Biology subjects

Sood, A.

Publications and source records attributed to Sood, A..

At least 19 recordsLinked to original sources

bioRxiv2026

A microbiome-derived metabolite from Staphylococcus epidermidis inhibits Staphylococcus aureus biofilm formation and virulence

Staphylococcus epidermidis is a common member of the healthy skin microbiome that contributes to barrier function and protection against pathogen colonization. In contrast, Staphylococcus aureus is a major human pathogen and the leading cause of skin and soft tissue infections, owing in part to its robust biofilm-forming capacity and increasing antimicrobial resistance. We previously demonstrated that S. epidermidis cell-free conditioned media (CFCM) inhibit S. aureus biofilm formation by altering bacterial gene expression without affecting growth. Here, we identify the metabolite responsible for this activity. Bioactivity-guided fractionation of S. epidermidis CFCM revealed pyroglutamic acid (PCA) as the active antibiofilm compound. Commercially sourced PCA inhibited S. aureus biofilm formation and reduced adhesion to epithelial cells. In a murine skin infection model, PCA treatment significantly attenuated disease severity, accelerated wound healing, and reduced bacterial burden. Analysis of S. epidermidis CFCM by chromatography, nuclear magnetic resonance spectroscopy, and mass spectrometry confirmed the presence of PCA and identified it as the bioactive constituent responsible for antibiofilm activity. Together, these findings uncover a previously unrecognized mechanism by which S. epidermidis suppresses S. aureus virulence and highlight the potential of microbiome-derived metabolites as therapeutics for the prevention and treatment of S. aureus skin infections.

microbiology↗

bioRxiv2026

Valency-Limited Molecular Dynamics Simulations of Stickers-and-Spacers Polymers Reveal a Tradeoff Between Condensation and Organization

Biomolecular condensates formed by intrinsically disordered proteins (IDPs) are often described using stickers-and-spacers models, in which specific sticker motifs form reversible crosslinks and spacer regions modulate phase behavior. Recent theory predicts that heterogeneous nonspecific spacer interactions can promote condensation but may also disrupt sticker-mediated organization. Here, we develop an off-lattice coarse-grained stickers-and-spacers polymer model for continuous molecular dynamics simulations and implement it in the GPU-accelerated OpenABC package. The model uses a directional sticker-sticker interaction to encode limited valency through interaction geometry, producing effectively one-to-one sticker binding without explicit bond assignment. Simulations of one-component systems show that sticker affinity and multivalency promote porous, network-like condensates, while nonspecific spacer interactions can also drive phase separation but produce more compact, spacer-dominated dense phases. When both interaction types are present, strong spacer heterogeneity reduces sticker conversion, suppresses sticker mobility, and disrupts the sticker-mediated network. In two-component systems, specific sticker interactions buffer client recruitment into host condensates, while nonspecific spacer interactions produce reservoir-dependent uptake. These results support a tradeoff in which spacer heterogeneity promotes condensation at the cost of condensate organization and compositional robustness, providing a physical rationale for the suppression of promiscuous spacer interactions in low-complexity IDP regions.

biophysics↗

bioRxiv2026

MAHLER: Integrating Metadynamics and Inverse Folding to Predict Antibody-Antigen Kinetics

Binding kinetics are crucial for antibody function, shaping pharmacokinetics and in vivo efficacy beyond what equilibrium affinity captures. We present "Metadynamics-Anchored Hybrid Learning for Engineering off-Rates (MAHLER)", a fully open-source machine learning/physics hybrid method that predicts relative antibody-antigen residence times at scale. Incorporating inverse-folding models into molecular dynamics simulations, MAHLER shows first-in-class screening-grade accuracy in calculating relative antibody-antigen dissociation kinetics across a family of point mutants. After initial antigen-specific setup, each prediction takes only 4 minutes on a single NVIDIA A100 GPU, compared to days even with already enhanced molecular dynamics simulations. This provides practical kinetics-aware complement to current computational design approaches that focus primarily on binding affinity for antibody-antigen complexes.

biophysics↗

bioRxiv2026

On improving experimental binding affinity predictions with synthetic data

The success of deep learning binding affinity prediction models depends critically on expanding experimental data with reliable synthetic data. We extend the Structurally Augmented IC50 Repository (SAIR) with {approx}80K absolute free energy perturbation (AFEP) calculations and present two distinct data splits, SAIR-FEP and SAIR-OOD (out-of-distribution), to simulate realistic drug discovery scenarios. We compare sequence-based proteochemometric (PCM) models and state-of-the-art, structure-based deep learning models and demonstrate that PCM models can be enhanced by physics-based descriptors. While structure-based deep learning methods capture finer geometric detail, their performance is highly sensitive to the input structure. By filtering for high-confidence, co-folded complexes, we show that the performance improves predictably, whereas training on all complexes blindly does not yield performance gains. Finally, using the SAIR-OOD split, we demonstrate that simultaneous training on synthetic and experimental data improves performance on publicly available, experimental benchmarks. These results provide a clear strategy for using synthetic data to advance experimental binding affinity predictions.

molecular biology↗

bioRxiv2026

Combination Treatment with Intravesical Interferon-Alpha Gene Therapy and Oral Pan-ErbB Receptor Family Blocker Improves Survival in Mice with Bladder Cancer

PurposeIntravesical interferon-alpha (IFN) gene therapy has shown promise in treating BCG-unresponsive non-muscle invasive bladder cancer (NMIBC). Ongoing work in our lab aims to further improve its treatment efficacy by identifying resistance mechanisms and deploying targeted combination treatment strategies. Experimental designWe performed end-tumor RNA-seq analysis of MB49 murine tumors treated with IFN gene therapy, identifying the ErbB pathway as a resistance mechanism. We consequently hypothesized that a combination treatment involving an ErbB pathway blocker and IFN could yield improved outcomes. MB49 cells were treated in vitro with lentiviral IFN (LV-IFN) gene therapy, with/without Afatinib, a pan-ErbB inhibitor, and cell viability and migration assays were performed. Next, in vivo studies were conducted in the syngeneic MB49 orthotopic murine bladder cancer model. The mice were randomized into 5 treatment groups (n=10 each): saline (Ctrl), LV-Ctrl, oral Afatinib monotherapy, intravesical LV-IFN monotherapy, and the experimental intravesical LV-IFN + oral Afatinib combination therapy. Overall survival (OS) and drug toxicity were assessed. ResultsCombination therapy significantly reduced MB49 cell viability in vitro compared to all other treatment conditions (mean relative ATPase activity at 72 h for the combination treatment was 4%, compared to 100%, 26%, and 28% for Ctrl, LV-IFN, and Afatinib, respectively, p<0.001). This additive effect on cell viability appeared to be driven by a combination of early-cytostatic and late-cytolytic effects. The combination treatment also markedly inhibited cell migration (mean migrated cells/10x Boyden chamber assay at 36 h were: 92.3 for the combination therapy and 631.0, 600.4, and 270.3 for Ctrl, LV-IFN, and Afatinib, respectively, p<0.001). Finally, the in vivo studies demonstrated improved OS with combination therapy (median OS was 49 d in the combination group vs 15, 29, and 26 d in Ctrl, LV-IFN, and Afatinib groups, respectively, Log-rank p<0.001). No mice in the combination therapy group died of drug toxicity. ConclusionsOur preliminary findings suggest that the ErbB pathway may serve as a clinically significant resistance mechanism to intravesical IFN gene therapy, and when targeted concurrently, may improve treatment efficacy.

cancer biology↗

bioRxiv2026

The C. elegans nervous system reads the internal state of the hydrogen peroxide-detoxification machinery to trigger escape from this common reactive chemical

Hydrogen peroxide (H2O2) is the most common reactive chemical threat faced by organisms. Here, we map the neural circuit that drives chemotactic escape from environmental H2O2 in the nematode C. elegans. Twenty-four neuron classes with sensory endings at the mouth and nose of the animal detect H2O2. Their response dynamics encode stimulus intensity and exposure history, and their partial redundancy makes avoidance resilient to the loss of individual inputs. Sensing begins when H2O2 oxidizes the peroxidatic and resolving cysteines of the cytosolic peroxiredoxin PRDX-2, which relays this oxidative signal to cysteines on the LITE-1 and GUR-3 ion channels, triggering calcium influx in sensory neurons that drive escape. Most of these neurons release glutamate to drive H2O2-dependent excitation of AIA interneurons, whereas others signal through non-glutamatergic routes, providing multiple routes for signal transmission. Thus, the C. elegans nervous system acts as a hydrogen peroxide sentinel that monitors H2O2-induced changes in the intracellular H2O2-detoxification machinery and relays them to interneurons driving organism-wide escape. This raises the possibility that circuit defects in aging and neurodegenerative disease arise from altered peroxiredoxin-mediated H2O2 signaling rather than primarily from direct macromolecular damage.

neuroscience↗

bioRxiv2025

The Challenge of Choosing a Negative Control: A Behavioural and Morphological Characterization of Various unc-43 LOF Alleles in the Model Organism C. elegans

Loss-of-Function (LOF) analyses have been pivotal in the discovery of genetic function in biological processes. However, phenotypic variation can occur between different supposedly LOF alleles of the same gene. We investigated the body of research surrounding the nematode ortholog of the Calcium/Calmodulin-dependent protein Kinase II (CAMKII), unc-43, because of its relevance in a large range of biological functions. Our analysis shows that published findings on unc-43 function were obtained from studies using numerous loss-of-function alleles, leading to potential challenges in aligning research findings. We investigated the similarity of these putative loss-of-function (LOF) mutations by using the Multi-Worm Tracker (Swierczek et al., 2011) to phenotype nine LOF alleles across 27 phenotypes, spanning morphology, baseline locomotion and habituation learning and memory. Interestingly, our study reveals significant differences in phenotypes for these LOF alleles. From our data, we have identified the three putative LOF alleles with the most severe and similar phenotypes propose for two of them (n498n1186 and js125) to be regarded as reference alleles to streamline future research on unc-43 function. This data will help future researchers optimise their research of unc-43 function and determine how to choose a strain/strains to use as a negative control.

genetics↗

bioRxiv2024

Developmental variability in cotton fiber cell wall properties linked to important agronomic traits

The economic value of cotton is based on its long, thin, strong, and twisted trichoblasts that emerge from the ovule epidermis. The mature dried fiber cell reflects the outcome of a rapid tapering of the nascent trichoblast, weeks of polarized diffuse growth, followed by a transition to persistent secondary cell wall synthesis. Highly conserved and dynamic microtubule and cellulose microfibril-based anisotropic growth control modules are central to all of these phases. In this paper, we developed novel quantitative phenotyping and computational modeling pipelines to analyze fiber growth behaviors at a daily resolution. We uncovered unexpected variability in growth rate, cell wall properties, and cell geometry across a critical window of fiber development. Finite element computational modeling of fiber growth was used to analyze the instability of cell diameter control and predict how spatial gradients of fiber and matrix material properties can interact to dictate the patterns of shape change. As an initial step toward gaining insight into the molecular orchestration of cellulose biosynthesis, expression profiles of a broad set of relevant genes were quantified across the same developmental timeline and correlated with fiber phenotypes. This analysis identified specific candidate genes that may serve as targets for fiber quality improvement.

plant biology↗

bioRxiv2023

Preserving condensate structure and composition by lowering sequence complexity

Biological condensates play a vital role in organizing cellular chemistry. They selectively partition biomolecules, preventing unwanted cross-talk and buffering against chemical noise. Intrinsically disordered proteins (IDPs) serve as primary components of these condensates due to their flexibility and ability to engage in multivalent, nonspecific interactions, leading to spontaneous aggregation. Theoretical advancements are critical at connecting IDP sequences with condensate emergent properties to establish the so-called molecular grammar. We proposed an extension to the stickers and spacers model, incorporating non-specific pairwise interactions between spacers alongside specific interactions among stickers. Our investigation revealed that while spacer interactions contribute to phase separation and co-condensation, their non-specific nature leads to disorganized condensates. Specific sticker-sticker interactions drive the formation of condensates with well-defined structures and molecular composition. We discussed how evolutionary pressures might emerge to affect these interactions, leading to the prevalence of low complexity domains in IDP sequences. These domains suppress spurious interactions and facilitate the formation of biologically meaningful condensates. Significance StatementBiomolecular condensates serve as pivotal mechanisms in cellular organization, often characterized by an abundance of intrinsically disordered proteins (IDPs) that undergo frequent mutations in their sequences. Despite this, IDP sequences exhibit non-random patterns, yet the precise relationship between these sequences and the emergent properties of condensates remains unclear. To address this gap, we propose a molecular theory that delineates how various sequence features of IDPs contribute to the organization and composition of condensates. This theory not only sheds light on the evolution of IDPs but also elucidates the emergence of non-random sequence patterns as essential elements for the formation of functional condensates. Correspondingly, we posit that the prevalence of low-complexity regions within IDPs is a result of evolutionary selection.

biophysics↗

bioRxiv2023

Planar Amorphous Silicon Carbide Microelectrode Arrays for Chronic Recording in Rat Motor Cortex

Chronic implantation of intracortical microelectrode arrays (MEAs) capable of recording from individual neurons can be used for the development of brain-machine interfaces. However, these devices show reduced recording capabilities under chronic conditions due, at least in part, to the brains foreign body response. This creates a need for MEAs that can minimize the foreign body response to enable long-term recording. A potential approach to reduce the foreign body response is the use of ultrathin MEAs. Here, we fabricated ultrathin (cross-sectional area: 160 {micro}m2) amorphous silicon carbide (a-SiC) MEAs with sixteen electrode channels and implanted them into the motor cortex of seven female Sprague-Dawley rats. A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication techniques. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized in vitro pre-implantation and in vivo using electrochemical impedance spectroscopy and cyclic voltammetry at 50 mV/s and 50,000 mV/s. Neural recordings were analyzed for single unit activity. At the end of the study, animals were sacrificed for immunohistochemistry analysis. We observed statistically significant, but small, increases in 1 and 30 kHz impedance values and 50,000 mV/s charge storage capacity over the 16-week implantation period. Slow sweep 50 mV/s CV and 1 Hz impedance did not significantly change over time. Impedance values increased from 11.6 M{Omega} to 13.5 M{Omega} at 1 Hz, 1.2 M{Omega} to 2.9 M{Omega} at 1 kHz, and 0.11 M{Omega} to 0.13 M{Omega} at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s were 58.1 mC/cm2 on week 1 and 55.9 mC/cm2 on week 16, and at 50,000 mV/s were 4.27 mC/cm2 on week 1 and 5.93 mC/cm2 on week 16. Devices were able to record neural activity from 92% of all active channels at the beginning of the study, At the study endpoint, a-SiC devices were still recording single-unit activity on 51% of electrochemically active electrode channels. In addition, we observed that the signal-to-noise ratio experienced a small decline of only -0.19 per week. We also classified the units as fast and slow spiking based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow spiking units declined at a similar rate. Furthermore, immunohistochemistry showed minimal foreign body response to the a-SiC devices, as highlighted by statistically insignificant differences in activated glial cells between implanted brains slices and contralateral sham slices, as evidenced by GFAP staining. NeuN staining revealed the presence of neural cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results support the use of ultrathin a-SiC MEAs for long-term implantation and use in brain-machine interfaces.

bioengineering↗

bioRxiv2023

Outcome devaluation by sensory-specific satiety alters Pavlovian-conditioned behavior in male and female rats

Goal-directed behavior relies on accurate mental representations of the value of expected outcomes. Disruptions to this process are a central feature of several neuropsychiatric disorders, including addiction. Goal-directed behavior is most frequently studied using instrumental paradigms paired with outcome devaluation, but cue-evoked behaviors in Pavlovian settings can also be goal-directed and therefore sensitive to changes in outcome value. Emerging literature suggests that male and female rats may differ in the degree to which their Pavlovian-conditioned responses are goal-directed, but interpretation of these findings is complicated by the tendency of female and male rats to engage in distinct types of Pavlovian responses when trained with localizable cues. Here, we used outcome devaluation via sensory-specific satiety to assess the behavioral responses in male and female Long Evans rats trained to respond to an auditory CS (conditioned stimulus) in a Pavlovian-conditioning paradigm. We found that satiety-induced devaluation led to a decrease in behavioral responding to the reward-predictive CS, with males showing an effect on both port entry latency and probability and females showing an effect only on port entry probability. Overall, our results suggest that outcome devaluation affects Pavlovian-conditioned responses in both male and female rats, but that females may be less sensitive to outcome devaluation.

neuroscience↗

bioRxiv2023

ATF4 Expression in Thermogenic Adipocytes is Required for Cold-Induced Thermogenesis in Mice via FGF21-Independent Mechanisms

In brown adipose tissue (BAT), short-term cold exposure induces the activating transcription factor 4 (ATF4), and its downstream target fibroblast growth factor 21 (FGF21). Induction of ATF4 in BAT in response to mitochondrial stress is required for thermoregulation, partially via upregulation of FGF21. In the present study, we tested the hypothesis that Atf4 and Fgf21 induction in BAT are both required for BAT thermogenesis by generating mice selectively lacking either Atf4 (ATF4 BKO) or Fgf21 (FGF21 BKO) in UCP1-expressing adipocytes. After 3 days of cold exposure, core body temperature was significantly reduced in ad-libitum-fed ATF4 BKO mice, which correlated with Fgf21 downregulation in brown and beige adipocytes, and impaired browning of white adipose tissue (WAT). Conversely, despite having reduced browning, FGF21 BKO mice had preserved core body temperature after cold exposure. Mechanistically, ATF4, but not FGF21, regulates amino acid import and metabolism in response to cold, likely contributing to BAT thermogenic capacity under ad libitum-fed conditions. Importantly, under fasting conditions, both ATF4 and FGF21 were required for thermogenesis in cold-exposed mice. Thus, ATF4 regulates BAT thermogenesis by activating amino acid metabolism in BAT in a FGF21-independent manner. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/531964v2_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@1d2c3fdorg.highwire.dtl.DTLVardef@414f5forg.highwire.dtl.DTLVardef@1c1fa9eorg.highwire.dtl.DTLVardef@2cc815_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2022

Coupling chromatin folding with histone modifications reveals dynamical asymmetry in the epigenetic landscape

Genomic regions adopt heritable epigenetic states with unique histone modifications, resulting in bistable gene expression without changes to the underlying DNA sequence. The significance of chromatin conformational dynamics to epigenetic stability is not well understood. We introduce a kinetic model to simulate the dynamic fluctuation of histone modifications. The model explicitly incorporates the impact of chemical modifications on chromatin stability as well as the contribution of chromatin contacts to the cooperativity of chemical reactions. Leveraging the models computational efficiency, we study the disparate time scales of chromatin relaxation and epigenetic spread to account for the recent discovery of both liquid and gel-like properties of chromatin. Strikingly different results were obtained for the steady state and kinetic behavior of histone modification patterns in fast and slow chromatin structural relaxation regimes. Our study suggests that the timescale of chromatin conformational dynamics maybe an important axis that biology fine tunes to regulate epigenetic stability.

biophysics↗

bioRxiv2022

Human Digital Twin: Automated Cell Type Distance Computation and 3D Atlas Construction in Multiplexed Skin Biopsies

Mapping the human body at single cell resolution in three-dimensions (3D) is an important step toward a "digital twin" model that captures important structure and dynamics of cell-cell interactions. Current 3D imaging methods suffer from low resolution and are limited in their ability to distinguish cell types and their spatial relationships. We present a novel 3D workflow: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis) that generates a 3D map of cells from multiplexed images and calculates cell type distance from endothelial cells and other features of interest. We applied this workflow to multiplexed data from sequential skin sections from younger and older donors (n=10; 33-72 years) with biopsies from ten anatomical regions with different sun exposure effects (mild, moderate-marked). Up to 26 sequential sections from each sample underwent multiplexed imaging with 18 biomarkers covering 12 cell types (keratinocytes (granular, spinous, basal), epithelial and myoepithelial cells, fibroblasts, macrophages, T helpers, T killers, T regs, neurons and endothelial cells, markers of DNA damage and repair (p53, DDB2) and cell proliferation (Ki67). Following cell classification, the tissue and classified cells were reconstructed into 3D volumes. A significant inverse correlation between DDB2 positive cells and age was found (corr= -0.78, adj. p=0.047). This suggests reduced capacity for repair in non-cancer older sun-exposed individuals. While absolute immune cell count did not differ by age or sun exposure, the ratio of T Helper/T Killer cells was positively correlated with age (corr=0.82, adj. p=0.048) This is the first such 3D study in skin and paves the way for cataloging more cell types and spatial relationships in aging and disease in skin and other organs.

cell biology↗

bioRxiv2021

Pre-existing chromatin accessibility and gene expression differences among naïve CD4+ T cells influence effector potential

CD4+ T cells have a remarkable potential to differentiate into diverse effector lineages following activation. Here, we probed the heterogeneity present among naive CD4+ T cells before encountering their cognate antigen to ask whether their effector potential is modulated by pre-existing transcriptional and epigenetic differences. Using single-cell RNA sequencing, we showed that key drivers of variability are genes involved in T cell receptor (TCR) signaling. Using CD5 expression as a read-out of the strength of tonic TCR interactions with self-peptide MHC, and sorting on the ends of this self-reactivity spectrum, we find that pre-existing transcriptional differences among naive CD4+ T cells impact follicular helper cell (TFH) versus non-TFH effector lineage choice. Moreover, our data implicate TCR signal strength during thymic development in establishing differences in naive CD4 T cell chromatin landscapes that ultimately shape their effector potential.

immunology↗

bioRxiv2021

An atlas of inter- and intra-tumor heterogeneityof apoptosis competency in colorectal cancertissue at single cell resolution

Cancer cells ability to inhibit apoptosis is key to malignant transformation and limits response to therapy. Here, we performed multiplexed immunofluorescence analysis on tissue microarrays with 373 cores from 168 patients, segmentation of 2.4 million individual cells and quantification of 20 cell lineage and apoptosis proteins. Ordinary differential equation-based modelling of apoptosis sensitivity at single cell resolution was conducted and an atlas of inter- and intra-tumor heterogeneity in apoptosis susceptibility generated. We identified an enrichment for BCL2 in immune, and BAK, SMAC and XIAP in cancer cells. ODE-based modelling at single cell resolution identified an enhanced sensitivity of cancer cells to mitochondrial permeabilization and executioner caspase activation compared to immune and stromal cells, with significant inter- and intra-tumor heterogeneity. However, we did not find increased spatial heterogeneity of apoptosis signaling in cancer cells, suggesting that such heterogeneity is an intrinsic, non-genomic property not increased by the process of malignant transformation.

cancer biology↗

bioRxiv2021

Stratification Of Chemotherapy-Treated Stage III Colorectal Cancer Patients Using Multiplexed Imaging And Single Cell Analysis Of T Cell Populations

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Predictive biomarkers for identification of patients with increased risk for disease recurrence are currently lacking, with progress in biomarker discovery hindered by the diseases inherent heterogeneity. The immune profile of colorectal tumors has previously been found to have prognostic value. The aims of this study were to evaluate immune signatures in the tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single cell analysis technology (Cell DIVE). Tissue microarrays (TMAs) with up to three 1mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin chemotherapy. Single sections underwent multilplexed immunofluorescence with Cy3- and Cy5-conjugated antibodies for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase and S6). We applied a probabilistic multi-class, multi-label classification algorithm based on multi-parametric models to build statistical models of protein expression to classify immune cells. Expert annotations of immune cell markers were made on a range of images, and Support Vector Machines (SVM) were used to derive a statistical model for cell classification. Images were also manually scored independently by a Pathologist as high, moderate or low, for stromal and total immune cell content. Excellent agreement was found between manual and total automated scores (p<0.0001). Higher levels of multi-marker classified regulatory T cells (CD3+CD4+FOXP3+PD1-) were significantly associated with disease-free survival (DFS) and overall-survival (OS) (p=0.049 and 0.032), compared to FOXP3 alone. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cells with greater potential for predicting patient outcomes.

cancer biology↗

bioRxiv2021

Rapid adaptation and remote delivery of undergraduate research training during the COVID 19 Pandemic

COVID-19 continues to alter daily life around the globe. Education is particularly affected by shifts to distance learning. This change has poignant effects on all aspects of academic life, including the consequence of increased mental stress reported specifically for students. COVID-19 cancellations of many summer fellowships and internships for undergraduates across the country increased students uncertainty about their educational opportunities and careers. When the pandemic necessitated elimination of on-campus programming at Mayo Clinic, a new program was developed for remote delivery. Summer Foundations in Research (SFIR) was drafted around 4 aims: 1) support the academic trajectory gap in research science created by COVID-19; 2) build sustainable scientific relationships with mentors, peers, and the community; 3) create opportunities for participants to share and address concerns with their own experiences in the pandemic; and 4) provide support for individual wellbeing. SFIR included research training, but also training in communication through generative Dialogue and resilience through Amit Soods SMART program. 170 participants were followed for outcomes in these spaces. Knowledge of and interest in careers involving biomedical research rose significantly following SFIR. Participants mean confidence levels in 12 Key areas of research rose between 0.08 to 1.32 points on a 7-point scale. The strongest gains in mean confidence levels were seen in designing a study and collaborating with others. SFIR participants demonstrated gains in perceived happiness, and measured resilience and a reduction in stress. Participants qualitative responses indicated exceptionally positive mentor relationships and specific benefit of both the SMART program and Dialogue.

scientific communication and education↗