Mapping systemic lupus erythematosus heterogeneity at the single-cell level.

Patients with systemic lupus erythematosus (SLE) display a complex blood transcriptome whose cellular origin is poorly resolved. Using single-cell RNA sequencing, we profiled ~276,000 peripheral blood mononuclear cells from 33 children with SLE with different degrees of disease activity and 11 matched controls. Increased expression of interferon-stimulated genes (ISGs) distinguished cells from children with SLE from healthy control cells. The high ISG expression signature (ISGhi) derived from a small number of transcriptionally defined subpopulations within major cell types, including monocytes, CD4+ and CD8+ T cells, natural killer cells, conventional and plasmacytoid dendritic cells, B cells and especially plasma cells. Expansion of unique subpopulations enriched in ISGs and/or in monogenic lupus-associated genes classified patients with the highest disease activity. Profiling of ~82,000 single peripheral blood mononuclear cells from adults with SLE confirmed the expansion of similar subpopulations in patients with the highest disease activity. This study lays the groundwork for resolving the origin of the SLE transcriptional signatures and the disease heterogeneity towards precision medicine applications.

Challenging Dogma by Skipping the Emergency Department Thoracotomy: A Propensity Score Matched Analysis of the Trauma Quality Improvement Database.

INTRODUCTION: Survival following emergency department thoracotomy (EDT) for patients in extremis is poor. Whether intervention in the operating room instead of EDT in select patients could lead to improved outcomes is unknown. We hypothesized that patients who underwent intervention in the operating room would have improved outcomes compared to those who underwent EDT. METHODS: We conducted a retrospective review of the Trauma Quality Improvement Program database from 2017 to 2021. All adult patients who underwent EDT, operating room thoracotomy (ORT), or sternotomy as the first form of surgical intervention within 1 h of arrival were included. Of patients without prehospital cardiac arrest, propensity score matching was utilized to create three comparable groups. The primary outcome was survival. Secondary outcomes included time to procedure. RESULTS: There were 1865 EDT patients, 835 ORT patients, and 456 sternotomy patients who met the inclusion criteria. There were 349 EDT, 344 ORT, and 408 sternotomy patients in the matched analysis. On Cox multivariate regression, there was an increased risk of mortality with EDT versus sternotomy (HR 4.64, P < 0.0001), EDT versus ORT (HR 1.65, P < 0.0001), and ORT versus sternotomy (HR 2.81, P < 0.0001). Time to procedure was shorter with EDT versus sternotomy (22 min versus 34 min, P < 0.0001) and versus ORT (22 min versus 37 min, P < 0.0001). CONCLUSIONS: There was an association between sternotomy and ORT versus EDT and improved mortality. In select patients, operative approaches rather than the traditional EDT could be considered.

The COVID-19 pandemic has not changed stage at presentation nor treatment patterns of head and neck cancer: A retrospective cohort study.

OBJECTIVES: To evaluate the impact of the COVID-19 lockdown measures on HNC, by comparing the stage at presentation and treatment of HNC before and after the most severe COVID-19 restrictions. DESIGN: A retrospective cohort study. SETTING: A regional cancer network serving a patient population of 2.4 million. PARTICIPANTS: Newly diagnosed patients with HNC between June and October 2019 (pre-pandemic) and June and October 2021 (post-pandemic). MAIN OUTCOME MEASURES: Symptom duration before diagnosis, stage at diagnosis, patient performance status (PS) and intent of treatment delivered (palliative vs. curative). RESULTS: Five hundred forty-five patients were evaluated-250 in the 2019 and 295 in the 2021 cohort. There were no significant differences in symptom duration between the cohorts (p = .359) or patient PS (p = .821). There were no increased odds of presenting with a late (Stage III or IV) AJCC cancer stage in 2021 compared with 2019 (odds ratio [OR] = 0.90; 95% confidence interval [CI]: 0.76-1.08); nor increased odds of receiving palliative rather than curative treatment in 2021 compared with 2019 (OR = 0.68; 95% CI: 0.45-1.03). CONCLUSION: The predicted stage shift to more advanced disease at the time of diagnosis of HNC due to the COVID-19 pandemic has not been realised in the longer term. In keeping with this, there was no difference in symptom duration, patient PS, or treatment patterns between the 2019 and 2021 cohorts.

Neurokinin B-Expressing Neurons of the Central Extended Amygdala Mediate Inhibitory Synaptic Input onto Melanin-Concentrating Hormone Neuron Subpopulations.

The lateral hypothalamic area (LHA) is a highly conserved brain region critical for maintaining physiological homeostasis and goal-directed behavior. LHA neurons that express melanin-concentrating hormone (MCH) are key regulators of arousal, energy balance, and motivated behavior. However, cellular and functional diversity among LHAMCH neurons is not well understood. Previous anatomic and molecular data suggest that LHAMCH neurons may be parsed into at least two distinct subpopulations, one of which is enriched in neurokinin-3 receptor (NK3R), the receptor for neurokinin B (NKB), encoded by the Tac2 gene. This tachykininergic ligand-receptor system has been implicated in reproduction, fear memory, and stress in other brain regions, but NKB interactions with LHAMCH neurons are poorly understood. We first identified how LHAMCH subpopulations may be distinguished anatomically and electrophysiologically. To dissect functional connectivity between NKB-expressing neurons and LHAMCH neurons, we used Cre-dependent retrograde and anterograde viral tracing in male Tac2-Cre mice and identified Tac2/EYFP+ neurons in the bed nucleus of the stria terminalis and central nucleus of the amygdala, the central extended amygdala, as major sources of NKB input onto LHAMCH neurons. In addition to innervating the LHA, these limbic forebrain NKB neurons also project to midbrain and brainstem targets. Finally, using a dual-virus approach, we found that optogenetic activation of these inputs in slices evokes GABA release onto a subset of LHAMCH neurons but lacked specificity for the NK3R+ subpopulation. Overall, these data define parallel tachykininergic/GABAergic limbic forebrain projections that are positioned to modulate multiple nodes of homeostatic and behavioral control.SIGNIFICANCE STATEMENT The LHA orchestrates fundamental behavioral states in the mammalian hypothalamus, including arousal, energy balance, memory, stress, and motivated behavior. The neuropeptide MCH defines one prominent population of LHA neurons, with multiple roles in the regulation of homeostatic behavior. Outstanding questions remain concerning the upstream inputs that control MCH neurons. We sought to define neurochemically distinct pathways in the mouse brain that may communicate with specific MCH neuron subpopulations using viral-based retrograde and anterograde neural pathway tracing and optogenetics in brain slices. Here, we identify a specific neuropeptide-defined forebrain circuit that makes functional synaptic connections with MCH neuron subpopulations. This work lays the foundation for further manipulating molecularly distinct neural circuits that modulate innate behavioral states.

Background complexity can mitigate poor camouflage.

Avoiding detection through camouflage is often key to survival. However, an animal's appearance is not the only factor affecting conspicuousness: background complexity also alters detectability. This has been experimentally demonstrated for both artificially patterned backgrounds in the laboratory and natural backgrounds in the wild, but only for targets that already match the background well. Do habitats of high visual complexity provide concealment to even relatively poorly camouflaged animals? Using artificial prey which differed in their degrees of background matching to tree bark, we were able to determine their survival, under bird predation, with respect to the natural complexity of the background. The latter was quantified using low-level vision metrics of feature congestion (or 'visual clutter') adapted for bird vision. Higher background orientation clutter (edges with varying orientation) reduced the detectability of all but the poorest background-matching camouflaged treatments; higher background luminance clutter (varying achromatic lightness) reduced average mortality for all treatments. Our results suggest that poorer camouflage can be mitigated by more complex backgrounds, with implications for both camouflage evolution and habitat preferences.

The role of antibiotics in the surgical management of paediatric obstructive sleep apnoea (OSA): a cohort study.

PURPOSE: Obstructive sleep apnoea (OSA) describes an irregular night-time breathing pattern that is present in approximately 1.8% of children and can have a negative impact on quality of life. The use of antibiotics postoperatively is controversial. They are commonly prescribed; however, they can also be associated with side effects and resistance. This study explores the role of antibiotics in the post-operative management of children with OSA in a cohort of children. METHODS: We conducted a retrospective cohort study of children undergoing surgery for OSA or sleep disordered breathing (SDB) at a tertiary paediatric ENT referral centre from November 2018 to November 2019. RESULTS: This study identified 382 children who had undergone surgical treatment for OSA or sleep disordered breathing (SDB); 319 underwent adenotonsillectomy, 53 adenoidectomy and 10 tonsillectomies. Antibiotics were given post-operatively to 158 (41%) patients and 18 (11%) of these patients presented to hospital with post-operative complications. A higher number of patients re-presented to hospital from the group who did not receive antibiotics (p = 0.982). Bleeding (p = 0.886) and infection (p = 0.823) were also more common in those children who did not receive antibiotics. CONCLUSION: Antibiotics led to fewer complications and re-presentations to hospital in children undergoing operative management of OSA; however, this trend was not found to be statistically significant.

Delivering online alternatives to the anatomy laboratory: Early experience during the COVID-19 pandemic.

Social distancing measures due to the COVID-19 pandemic will make anatomy dissecting room practicals difficult, if not impossible to run at some institutions in the upcoming academic year. The learning community that exists within physical anatomy practicals needs to be moved online. Virtual replacement of visuo-spatial and social elements of learning anatomy pose particular challenges to educators. Our department has trialed Blackboard Collaborate, an online communication platform in conjunction with Visible Body, a 3D anatomical modeling program. We have delivered 266 hr of synchronous small group teaching to medical and physician associate students. We describe this approach and discuss the relevance of distance learning pedagogy to the design of new online anatomy teaching and development of online learning communities.

Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network.

To perform massive-scale replica exchange molecular dynamics (REMD) simulations for calculating binding free energies of protein-ligand complexes, we implemented the asynchronous replica exchange (AsyncRE) framework of the binding energy distribution analysis method (BEDAM) in implicit solvent on the IBM World Community Grid (WCG) and optimized the simulation parameters to reduce the overhead and improve the prediction power of the WCG AsyncRE simulations. We also performed the first massive-scale binding free energy calculations using the WCG distributed computing grid and 301 ligands from the SAMPL4 challenge for large-scale binding free energy predictions of HIV-1 integrase complexes. In total there are ∼10000 simulated complexes, ∼1 million replicas, and ∼2000 µs of aggregated MD simulations. Running AsyncRE MD simulations on the WCG requires accepting a trade-off between the number of replicas that can be run (breadth) and the number of full RE cycles that can be completed per replica (depth). As compared with synchronous Replica Exchange (SyncRE) running on tightly coupled clusters like XSEDE, on the WCG many more replicas can be launched simultaneously on heterogeneous distributed hardware, but each full RE cycle requires more overhead. We compared the WCG results with that from AutoDock and more advanced RE simulations including the use of flattening potentials to accelerate sampling of selected degrees of freedom of ligands and/or receptors related to slow dynamics due to high energy barriers. We propose a suitable strategy of RE simulations to refine high throughput docking results which can be matched to corresponding computing resources: from HPC clusters, to small or medium-size distributed campus grids, and finally to massive-scale computing networks including millions of CPUs like the resources available on the WCG.

Coevolutionary Landscape of Kinase Family Proteins: Sequence Probabilities and Functional Motifs.

The protein kinase catalytic domain is one of the most abundant domains across all branches of life. Although kinases share a common core function of phosphoryl-transfer, they also have wide functional diversity and play varied roles in cell signaling networks, and for this reason are implicated in a number of human diseases. This functional diversity is primarily achieved through sequence variation, and uncovering the sequence-function relationships for the kinase family is a major challenge. In this study we use a statistical inference technique inspired by statistical physics, which builds a coevolutionary "Potts" Hamiltonian model of sequence variation in a protein family. We show how this model has sufficient power to predict the probability of specific subsequences in the highly diverged kinase family, which we verify by comparing the model's predictions with experimental observations in the Uniprot database. We show that the pairwise (residue-residue) interaction terms of the statistical model are necessary and sufficient to capture higher-than-pairwise mutation patterns of natural kinase sequences. We observe that previously identified functional sets of residues have much stronger correlated interaction scores than are typical.

Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.

Understanding the complex mutation patterns that give rise to drug resistant viral strains provides a foundation for developing more effective treatment strategies for HIV/AIDS. Multiple sequence alignments of drug-experienced HIV-1 protease sequences contain networks of many pair correlations which can be used to build a (Potts) Hamiltonian model of these mutation patterns. Using this Hamiltonian model, we translate HIV-1 protease sequence covariation data into quantitative predictions for the probability of observing specific mutation patterns which are in agreement with the observed sequence statistics. We find that the statistical energies of the Potts model are correlated with the fitness of individual proteins containing therapy-associated mutations as estimated by in vitro measurements of protein stability and viral infectivity. We show that the penalty for acquiring primary resistance mutations depends on the epistatic interactions with the sequence background. Primary mutations which lead to drug resistance can become highly advantageous (or entrenched) by the complex mutation patterns which arise in response to drug therapy despite being destabilizing in the wildtype background. Anticipating epistatic effects is important for the design of future protease inhibitor therapies.

Improving Prediction Accuracy of Binding Free Energies and Poses of HIV Integrase Complexes Using the Binding Energy Distribution Analysis Method with Flattening Potentials.

To accelerate conformation sampling of slow dynamics from receptor or ligand, we introduced flattening potentials on selected bonded and nonbonded intramolecular interactions to the binding energy distribution analysis method (BEDAM) for calculating absolute binding free energies of protein-ligand complexes using an implicit solvent model and implemented flattening BEDAM using the asynchronous replica exchange (AsyncRE) framework for performing large scale replica exchange molecular dynamics (REMD) simulations. The advantage of using the flattening feature to reduce high energy barriers was exhibited first by the p-xylene-T4 lysozyme complex, where the intramolecular interactions of a protein side chain on the binding site were flattened to accelerate the conformational transition of the side chain from the trans to the gauche state when the p-xylene ligand is present in the binding site. Much more extensive flattening BEDAM simulations were performed for 53 experimental binders and 248 nonbinders of HIV-1 integrase which formed the SAMPL4 challenge, with the total simulation time of 24.3 µs. We demonstrated that the flattening BEDAM simulations not only substantially increase the number of true positives (and reduce false negatives) but also improve the prediction accuracy of binding poses of experimental binders. Furthermore, the values of area under the curve (AUC) of receiver operating characteristic (ROC) and the enrichment factors at 20% cutoff calculated from the flattening BEDAM simulations were improved significantly in comparison with that of simulations without flattening as we previously reported for the whole SAMPL4 database. Detailed analysis found that the improved ability to discriminate the binding free energies between the binders and nonbinders is due to the fact that the flattening simulations reduce the reorganization free energy penalties of binders and decrease the overlap of binding free energy distributions of binders relative to that of nonbinders. This happens because the conformational ensemble distributions for both the ligand and protein in solution match those at the fully coupled (complex) state more closely when the systems are more fully sampled after the flattening potentials are applied to the intermediate states.

A combined treatment of hydration and dynamical effects for the modeling of host-guest binding thermodynamics: the SAMPL5 blinded challenge.

As part of the SAMPL5 blinded experiment, we computed the absolute binding free energies of 22 host-guest complexes employing a novel approach based on the BEDAM single-decoupling alchemical free energy protocol with parallel replica exchange conformational sampling and the AGBNP2 implicit solvation model specifically customized to treat the effect of water displacement as modeled by the Hydration Site Analysis method with explicit solvation. Initial predictions were affected by the lack of treatment of ionic charge screening, which is very significant for these highly charged hosts, and resulted in poor relative ranking of negatively versus positively charged guests. Binding free energies obtained with Debye-Hückel treatment of salt effects were in good agreement with experimental measurements. Water displacement effects contributed favorably and very significantly to the observed binding affinities; without it, the modeling predictions would have grossly underestimated binding. The work validates the implicit/explicit solvation approach employed here and it shows that comprehensive physical models can be effective at predicting binding affinities of molecular complexes requiring accurate treatment of conformational dynamics and hydration.

Development of a microbial dose response visualization and modelling application for QMRA modelers and educators.

Microbial dose response modelling is vital to a well-characterized microbial risk estimate. Dose response modelling is an inherently multidisciplinary field, which collates knowledge and data from disparate scientific fields. This multidisciplinary nature presents a key challenge to the expansion of microbial dose response modelling into new groups of researchers and modelers. This research employs a dose response optimization R code used in 18 peer-reviewed research studies to develop a multi-functional dose response software. The underlying R code performs an optimization of the two primary dose response models using the MLE method and outputs statistical analyses of the fits and bootstrapped uncertainty information for the models. VizDR (Visual Dose Response) was developed to provide microbial dose response modelling capabilities to a larger audience. VizDR is programmed in JavaScript with underlying Python scripts for intercommunication with Rserve. VizDR allows for dose response model visualization and optimization of a user's own experimental data.

Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease.

While the role of drug resistance mutations in HIV protease has been studied comprehensively, mutations in its substrate, Gag, have not been extensively cataloged. Using deep sequencing, we analyzed a unique collection of longitudinal viral samples from 93 patients who have been treated with therapies containing protease inhibitors (PIs). Due to the high sequence coverage within each sample, the frequencies of mutations at individual positions were calculated with high precision. We used this information to characterize the variability in the Gag polyprotein and its effects on PI-therapy outcomes. To examine covariation of mutations between two different sites using deep sequencing data, we developed an approach to estimate the tight bounds on the two-site bivariate probabilities in each viral sample, and the mutual information between pairs of positions based on all the bounds. Utilizing the new methodology we found that mutations in the matrix and p6 proteins contribute to continued therapy failure and have a major role in the network of strongly correlated mutations in the Gag polyprotein, as well as between Gag and protease. Although covariation is not direct evidence of structural propensities, we found the strongest correlations between residues on capsid and matrix of the same Gag protein were often due to structural proximity. This suggests that some of the strongest inter-protein Gag correlations are the result of structural proximity. Moreover, the strong covariation between residues in matrix and capsid at the N-terminus with p1 and p6 at the C-terminus is consistent with residue-residue contacts between these proteins at some point in the viral life cycle.

Large scale free energy calculations for blind predictions of protein-ligand binding: the D3R Grand Challenge 2015.

We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90. The present D3R challenge was built around experimental datasets involving Heat shock protein (Hsp) 90, an ATP-dependent molecular chaperone which is an important anticancer drug target. The Hsp90 ATP binding site is known to be a challenging target for accurate calculations of ligand binding affinities because of the ligand-dependent conformational changes in the binding site, the presence of ordered waters and the broad chemical diversity of ligands that can bind at this site. Our primary focus here is to distinguish binders from nonbinders. Large scale absolute binding free energy calculations that cover over 3000 protein-ligand complexes were performed using the BEDAM method starting from docked structures generated by Glide docking. Although the ligand dataset in this study resembles an intermediate to late stage lead optimization project while the BEDAM method is mainly developed for early stage virtual screening of hit molecules, the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target. Results show that, using a statistical mechanics based free energy method like BEDAM starting from docked poses offers better enrichment than classical docking scoring functions and rescoring methods like Prime MM-GBSA for the Hsp90 data set in this blind challenge. Importantly, among the three methods tested here, only the mean value of the BEDAM binding free energy scores is able to separate the large group of binders from the small group of nonbinders with a gap of 2.4 kcal/mol. None of the three methods that we have tested provided accurate ranking of the affinities of the 147 active compounds. We discuss the possible sources of errors in the binding free energy calculations. The study suggests that BEDAM can be used strategically to discriminate binders from nonbinders in virtual screening and to more accurately predict the ligand binding modes prior to the more computationally expensive FEP calculations of binding affinity.

Large-scale asynchronous and distributed multidimensional replica exchange molecular simulations and efficiency analysis.

We describe methods to perform replica exchange molecular dynamics (REMD) simulations asynchronously (ASyncRE). The methods are designed to facilitate large scale REMD simulations on grid computing networks consisting of heterogeneous and distributed computing environments as well as on homogeneous high-performance clusters. We have implemented these methods on NSF (National Science Foundation) XSEDE (Extreme Science and Engineering Discovery Environment) clusters and BOINC (Berkeley Open Infrastructure for Network Computing) distributed computing networks at Temple University and Brooklyn College at CUNY (the City University of New York). They are also being implemented on the IBM World Community Grid. To illustrate the methods, we have performed extensive (more than 60 ms in aggregate) simulations for the beta-cyclodextrin-heptanoate host-guest system in the context of one- and two-dimensional ASyncRE, and we used the results to estimate absolute binding free energies using the binding energy distribution analysis method. We propose ways to improve the efficiency of REMD simulations: these include increasing the number of exchanges attempted after a specified molecular dynamics (MD) period up to the fast exchange limit and/or adjusting the MD period to allow sufficient internal relaxation within each thermodynamic state. Although ASyncRE simulations generally require long MD periods (>picoseconds) per replica exchange cycle to minimize the overhead imposed by heterogeneous computing networks, we found that it is possible to reach an efficiency similar to conventional synchronous REMD, by optimizing the combination of the MD period and the number of exchanges attempted per cycle.

Asynchronous Replica Exchange Software for Grid and Heterogeneous Computing.

Parallel replica exchange sampling is an extended ensemble technique often used to accelerate the exploration of the conformational ensemble of atomistic molecular simulations of chemical systems. Inter-process communication and coordination requirements have historically discouraged the deployment of replica exchange on distributed and heterogeneous resources. Here we describe the architecture of a software (named ASyncRE) for performing asynchronous replica exchange molecular simulations on volunteered computing grids and heterogeneous high performance clusters. The asynchronous replica exchange algorithm on which the software is based avoids centralized synchronization steps and the need for direct communication between remote processes. It allows molecular dynamics threads to progress at different rates and enables parameter exchanges among arbitrary sets of replicas independently from other replicas. ASyncRE is written in Python following a modular design conducive to extensions to various replica exchange schemes and molecular dynamics engines. Applications of the software for the modeling of association equilibria of supramolecular and macromolecular complexes on BOINC campus computational grids and on the CPU/MIC heterogeneous hardware of the XSEDE Stampede supercomputer are illustrated. They show the ability of ASyncRE to utilize large grids of desktop computers running the Windows, MacOS, and/or Linux operating systems as well as collections of high performance heterogeneous hardware devices.

Medication health literacy measure: development and psychometric properties.

BACKGROUND AND PURPOSE: Low levels of health literacy are prevalent worldwide. This report details development and psychometric properties of a health literacy measure for oral medications based on design of the Newest Vital Sign. METHODS: The measure was completed during the baseline interview. A principal components analysis evaluated dimensionality of the measure. Cronbach's alpha assessed subscale internal consistencies. RESULTS: Internal consistencies and reliability for the subscales were acceptable for a new instrument (alpha = .661, alpha = .686, alpha = .400). A 3-factor structure explained 65.34% of the total variance. Divergent validity with the Rapid Estimate of Adult Literacy in Medicine (REALM) was established. CONCLUSIONS: Our data indicates that the medication health literacy tool is multidimensional, valid, and reliable. This information is important in light of emerging evidence of the impact of health literacy on medication adherence and health.

Efficacy and Safety of a Preservative-Free Latanoprost Cationic Emulsion in Patients with Open-Angle Glaucoma and Concurrent Ocular Surface Disease: A Randomized Phase 2 Study.

Purpose: To compare intraocular pressure (IOP), ocular surface disease (OSD) parameters, and safety in patients with open-angle glaucoma (OAG)/ocular hypertension (OH) and concurrent OSD treated with preservative-free latanoprost 0.005% cationic emulsion (PF-latanoprost-E) or travoprost-Z 0.004% ophthalmical solution containing a soft preservative system. Methods: Patients with OAG/OH and OSD were randomized to treatment with PF-latanoprost-E or travoprost-Z nightly for 3 months. Outcomes included mean diurnal IOP reduction; OSD endpoints, including symptom improvement, tear break-up time (TBUT), and corneal fluorescein staining (CFS) score; and safety after 1 and 3 months. Results: A total of 105 patients were randomized, 51 to PF-latanoprost-E and 54 to travoprost-Z. IOP reductions (LS mean differences) at 3 months were numerically greater in the PF-latanoprost-E than in the travoprost-Z group at 8AM (7.2 versus 6.0 mmHg), 10AM (6.7 versus 5.9 mmHg), and 4PM (6.0 versus 5.4 mmHg). LS mean changes in IOP from baseline in both groups at 1 and 3 months, however, were comparable. Mean ± SD CFS scores on the Ora scale at month 3 showed significantly greater reductions in the PF-latanoprost-E than in the travoprost-Z group (-1.07 ± 1.863 versus -0.16 ± 2.553 P = 0.0461). The mean TBUT at month 3 showed similar improvements in both groups (1.1 versus 1.0 s, P > 0.05). OSD symptoms improved but did not differ significantly in the two groups. Overall safety was comparable in both groups. Conclusion: PF-latanoprost-E effectively and safely lowered IOP and improved OSD parameters in patients with OAG/OH. These findings provide evidence for the beneficial effects of this new formulation of latanoprost in glaucoma patients with OSD.

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans.

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.