Securing cloud data using secret key 4 optimization algorithm (SK4OA) with a non-linearity run time trend.

Cloud computing alludes to the on-demand availability of personal computer framework resources, primarily information storage and processing power, without the customer's direct personal involvement. Cloud computing has developed dramatically among many organizations due to its benefits such as cost savings, resource pooling, broad network access, and ease of management; nonetheless, security has been a major concern. Researchers have proposed several cryptographic methods to offer cloud data security; however, their execution times are linear and longer. A Security Key 4 Optimization Algorithm (SK4OA) with a non-linear run time is proposed in this paper. The secret key of SK4OA determines the run time rather than the size of the data as such is able to transmit large volumes of data with minimal bandwidth and able to resist security attacks like brute force since its execution timings are unpredictable. A data set from Kaggle was used to determine the algorithm's mean and standard deviation after thirty (30) times of execution. Data sizes of 3KB, 5KB, 8KB, 12KB, and 16 KB were used in this study. There was an empirical analysis done against RC4, Salsa20, and Chacha20 based on encryption time, decryption time, throughput and memory utilization. The analysis showed that SK4OA generated lowest mean non-linear run time of 5.545±2.785 when 16KB of data was executed. Additionally, SK4OA's standard deviation was greater, indicating that the observed data varied far from the mean. However, RC4, Salsa20, and Chacha20 showed smaller standard deviations making them more clustered around the mean resulting in predictable run times.

An pair of an atypical NLR encoding genes confer Asian soybean rust resistance in soybean.

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is a devastating disease that is present in all major soybean-producing regions. The limited availability of resistant germplasm has resulted in a scarcity of commercial soybean cultivars that are resistant to the disease. To date, only the Chinese soybean landrace SX6907 has demonstrated an immune response to ASR. In this study, we present the isolation and characterization of Rpp6907-7 and Rpp6907-4, a gene pair that confer broad-spectrum resistance to ASR. Rpp6907-7 and Rpp6907-4 encode atypic nucleotide-binding leucine-rich repeat (NLR) proteins that are found to be required for NLR-mediated immunity. Genetic analysis shows that only Rpp6907-7 confers resistance, while Rpp6907-4 regulates Rpp6907-7 signaling activity by acting as a repressor in the absence of recognized effectors. Our work highlights the potential value of using Rpp6907 in developing resistant soybean cultivars.

Morphological profiling in human neural progenitor cells classifies hits in a pilot drug screen for Alzheimer's disease.

Alzheimer's disease accounts for 60-70% of dementia cases. Current treatments are inadequate and there is a need to develop new approaches to drug discovery. Recently, in cancer, morphological profiling has been used in combination with high-throughput screening of small-molecule libraries in human cells in vitro. To test feasibility of this approach for Alzheimer's disease, we developed a cell morphology-based drug screen centred on the risk gene, SORL1 (which encodes the protein SORLA). Increased Alzheimer's disease risk has been repeatedly linked to variants in SORL1, particularly those conferring loss or decreased expression of SORLA, and lower SORL1 levels are observed in post-mortem brain samples from individuals with Alzheimer's disease. Consistent with its role in the endolysosomal pathway, SORL1 deletion is associated with enlarged endosomes in neural progenitor cells and neurons. We, therefore, hypothesized that multi-parametric, image-based cell phenotyping would identify features characteristic of SORL1 deletion. An automated morphological profiling method (Cell Painting) was adapted to neural progenitor cells and used to determine the phenotypic response of SORL1-/- neural progenitor cells to treatment with compounds from a small internationally approved drug library (TargetMol, 330 compounds). We detected distinct phenotypic signatures for SORL1-/- neural progenitor cells compared to isogenic wild-type controls. Furthermore, we identified 16 compounds (representing 14 drugs) that reversed the mutant morphological signatures in neural progenitor cells derived from three SORL1-/- induced pluripotent stem cell sub-clones. Network pharmacology analysis revealed the 16 compounds belonged to five mechanistic groups: 20S proteasome, aldehyde dehydrogenase, topoisomerase I and II, and DNA synthesis inhibitors. Enrichment analysis identified DNA synthesis/damage/repair, proteases/proteasome and metabolism as key pathways/biological processes. Prediction of novel targets revealed enrichment in pathways associated with neural cell function and Alzheimer's disease. Overall, this work suggests that (i) a quantitative phenotypic metric can distinguish induced pluripotent stem cell-derived SORL1-/- neural progenitor cells from isogenic wild-type controls and (ii) phenotypic screening combined with multi-parametric high-content image analysis is a viable option for drug repurposing and discovery in this human neural cell model of Alzheimer's disease.

High throughput screening identifies dasatinib as synergistic with trametinib in low grade serous ovarian carcinoma.

BACKGROUND: Low grade serous ovarian carcinoma (LGSOC) is a distinct histotype of ovarian cancer characterised high levels of intrinsic chemoresistance, highlighting the urgent need for new treatments. High throughput screening in clinically-informative cell-based models represents an attractive strategy for identifying candidate treatment options for prioritisation in clinical studies. METHODS: We performed a high throughput drug screen of 1610 agents across a panel of 6 LGSOC cell lines (3 RAS/RAF-mutant, 3 RAS/RAF-wildtype) to identify novel candidate therapeutic approaches. Validation comprised dose-response analysis across 9 LGSOC models and 5 high grade serous comparator lines. RESULTS: 16 hits of 1610 screened compounds were prioritised for validation based on >50% reduction in nuclei counts in over half of screened cell lines at 1000 nM concentration. 11 compounds passed validation, and the four agents of greatest interest (dasatinib, tyrosine kinase inhibitor; disulfiram, aldehyde dehydrogenase inhibitor; carfilzomib, proteasome inhibitor; romidepsin, histone deacetylase inhibitor) underwent synergy profiling with the recently approved MEK inhibitor trametinib. Disulfiram demonstrated excellent selectivity for LGSOC versus high grade serous ovarian carcinoma comparator lines (P = 0.003 for IC50 comparison), while the tyrosine kinase inhibitor dasatinib demonstrated favourable synergy with trametinib across multiple LGSOC models (maximum zero interaction potency synergy score 46.9). The novel, highly selective Src family kinase (SFK) inhibitor NXP900 demonstrated a similar trametinib synergy profile to dasatinib, suggesting that SFK inhibition is the likely driver of synergy. CONCLUSION: Dasatinib and other SFK inhibitors represent novel candidate treatments for LGSOC and demonstrate synergy with trametinib. Disulfiram represents an additional treatment strategy worthy of investigation.

The application of the "inverse problem" method for constructing confining potentials that make N-soliton waveforms exact solutions in the Gross-Pitaevskii equation.

In this work, we discuss an application of the "inverse problem" method to find the external trapping potential, which has particular N trapped soliton-like solutions of the Gross-Pitaevskii equation (GPE) also known as the cubic nonlinear Schrödinger equation (NLSE). This inverse method assumes particular forms for the trapped soliton wave function, which then determines the (unique) external (confining) potential. The latter renders these assumed waveforms exact solutions of the GPE (NLSE) for both attractive (g<0) and repulsive (g>0) self-interactions. For both signs of g, we discuss the stability with respect to self-similar deformations and translations. For g<0, a critical mass Mc or equivalently the number of particles for instabilities to arise can often be found analytically. On the other hand, for the case with g>0 corresponding to repulsive self-interactions which is often discussed in the atomic physics realm of Bose-Einstein condensates, the bound solutions are found to be always stable. For g<0, we also determine the critical mass numerically by using linear stability or Bogoliubov-de Gennes analysis, and compare these results with our analytic estimates. Various analytic forms for the trapped N-soliton solutions in one, two, and three spatial dimensions are discussed, including sums of Gaussians or higher-order eigenfunctions of the harmonic oscillator Hamiltonian.

Removal of Spinal Instrumentation Is Not Required to Successfully Treat Postoperative Wound Infections in Most Cases.

INTRODUCTION: Controversy exists regarding whether spinal implants need to be removed to treat postoperative deep wound infections (DWIs). This retrospective study aimed to determine whether the removal or retention of implants impacts the successful treatment of a DWI after spine surgery. METHODS: Postoperative spine surgery patients presenting with signs of infection who underwent irrigation and debridement (I&D) at Twin Cities Spine Surgeons at Abbott Northwestern Hospital, Minnesota, USA, were studied. First, the persistence of infection when implants were retained or removed was assessed. Second, we analyzed the persistence of infection with respect to the number of I&D, the use of vacuum-assisted closure (VAC) treatment, pseudoarthrosis status, and functional outcomes. RESULTS: One hundred thirty-five patients were included. Treatment of infection with retention of implants occurred in 64% (87/135); of these, 7% (6/87) had a persistent infection. Of patients with implant removal (36%, 48/135), 6% (3/48) had a persistent infection. Thus, we observed no difference between treatment with implants present compared to implants removed (p = 1.0). Fifty of the 135 patients (37%) received I&D and primary wound closure, and 85 (63%) patients received I&D and VAC treatment. There was no statistical difference between primary wound closure and VAC treatment (p = 0.15) with respect to persistence. Repeat I&D with VAC (three or more times) had a significantly lower rate of recurrence than those with two I&Ds. Pseudoarthrosis and persistent infection were unrelated. At minimum one-year follow-up, achieving a minimum clinically important difference in functional outcome was independent of persistent infection status. CONCLUSION: Persistent infection was unrelated to the retention of implants. When VAC treatment was deemed necessary, more than two I&Ds resulted in a significantly better cure for infection. Those with a persistent infection were no more likely to exhibit pseudoarthrosis than those with no persistent infection. All patients showed improvement in functional outcomes at minimum one-year follow-up.

Anti-obesity and metabolic benefits of metformin: Comparison of different delivery routes.

Obesity is a severe public health problem. Healthy lifestyle interventions are commonly recommended for fighting obesity. But they are hard to follow and have low efficacy. Pharmacotherapy and surgery are of high efficacy but are beset with side effects. Browning subcutaneous white adipose tissue (WAT) is a practical and efficient approach for combating obesity. Metformin, a commonly used FDA-approved antidiabetic drug, is potent to induce browning of WAT through phosphorylation and activation of AMP-activated protein kinase. However, oral administration of metformin has low oral bioavailability, fast renal clearance, and low target specificity that limit metformin's application in browning WAT. Local and transdermal delivery of metformin directly to subcutaneous WAT using injection or microneedle (MN) in combination with iontophoresis (INT) may solve these problems. In this paper, we administered metformin to C57BL/6J obese mice using the following three routes: transdermal delivery (MN and INT), local injection into inguinal WAT (IgWAT, a type of subcutaneous WAT in mice), and oral gavage. The anti-obesity and metabolic effects of metformin via these delivery routes were determined and compared. As compared to local IgWAT injection and oral gavage delivery, transdermal delivery of metformin using MN and INT resulted in 9% lower body weight and 7% decrease in body fat% accompanied by improved energy metabolism and decreased inflammation through browning IgWAT in obese C57BL/6J mice. Transdermal delivery of metformin using MN and INT is an effective approach in browning subcutaneous WAT for combating obesity and improving metabolic health.

Moderate scoliosis continues to progress at 30-year follow-up: a call for concern?

PURPOSE: This natural history study reports long-term radiographic and clinical outcomes of patients with diagnosis of AIS with curves between 30° and 50°. Our purpose was to determine if any intervention in the natural history is warranted. METHODS: This was a longitudinal descriptive study at a single institution. We reviewed patient factors, radiographic parameters, and patient-reported outcomes at 20- and 30-year follow-up. RESULTS: A total of 31 patients were included. At skeletal maturity (which was the initial point of measurement), the median age was 17 years (range 12-21), the thoracic Cobb angle was 35° ± 5° (maximum-minimum 27°-47°), and the lumbar Cobb angle was 33° ± 7° (maximum-minimum 18°-45°). The median final follow-up was 35 years (median age 52, range 32-61) when the thoracic Cobb angle was 47° ± 12° (maximum-minimum 31°-74°) and the lumbar Cobb angle was 40° ± 17° (maximum-minimum 19°-69°). At final follow-up, 9 (29%) patients had a structural curve > 50°. Ten (32%) patients had a curve from 40° to 49° and 11 (35%) patients had a curve < 40°. The thoracic Cobb angle had progressed from < 40° to > 50° in 5 patients. Thoracolumbar and lumbar Cobb angles progressed from < 40° to greater than > 50° in 1 and 3 patients, respectively. Few patients had functional limitations according to Roland-Morris, Oswestry, and SF36 scores. Pain scores were minimal at final follow-up. CONCLUSION: All AIS curves between 30° and 50° at skeletal maturity tend to progress. Thoracic curves progress more than lumbar curves during the first 20 years and then progression slows down. The opposite happens with lumbar curves. Therefore, the rate of progression decreases with thoracic curves and increases with lumbar curves. Nevertheless, few patients have functional limitations. Further follow-up is necessary to define the true long-term outcome of moderate curves at maturity.

Molecular determinants of antagonist interactions with chemokine receptors CCR2 and CCR5.

By driving monocyte chemotaxis, the chemokine receptor CCR2 shapes inflammatory responses and the formation of tumor microenvironments. This makes it a promising target in inflammation and immuno-oncology; however, despite extensive efforts, there are no FDA-approved CCR2-targeting therapeutics. Cited challenges include the redundancy of the chemokine system, suboptimal properties of compound candidates, and species differences that confound the translation of results from animals to humans. Structure-based drug design can rationalize and accelerate the discovery and optimization of CCR2 antagonists to address these challenges. The prerequisites for such efforts include an atomic-level understanding of the molecular determinants of action of existing antagonists. In this study, using molecular docking and artificial-intelligence-powered compound library screening, we uncover the structural principles of small molecule antagonism and selectivity towards CCR2 and its sister receptor CCR5. CCR2 orthosteric inhibitors are shown to universally occupy an inactive-state-specific tunnel between receptor helices 1 and 7; we also discover an unexpected role for an extra-helical groove accessible through this tunnel, suggesting its potential as a new targetable interface for CCR2 and CCR5 modulation. By contrast, only shape complementarity and limited helix 8 hydrogen bonding govern the binding of various chemotypes of allosteric antagonists. CCR2 residues S1012.63 and V2446.36 are implicated as determinants of CCR2/CCR5 and human/mouse orthosteric and allosteric antagonist selectivity, respectively, and the role of S1012.63 is corroborated through experimental gain-of-function mutagenesis. We establish a critical role of induced fit in antagonist recognition, reveal strong chemotype selectivity of existing structures, and demonstrate the high predictive potential of a new deep-learning-based compound scoring function. Finally, this study expands the available CCR2 structural landscape with computationally generated chemotype-specific models well-suited for structure-based antagonist design.

Ensuring privacy and confidentiality of cloud data: A comparative analysis of diverse cryptographic solutions based on run time trend.

The cloud is becoming a hub for sensitive data as technology develops, making it increasingly vulnerable, especially as more people get access. Data should be protected and secured since a larger number of individuals utilize the cloud for a variety of purposes. Confidentiality and privacy of data is attained through the use of cryptographic techniques. While each cryptographic method completes the same objective, they all employ different amounts of CPU, memory, throughput, encryption, and decryption times. It is necessary to contrast the various possibilities in order to choose the optimal cryptographic algorithm. An integrated data size of 5n*102 (KB (∈ 1,2,4,10,20,40) is evaluated in this article. Performance metrics including run time, memory use, and throughput time were used in the comparison. To determine the effectiveness of each cryptographic technique, the data sizes were run fifteen (15) times, and the mean simulation results were then reported. In terms of run time trend, NCS is superior to the other algorithms according to Friedman's test and Bonferroni's Post Hoc test.

A multiscale predictive digital twin for neurocardiac modulation.

Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the ß-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.

Uniform-density Bose-Einstein condensates of the Gross-Pitaevskii equation found by solving the inverse problem for the confining potential.

In this work, we study the existence and stability of constant density (flat-top) solutions to the Gross-Pitaevskii equation (GPE) in confining potentials. These are constructed by using the "inverse problem" approach which corresponds to the identification of confining potentials that make flat-top waveforms exact solutions to the GPE. In the one-dimensional case, the exact solution is the sum of stationary kink and antikink solutions, and in the overlapping region, the density is constant. In higher spatial dimensions, the exact solutions are generalizations of this wave function. In the absence of self-interactions, the confining potential is similar to a smoothed-out finite square well with minima also at the edges. When self-interactions are added, terms proportional to ±gψ^{*}ψ and ±gM with M representing the mass or number of particles in Bose-Einstein condensates get added to the confining potential and total energy, respectively. In the realm of stability analysis, we find (linearly) stable solutions in the case with repulsive self-interactions which also are stable to self-similar deformations. For attractive interactions, however, the minima at the edges of the potential get deeper and a barrier in the center forms as we increase the norm. This leads to instabilities at a critical value of M. Comparing the stability criteria from Derrick's theorem with Bogoliubov-de Gennes (BdG) analysis stability results, we find that both predict stability for repulsive self-interactions and instability at a critical mass M for attractive interactions. However, the numerical analysis gives a much lower critical mass. This is due to the emergence of symmetry-breaking instabilities that were detected by the BdG analysis and violate the symmetry x→-x assumed by Derrick's theorem.

Chemogenomic library design strategies for precision oncology, applied to phenotypic profiling of glioblastoma patient cells.

Designing a targeted screening library of bioactive small molecules is a challenging task since most compounds modulate their effects through multiple protein targets with varying degrees of potency and selectivity. We implemented analytic procedures for designing anticancer compound libraries adjusted for library size, cellular activity, chemical diversity and availability, and target selectivity. The resulting compound collections cover a wide range of protein targets and biological pathways implicated in various cancers, making them widely applicable to precision oncology. We characterized the compound and target spaces of the virtual libraries, in comparison with a minimal screening library of 1,211 compounds for targeting 1,386 anticancer proteins. In a pilot screening study, we identified patient-specific vulnerabilities by imaging glioma stem cells from patients with glioblastoma (GBM), using a physical library of 789 compounds that cover 1,320 of the anticancer targets. The cell survival profiling revealed highly heterogeneous phenotypic responses across the patients and GBM subtypes.

Discovery of senolytics using machine learning.

Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics are known due to the lack of well-characterised molecular targets. Here, we report the discovery of three senolytics using cost-effective machine learning algorithms trained solely on published data. We computationally screened various chemical libraries and validated the senolytic action of ginkgetin, periplocin and oleandrin in human cell lines under various modalities of senescence. The compounds have potency comparable to known senolytics, and we show that oleandrin has improved potency over its target as compared to best-in-class alternatives. Our approach led to several hundred-fold reduction in drug screening costs and demonstrates that artificial intelligence can take maximum advantage of small and heterogeneous drug screening data, paving the way for new open science approaches to early-stage drug discovery.

Effects of a Theory-Based, Multicomponent eHealth Intervention for Obesity Prevention in Young Children from Low-Income Families: A Pilot Randomized Controlled Study.

The purpose of this study was to evaluate a theory-based, multicomponent eHealth intervention aimed at improving child health behaviors and parental psychosocial attributes and feeding practices. A pilot randomized controlled trial was conducted among 73 parents with children (1-3 years). Intervention group participants (IG, n = 37) received theory-based educational videos, cooking tutorials, and text messages with key information for a total of 8 weeks. Control group participants (CG, n = 36) received a booklet about general nutrition recommendations for children. A parent-administered questionnaire was used for data collection at baseline and post-intervention. Linear models were performed using R version 4.1.1. for data analysis. Children in the IG significantly increased their daily intake of fruit (ΔΔ = 0.89 servings, p = 0.00057) and vegetables (ΔΔ = 0.60 servings, p = 0.0037) and decreased use of screen time (ΔΔ = -33.87 min, p = 0.026), compared to the CG. Parents in the IG improved significantly more than the CG in self-efficacy (p = 0.0068) and comprehensive feeding practices (p = 0.0069). There were no significant differences between the study groups for changes in child outcomes, such as physical activity and sedentary behaviors, and parental nutrition knowledge and attitudes.

Actin's C-terminus coordinates actin structural changes and functions.

Actin is essential to eukaryotic cellular processes. Actin's C-terminus appears to play a direct role in modulating actin's structure and properties, facilitating the binding and function of actin-binding proteins (ABPs). The structural and functional characterization of filamentous actin's C-terminus has been impeded by its inherent flexibility, as well as actin's resistance to crystallization for x-ray diffraction and the historical resolution constraints associated with electron microscopy. Many biochemical studies have established that actin's C-terminus must retain its flexibility and structural integrity to modulate actin's structure and functions. For example, C-terminal structural changes are known to affect nucleotide binding and exchange, as well as propagate actin structural changes throughout extensive allosteric networks, facilitating the binding and function of ABPs. Advances in electron microscopy have resulted in high-resolution structures of filamentous actin, providing insights into subtle structural changes that are mediated by actin's C-terminus. Here, we review existing knowledge establishing the importance of actin's C-terminus within actin structural changes and functions and discuss how modern structural characterization techniques provide the tools to understand the role of actin's C-terminus in cellular processes.

CRISPR/LbCas12a-Mediated Genome Editing in Soybean.

Currently methods for generating soybean edited lines are time-consuming, inefficient, and limited to certain genotypes. Here we describe a fast and highly efficient genome editing method based on CRISPR-Cas12a nuclease system in soybean. The method uses Agrobacterium-mediated transformation to deliver editing constructs and uses aadA or ALS genes as selectable marker. It only takes about 45 days to obtain greenhouse-ready edited plants at higher than 30% transformation efficiency and 50% editing rate. The method is applicable to other selectable markers including EPSPS and has low transgene chimera rate. The method is also genotype-flexible and has been applied to genome editing of several elite soybean varieties.

11ß-HSD1 inhibition does not affect murine tumour angiogenesis but may exert a selective effect on tumour growth by modulating inflammation and fibrosis.

Glucocorticoids inhibit angiogenesis by activating the glucocorticoid receptor. Inhibition of the glucocorticoid-activating enzyme 11ß-hydroxysteroid dehydrogenase type 1 (11ß-HSD1) reduces tissue-specific glucocorticoid action and promotes angiogenesis in murine models of myocardial infarction. Angiogenesis is important in the growth of some solid tumours. This study used murine models of squamous cell carcinoma (SCC) and pancreatic ductal adenocarcinoma (PDAC) to test the hypothesis that 11ß-HSD1 inhibition promotes angiogenesis and subsequent tumour growth. SCC or PDAC cells were injected into female FVB/N or C57BL6/J mice fed either standard diet, or diet containing the 11ß-HSD1 inhibitor UE2316. SCC tumours grew more rapidly in UE2316-treated mice, reaching a larger (P<0.01) final volume (0.158 ± 0.037 cm3) than in control mice (0.051 ± 0.007 cm3). However, PDAC tumour growth was unaffected. Immunofluorescent analysis of SCC tumours did not show differences in vessel density (CD31/alpha-smooth muscle actin) or cell proliferation (Ki67) after 11ß-HSD1 inhibition, and immunohistochemistry of SCC tumours did not show changes in inflammatory cell (CD3- or F4/80-positive) infiltration. In culture, the growth/viability (assessed by live cell imaging) of SCC cells was not affected by UE2316 or corticosterone. Second Harmonic Generation microscopy showed that UE2316 reduced Type I collagen (P<0.001), whilst RNA-sequencing revealed that multiple factors involved in the innate immune/inflammatory response were reduced in UE2316-treated SCC tumours. 11ß-HSD1 inhibition increases SCC tumour growth, likely via suppression of inflammatory/immune cell signalling and extracellular matrix deposition, but does not promote tumour angiogenesis or growth of all solid tumours.