections and opening up post-graduation opportunities.

Metrology for 2D materials: a perspective review from the international roadmap for devices and systems.

The International Roadmap for Devices and Systems (IRDS) predicts the integration of 2D materials into high-volume manufacturing as channel materials within the next decade, primarily in ultra-scaled and low-power devices. While their widespread adoption in advanced chip manufacturing is evolving, the need for diverse characterization methods is clear. This is necessary to assess structural, electrical, compositional, and mechanical properties to control and optimize 2D materials in mass-produced devices. Although the lab-to-fab transition remains nascent and a universal metrology solution is yet to emerge, rapid community progress underscores the potential for significant advancements. This paper reviews current measurement capabilities, identifies gaps in essential metrology for CMOS-compatible 2D materials, and explores fundamental measurement science limitations when applying these techniques in high-volume semiconductor manufacturing.

Nanoscale Three-Dimensional Imaging of Integrated Circuits Using a Scanning Electron Microscope and Transition-Edge Sensor Spectrometer.

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO2 integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed.

Unlocking Precision Gene Therapy: Harnessing AAV Tropism with Nanobody Swapping at Capsid Hotspots.

Adeno-associated virus has been remarkably successful in the clinic, but its broad tropism is a practical limitation of precision gene therapy. A promising path to engineer AAV tropism is the addition of binding domains to the AAV capsid that recognize cell surface markers present on a targeted cell type. We have recently identified two previously unexplored capsid regions near the 2-fold valley and 5-fold pore of the AAV capsid that are amenable to insertion of larger protein domains including nanobodies. Here, we demonstrate that these hotspots facilitate AAV tropism switching through simple nanobody replacement without extensive optimization in both VP1 and VP2. We demonstrate highly specific targeting of human cancer cells expressing fibroblast activating protein (FAP). Our data suggest that engineering VP2 is the preferred path for maintaining both virus production yield and infectivity. Our study shows that nanobody swapping at multiple capsid location is a viable strategy for nanobody-directed cell-specific AAV targeting.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Unique Method for Facile Postsynthetic Modification of Nonisocyanate Polyurethanes.

Nonisocyanate polyurethanes (NIPUs) are broadly investigated as a potential replacement for conventional polyurethanes (PUs) to eliminate the use of toxic isocyanates and reduce occupational hazards. One of the most popular approaches to NIPU synthesis is the polyaddition of cyclic bis(carbonate)s and diamines to form poly(hydroxyurethane)s (PHUs). However, such PHUs are highly hydrophilic due to the presence of two hydroxyl groups per repeat unit, and the resulting moisture absorption significantly degrades their thermomechanical performance and physical stability upon exposure to humidity, thus limiting their utility. Here, we introduce a simple and scalable approach for the modification of PHUs to increase hydrophobicity and adjust their properties. The proposed reaction between aldehydes and appropriately spaced hydroxyl groups in the polymer backbone resulted in high degrees of modification (up to 84%) and up to 3-fold reductions in water uptake at 85% RH. Furthermore, the use of aromatic aldehydes in particular enabled the retention of mechanical properties over a wide range of humidity levels, resulting in performance comparable to conventional PUs. Finally, we note that this approach is not limited to reducing moisture sensitivity alone and provides ample opportunities for imparting a broad range of novel properties to PHUs through an appropriate selection of functional aldehydes.

Unravelling the mystery of endemic versus translocated populations of the endangered Australian lungfish (Neoceratodus forsteri).

The Australian lungfish is a primitive and endangered representative of the subclass Dipnoi. The distribution of this species is limited to south-east Queensland, with some populations considered endemic and others possibly descending from translocations in the late nineteenth century shortly after European discovery. Attempts to resolve the historical distribution of this species have met with conflicting results based on descriptive genetic studies. Understanding if all populations are endemic or some are the result of, or influenced by, translocation events, has implications for conservation management. In this work, we analysed the genetic variation at three types of markers (mtDNA genomes, 11 STRs and 5196 nuclear SNPs) using the approximate Bayesian computation (ABC) algorithm to compare several demographic models. We postulated different contributions of Mary River and Burnett River gene pools into the Brisbane River and North Pine River populations, related to documented translocation events. We ran the analysis for each marker type separately, and we also estimated the posterior probabilities of the models combining the markers. Nuclear SNPs have the highest power to correctly identify the true model among the simulated datasets (where the model was known), but different marker types typically provided similar answers. The most supported demographic model able to explain the real dataset implies that an endemic gene pool is still present in the Brisbane and North Pine Rivers and coexists with the gene pools derived from past documented translocation events. These results support the view that ABC modelling can be useful to reconstruct complex historical translocation events with contemporary implications, and will inform ongoing conservation efforts for the endangered and iconic Australian lungfish.

Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures.

BACKGROUND: Cirrus is an automated risk predictor for breast cancer that comprises texture-based mammographic features and is mostly independent of mammographic density. We investigated genetic and environmental variance of variation in Cirrus. METHODS: We measured Cirrus for 3,195 breast cancer-free participants, including 527 pairs of monozygotic (MZ) twins, 271 pairs of dizygotic (DZ) twins, and 1,599 siblings of twins. Multivariate normal models were used to estimate the variance and familial correlations of age-adjusted Cirrus as a function of age. The classic twin model was expanded to allow the shared environment effects to differ by zygosity. The SNP-based heritability was estimated for a subset of 2,356 participants. RESULTS: There was no evidence that the variance or familial correlations depended on age. The familial correlations were 0.52 (SE, 0.03) for MZ pairs and 0.16(SE, 0.03) for DZ and non-twin sister pairs combined. Shared environmental factors specific to MZ pairs accounted for 20% of the variance. Additive genetic factors accounted for 32% (SE = 5%) of the variance, consistent with the SNP-based heritability of 36% (SE = 16%). CONCLUSION: Cirrus is substantially familial due to genetic factors and an influence of shared environmental factors that was evident for MZ twin pairs only. The latter could be due to nongenetic factors operating in utero or in early life that are shared by MZ twins. IMPACT: Early-life factors, shared more by MZ pairs than DZ/non-twin sister pairs, could play a role in the variation in Cirrus, consistent with early life being recognized as a critical window of vulnerability to breast carcinogens.

New care pathway to enable ambulances transfer patients to a model 2 hospital medical assessment unit.

BACKGROUND: Reconfiguration of the Irish acute hospital sector resulted in the establishment of a Medical Assessment Unit (MAU) in Mallow General Hospital (MGH). We developed a protocol whereby certain patients deemed to be low risk for clinical deterioration could be brought by the National Ambulance Service (NAS) to the MAU following a 999 or 112 call. AIMS: The aim of this paper is to report on the initial experience of this quality improvement initiative. METHODS: The Plan-Do-Study-Act (PDSA) Cycle for quality improvement was implemented when undertaking this project. A pathway was established whereby, following discussion between paramedic and physician, patients for whom a 999 or 112 call had been made could be brought directly to the MAU in MGH. Strict inclusion and exclusion criteria were agreed. The protocol was implemented from the 1st of September 2022 for a 3-month pilot period. RESULTS: Of 39 patients discussed, 29 were accepted for review in the MAU. One of the 29 accepted patients declined transfer to MAU. Of 28 patients reviewed in the MAU, 7 were discharged home. One patient required same day transfer to a model 4 centre. Twenty patients were admitted to MGH with an average length of stay of 8 days. Frailty and falls accounted for 7 of the admissions and the mean length of stay for these patients was 12 days. CONCLUSIONS: Our results have demonstrated the safety, feasibility and effectiveness of this pathway. With increased resourcing, upscaling of this initiative is possible and should be considered.

PmxPred: A data-driven approach for the identification of active polymyxin analogues against gram-negative bacteria.

The multidrug-resistant Gram-negative bacteria has evolved into a worldwide threat to human health; over recent decades, polymyxins have re-emerged in clinical practice due to their high activity against multidrug-resistant bacteria. Nevertheless, the nephrotoxicity and neurotoxicity of polymyxins seriously hinder their practical use in the clinic. Based on the quantitative structure-activity relationship (QSAR), analogue design is an efficient strategy for discovering biologically active compounds with fewer adverse effects. To accelerate the polymyxin analogues discovery process and find the polymyxin analogues with high antimicrobial activity against Gram-negative bacteria, here we developed PmxPred, a GCN and catBoost-based machine learning framework. The RDKit descriptors were used for the molecule and residues representation, and the ensemble learning model was utilized for the antimicrobial activity prediction. This framework was trained and evaluated on multiple Gram-negative bacteria datasets, including Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and a general Gram-negative bacteria dataset achieving an AUROC of 0.857, 0.880, 0.756, 0.895 and 0.865 on the independent test, respectively. PmxPred outperformed the transfer learning method that trained on 10 million molecules. We interpreted our model well-trained model by analysing the importance of global and residue features. Overall, PmxPred provides a powerful additional tool for predicting active polymyxin analogues, and holds the potential elucidate the mechanisms underlying the antimicrobial activity of polymyxins. The source code is publicly available on GitHub (https://github.com/yanwu20/PmxPred).

Does the 11-year solar cycle affect lake and river ice phenology?

Records of ice-on and ice-off dates are available for lakes and rivers across the Northern Hemisphere spanning decades and in some cases centuries. This data provides an opportunity to investigate the climatic processes that may control ice phenology. Previous studies have reported a trend toward shorter ice-covered seasons with global warming, as well as links between ice phenology and several modes of natural climate variability such as the North Atlantic Oscillation, the Pacific-North American Pattern, the El Niño-Southern Oscillation, the Pacific Decadal Oscillation, and the Atlantic Multidecadal Oscillation. The 11-year sunspot cycle has also been proposed as a driver of ice phenology, which is somewhat surprising given that this cycle's strongest impacts are in the stratosphere. In this study, we use a large data set of lakes and rivers across the Northern Hemisphere to test this potential link. We find little or no connection between the sunspot cycle and either ice-on or ice-off dates. We conclude that while many well-known climate cycles do impact ice phenology, we are able to rule out any strong impact of the solar cycle.

Model Parameter Estimation As Features to Predict the Duration of Epileptic Seizures From Onset.

The durations of epileptic seizures are linked to severity and risk for patients. It is unclear if the spatiotemporal evolution of a seizure has any relationship with its duration. Understanding such mechanisms may help reveal treatments for reducing the duration of a seizure. Here, we present a novel method to predict whether a seizure is going to be short or long at its onset using features that can be interpreted in the parameter space of a brain model. The parameters of a Jansen-Rit neural mass model were tracked given intracranial electroencephalography (iEEG) signals, and were processed as time series features using MINIROCKET. By analysing 2954 seizures from 10 patients, patient-specific classifiers were built to predict if a seizure would be short or long given 7 s of iEEG at seizure onset. The method achieved an area under the receiver operating characteristic curve (AUC) greater than 0.6 for five of 10 patients. The behaviour in the parameter space has shown different mechanisms are associated with short/long seizures.Clinical relevance-This shows that it is possible to classify whether a seizure will be short or long based on its early characteristics. Timely interventions and treatments can be applied if the duration of the seizures can be predicted.

Statutory health insurance-covered pre-exposure prophylaxis in Germany: changing trends in nationwide tenofovir disoproxil/emtricitabine prescriptions during the COVID-19 pandemic.

Background: In 2019, Germany introduced a law to reimburse high-incidence populations for pre-exposure prophylaxis (PrEP), prescribed as tenofovir-disoproxil/emtricitabine (TDF/FTC), via statutory health insurance (SHI). We studied changes in TDF/FTC-prescriptions after the implementation of this law and during the COVID-19 pandemic. Methods: We performed an interrupted time series analysis with monthly prescriptions per defined time period as the outcome. We considered the introduction of SHI-covered PrEP (09/2019) as an interruption, and four COVID-19 waves and two national lockdowns (2020-2021) as explanatory variables. We extrapolated prescriptions had the lockdowns not occurred, and compared this to the actual prescriptions. We performed sub-analyses based on stratification by five federal states with the highest proportion of PrEP users. We assessed the models' goodness-of-fit based on the adjusted R-squared using RStudio. Results: The best fitting model included SHI-covered PrEP and the first COVID-19 lockdown (04/2020). The decrease in prescriptions during the first lockdown was significant nationally, and in the five federal states for single-month prescriptions. The first lockdown resulted in reductions of 57.7% (95% prediction interval (PI): 23.0%-92.4%) for single-month prescriptions, while 17.4% (95% PI: 0.28%-34.5%) nationally, and 13.9% (95% PI: -3.67%-31.5%) for 3-month prescriptions. Conclusion: Introduction of SHI-covered PrEP resulted in a doubling of TDF/FTC-prescriptions nationwide in the first month alone. A drop in prescriptions was most apparent after the first lockdown, and particularly affected PrEP initiations, possibly due to reduced healthcare access and behavioural changes. Ongoing monitoring of TDF/FTC-prescriptions is needed to safeguard access to preventative care such as PrEP and particularly PrEP initiation during public health crises like COVID-19.

Multiparametric domain insertional profiling of adeno-associated virus VP1.

Several evolved properties of adeno-associated virus (AAV), such as broad tropism and immunogenicity in humans, are barriers to AAV-based gene therapy. Most efforts to re-engineer these properties have focused on variable regions near AAV's 3-fold protrusions and capsid protein termini. To comprehensively survey AAV capsids for engineerable hotspots, we determined multiple AAV fitness phenotypes upon insertion of six structured protein domains into the entire AAV-DJ capsid protein VP1. This is the largest and most comprehensive AAV domain insertion dataset to date. Our data revealed a surprising robustness of AAV capsids to accommodate large domain insertions. Insertion permissibility depended strongly on insertion position, domain type, and measured fitness phenotype, which clustered into contiguous structural units that we could link to distinct roles in AAV assembly, stability, and infectivity. We also identified engineerable hotspots of AAV that facilitate the covalent attachment of binding scaffolds, which may represent an alternative approach to re-direct AAV tropism.

Artificial Intelligence and Deep Learning for Advancing PET Image Reconstruction: State-of-the-Art and Future Directions.

Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conventional image reconstruction (IR) techniques like filtered backprojection and iterative algorithms are powerful but face limitations. PET IR can be seen as an image-to-image translation. Artificial intelligence (AI) and deep learning (DL) using multilayer neural networks enable a new approach to this computer vision task. This review aims to provide mutual understanding for nuclear medicine professionals and AI researchers. We outline fundamentals of PET imaging as well as state-of-the-art in AI-based PET IR with its typical algorithms and DL architectures. Advances improve resolution and contrast recovery, reduce noise, and remove artifacts via inferred attenuation and scatter correction, sinogram inpainting, denoising, and super-resolution refinement. Kernel-priors support list-mode reconstruction, motion correction, and parametric imaging. Hybrid approaches combine AI with conventional IR. Challenges of AI-assisted PET IR include availability of training data, cross-scanner compatibility, and the risk of hallucinated lesions. The need for rigorous evaluations, including quantitative phantom validation and visual comparison of diagnostic accuracy against conventional IR, is highlighted along with regulatory issues. First approved AI-based applications are clinically available, and its impact is foreseeable. Emerging trends, such as the integration of multimodal imaging and the use of data from previous imaging visits, highlight future potentials. Continued collaborative research promises significant improvements in image quality, quantitative accuracy, and diagnostic performance, ultimately leading to the integration of AI-based IR into routine PET imaging protocols.

Causal relationships between breast cancer risk factors based on mammographic features.

BACKGROUND: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. METHODS: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. RESULTS: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). CONCLUSIONS: In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.

Vertical contact forces affect vibration perception in human hairy skin.

Background: Skin is the largest organ of the human body and fulfills many important functions, like detecting mechanical stimuli. Skin can be divided into glabrous (non-hairy) and hairy skin. These two skin types differ with regard to their mechanical properties and in the distribution of mechanoreceptors. Although many investigations focus on glabrous skin, hairy skin still plays a fundamental role in various activities, e.g., with regard to the perception of pleasantness or for developing wearable vibrotactile devices for pattern recognition in persons with disabilities. Unfortunately, investigations on influencing factors, like vertical contactor force, are scarce for hairy skin. Similarly, it would also be interesting to investigate whether regional vibratory sensitivity differences are present across the human torso. Hence, this study investigated the effects of vertical contactor forces and different anatomical locations on vibration perception. Four anatomical torso regions were studied. Based on findings in glabrous skin, we generally hypothesized improved vibration perception with increasing contactor forces and regional sensitivity differences between the anatomical locations. Methods: Forty young and healthy individuals participated (23.0 ± 2.0 yrs), and vibration perception thresholds (VPTs) were determined at 30 Hz for three vertical force levels (0.6, 2.4, and 4.8 N) at four torso locations (sternum, deltoid/shoulder, lower back, middle lateral torso side). Results: Higher contactor forces resulted in lower VPTs corresponding to improved vibration perception, regardless of anatomical location. In addition, the sternum region was more sensitive than the remaining three regions, regardless of force level. The reasons for these findings may be a varying number and activation pattern of afferents activated under the different conditions. The findings of this study complement the understanding of vibrotactile sensitivity in hairy skin and may offer implications when developing vibrotactile devices or clothing/textiles, for example.

Head-to-Head Comparison of Dual-Source and Split-Beam Filter Multi-Energy CT versus SPECT/CT for Assessing Lobar Lung Perfusion in Emphysema.

Purpose: To evaluate dual-source and split-beam filter multi-energy chest CT in assessing pulmonary perfusion on a lobar level in patients with lung emphysema, using perfusion SPECT as the reference standard. Materials and Methods: Patients with emphysema evaluated for lung volume reduction therapy between May 2016 and February 2021 were retrospectively included. All patients underwent SPECT and either dual-source or split-beam filter (SBF) multi-energy CT. To calculate the fractional lobar lung perfusion (FLLP), SPECT acquisitions were co-registered with chest CT scans (hereafter, SPECT/CT) and semi-manually segmented. For multi-energy CT scans, lung lobes were automatically segmented using a U-Net model. Segmentations were manually verified. The FLLP was derived from iodine maps computed from the multi-energy data. Statistical analysis included Pearson and intraclass correlation coefficients and Bland-Altman analysis. Results: Fifty-nine patients (30 male, 29 female; 31 underwent dual-source CT, 28 underwent SBF CT; mean age for all patients, 67 years ± 8 [SD]) were included. Both multi-energy methods significantly correlated with the SPECT/CT acquisitions for all individual lobes (P < .001). Pearson correlation concerning all lobes combined was significantly better for dual-source (r = 0.88) than for SBF multi-energy CT (r = 0.78; P = .006). On the level of single lobes, Pearson correlation coefficient differed for the right upper lobe only (dual-source CT, r = 0.88; SBF CT, r = 0.58; P = .008). Conclusion: Dual-source and SBF multi-energy CT accurately assessed lung perfusion on a lobar level in patients with emphysema compared with SPECT/CT. The overall correlation was higher for dual-source multi-energy CT.Keywords: Chronic Obstructive Pulmonary Disease, Comparative Studies, Computer Applications, CT Spectral Imaging, Image Postprocessing, Lung, Pulmonary Perfusion© RSNA, 2023.

Assessing immunogenicity barriers of the HIV-1 envelope trimer.

Understanding the balance between epitope shielding and accessibility on HIV-1 envelope (Env) trimers is essential to guide immunogen selection for broadly neutralizing antibody (bnAb) based vaccines. To investigate the antigenic space of Env immunogens, we created a strategy based on synthetic, high diversity, Designed Ankyrin Repeat Protein (DARPin) libraries. We show that DARPin Antigenicity Analysis (DANA), a purely in vitro screening tool, has the capability to extrapolate relevant information of antigenic properties of Env immunogens. DANA screens of stabilized, soluble Env trimers revealed that stronger trimer stabilization led to the selection of highly mutated DARPins with length variations and framework mutations mirroring observations made for bnAbs. By mimicking heterotypic prime-boost immunization regimens, DANA may be used to select immunogen combinations that favor the selection of trimer-reactive binders. This positions DANA as a versatile strategy for distilling fundamental antigenic features of immunogens, complementary to preclinical immunogenicity testing.

Screening in serum-derived medium reveals differential response to compounds targeting metabolism.

A challenge for screening new anticancer drugs is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels, which can influence cell metabolism and drug sensitivity. A general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To address this, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We screened several small molecule libraries and found that compounds targeting metabolic enzymes were differentially effective in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.