Identification of Fibrinogen as a Plasma Protein Binding Partner for Lecanemab Biosimilar IgG: Implications for Alzheimer's Disease Therapy.

Objective: Recombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimer's disease, offer a promising approach for modifying the disease progression. Due to its relatively short half-life, Lecanemab, administered as a bi-monthly infusion (typically 10mg/kg) has a relatively brief half-life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half-life. In this study we investigated potential plasma protein binding interaction to lecanemab using lecanemab biosimilar. Methods: Lecanemab biosimilar used in this study was based on publicly available sequences. ELISA and Western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions human plasma sample obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate binders was confirmed by Western blotting, ELISA, and surface plasmon resonance analysis. Results: Using a combination of equilibrium dialysis, ELISA, and Western blotting in human plasma, we first describe the presence of likely plasma protein binding partner to lecanemab biosimilar, and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta. Interpretation: In the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that plasma protein binding may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease.

The effect of pseudoknot base pairing on cotranscriptional structural switching of the fluoride riboswitch.

A central question in biology is how RNA sequence changes influence dynamic conformational changes during cotranscriptional folding. Here we investigated this question through the study of transcriptional fluoride riboswitches, non-coding RNAs that sense the fluoride anion through the coordinated folding and rearrangement of a pseudoknotted aptamer domain and a downstream intrinsic terminator expression platform. Using a combination of Escherichia coli RNA polymerase in vitro transcription and cellular gene expression assays, we characterized the function of mesophilic and thermophilic fluoride riboswitch variants. We showed that only variants containing the mesophilic pseudoknot function at 37°C. We next systematically varied the pseudoknot sequence and found that a single wobble base pair is critical for function. Characterizing thermophilic variants at 65°C through Thermus aquaticus RNA polymerase in vitro transcription showed the importance of this wobble pair for function even at elevated temperatures. Finally, we performed all-atom molecular dynamics simulations which supported the experimental findings, visualized the RNA structure switching process, and provided insight into the important role of magnesium ions. Together these studies provide deeper insights into the role of riboswitch sequence in influencing folding and function that will be important for understanding of RNA-based gene regulation and for synthetic biology applications.

Elucidating the influence of RNA modifications and Magnesium ions on tRNA Phe conformational dynamics in S. cerevisiae : Insights from Replica Exchange Molecular Dynamics simulations.

Post-transcriptional modifications in RNA can significantly impact their structure and function. In particular, transfer RNAs (tRNAs) are heavily modified, with around 100 different naturally occurring nucleotide modifications contributing to codon bias and decoding efficiency. Here, we describe our efforts to investigate the impact of RNA modifications on the structure and stability of tRNA Phenylalanine (tRNA Phe ) from S. cerevisiae using molecular dynamics (MD) simulations. Through temperature replica exchange MD (T-REMD) studies, we explored the unfolding pathway to understand how RNA modifications influence the conformational dynamics of tRNA Phe , both in the presence and absence of magnesium ions (Mg 2+ ). We observe that modified nucleotides in key regions of the tRNA establish a complex network of hydrogen bonds and stacking interactions which is essential for tertiary structure stability of the tRNA. Furthermore, our simulations show that modifications facilitate the formation of ion binding sites on the tRNA. However, high concentrations of Mg 2+ ions can stabilize the tRNA tertiary structure in the absence of modifications. Our findings illuminate the intricate interactions between modifications, magnesium ions, and RNA structural stability.

Differential roles of normal and lung cancer-associated fibroblasts in microvascular network formation.

Perfusable microvascular networks offer promising three-dimensional in vitro models to study normal and compromised vascular tissues as well as phenomena such as cancer cell metastasis. Engineering of these microvascular networks generally involves the use of endothelial cells stabilized by fibroblasts to generate robust and stable vasculature. However, fibroblasts are highly heterogenous and may contribute variably to the microvascular structure. Here, we study the effect of normal and cancer-associated lung fibroblasts on the formation and function of perfusable microvascular networks. We examine the influence of cancer-associated fibroblasts on microvascular networks when cultured in direct (juxtacrine) and indirect (paracrine) contacts with endothelial cells, discovering a generative inhibition of microvasculature in juxtacrine co-cultures and a functional inhibition in paracrine co-cultures. Furthermore, we probed the secreted factors differential between cancer-associated fibroblasts and normal human lung fibroblasts, identifying several cytokines putatively influencing the resulting microvasculature morphology and functionality. These findings suggest the potential contribution of cancer-associated fibroblasts in aberrant microvasculature associated with tumors and the plausible application of such in vitro platforms in identifying new therapeutic targets and/or agents that can prevent formation of aberrant vascular structures.

Mutation of two intronic nucleotides alters RNA structure and dynamics inhibiting MBNL1 and RBFOX1 regulated splicing of the Insulin Receptor.

Alternative splicing (AS) of Exon 11 of the Insulin Receptor ( INSR ) is highly regulated and disrupted in several human disorders. To better understand INSR exon 11 AS regulation, splicing activity of an INSR exon 11 minigene reporter was measured across a gradient of the AS regulator muscleblind-like 1 protein (MBNL1). The RNA-binding protein Fox-1 (RBFOX1) was added to determine its impact on MBNL1-regulated splicing. The role of the RBFOX1 UGCAUG binding site within intron 11 was assessed across the MBNL1 gradient. Mutating the UGCAUG motif inhibited RBFOX1 regulation of exon 11 and had the unexpected effect of reducing MBNL1 regulation of this exon. Molecular dynamics simulations showed that exon 11 and the adjacent RNA adopts a dynamically stable conformation. Mutation of the RBFOX1 binding site altered RNA structure and dynamics, while a mutation that created an optimal MBNL1 binding site at the RBFOX1 site shifted the RNA back to wild type. An antisense oligonucleotide (ASO) was used to confirm the structure in this region of the pre-mRNA. This example of intronic mutations shifting pre-mRNA structure and dynamics to modulate splicing suggests RNA structure and dynamics should be taken into consideration for AS regulation and therapeutic interventions targeting pre-mRNA.

Systematic comparison of rAAV vectors manufactured using large-scale suspension cultures of Sf9 and HEK293 cells.

Recombinant adeno-associated virus (rAAV) vectors could be manufactured by plasmid transfection into human embryonic kidney 293 (HEK293) cells or baculovirus infection of Spodoptera frugiperda (Sf9) insect cells. However, systematic comparisons between these systems using large-scale, high-quality AAV vectors are lacking. rAAV from Sf9 cells (Sf9-rAAV) at 2-50 L and HEK293 cells (HEK-rAAV) at 2-200 L scales were characterized. HEK-rAAV had ∼40-fold lower yields but ∼10-fold more host cell DNA measured by droplet digital PCR and next-generation sequencing, respectively. The electron microscope observed a lower full/empty capsid ratio in HEK-rAAV (70.8%) than Sf9-rAAV (93.2%), while dynamic light scattering and high-performance liquid chromatography analysis showed that HEK-rAAV had more aggregation. Liquid chromatography tandem mass spectrometry identified different post-translational modification profiles between Sf9-rAAV and HEK-rAAV. Furthermore, Sf9-rAAV had a higher tissue culture infectious dose/viral genome than HEK-rAAV, indicating better infectivity. Additionally, Sf9-rAAV achieved higher in vitro transgene expression, as measured by ELISA. Finally, after intravitreal dosing into a mouse laser choroidal neovascularization model, Sf9-rAAV and HEK-rAAV achieved similar efficacy. Overall, this study detected notable differences in the physiochemical characteristics of HEK-rAAV and Sf9-rAAV. However, the in vitro and in vivo biological functions of the rAAV from these systems were highly comparable. Sf9-rAAV may be preferred over HEK293-rAAV for advantages in yields, full/empty ratio, scalability, and cost.

The Effect of Pseudoknot Base Pairing on Cotranscriptional Structural Switching of the Fluoride Riboswitch.

A central question in biology is how RNA sequence changes influence dynamic conformational changes during cotranscriptional folding. Here we investigated this question through the study of transcriptional fluoride riboswitches, non-coding RNAs that sense the fluoride anion through the coordinated folding and rearrangement of a pseudoknotted aptamer domain and a downstream intrinsic terminator expression platform. Using a combination of E. coli RNA polymerase in vitro transcription and cellular gene expression assays, we characterized the function of mesophilic and thermophilic fluoride riboswitch variants. We showed that only variants containing the mesophilic pseudoknot function at 37 °C. We next systematically varied the pseudoknot sequence and found that a single wobble base pair is critical for function. Characterizing thermophilic variants at 65 °C through Thermus aquaticus RNA polymerase in vitro transcription showed the importance of this wobble pair for function even at elevated temperatures. Finally, we performed all-atom molecular dynamics simulations which supported the experimental findings, visualized the RNA structure switching process, and provided insight into the important role of magnesium ions. Together these studies provide deeper insights into the role of riboswitch sequence in influencing folding and function that will be important for understanding of RNA-based gene regulation and for synthetic biology applications.

Three-dimensional flat bands in pyrochlore metal CaNi2.

Electronic flat-band materials host quantum states characterized by a quenched kinetic energy. These flat bands are often conducive to enhanced electron correlation effects and emergent quantum phases of matter1. Long studied in theoretical models2-4, these systems have received renewed interest after their experimental realization in van der Waals heterostructures5,6 and quasi-two-dimensional (2D) crystalline materials7,8. An outstanding experimental question is if such flat bands can be realized in three-dimensional (3D) networks, potentially enabling new materials platforms9,10 and phenomena11-13. Here we investigate the C15 Laves phase metal CaNi2, which contains a nickel pyrochlore lattice predicted at a model network level to host a doubly-degenerate, topological flat band arising from 3D destructive interference of electronic hopping14,15. Using angle-resolved photoemission spectroscopy, we observe a band with vanishing dispersion across the full 3D Brillouin zone that we identify with the pyrochlore flat band as well as two additional flat bands that we show arise from multi-orbital interference of Ni d-electrons. Furthermore, we demonstrate chemical tuning of the flat-band manifold to the Fermi level that coincides with enhanced electronic correlations and the appearance of superconductivity. Extending the notion of intrinsic band flatness from 2D to 3D, this provides a potential pathway to correlated behaviour predicted for higher-dimensional flat-band systems ranging from tunable topological15 to fractionalized phases16.

Complex Three-Dimensional Microscale Structures for Quantum Sensing Applications.

We present a novel method for fabricating highly customizable three-dimensional structures hosting quantum sensors based on nitrogen vacancy (NV) centers using two-photon polymerization. This approach overcomes challenges associated with structuring traditional single-crystal quantum sensing platforms and enables the creation of complex, fully three-dimensional, sensor assemblies with submicroscale resolutions (down to 400 nm) and large fields of view (>1 mm). By embedding NV center-containing nanoparticles in exemplary structures, we demonstrate high sensitivity optical sensing of temperature and magnetic fields at the microscale. Our work showcases the potential for integrating quantum sensors with advanced manufacturing techniques, facilitating the incorporation of sensors into existing microfluidic and electronic platforms, and opening new avenues for widespread utilization of quantum sensors in various applications.

Bootstrapping the String Kawai-Lewellen-Tye Kernel.

We show that double-copy maps for amplitudes in effective field theory are severely constrained at four points by self-consistency and locality at six points. The resulting double-copy kernel depends only on two parameters as well as a specific symmetric function in s, t, u and interpolates between the original Kawai-Lewellen-Tye (KLT) string double copy and the open and closed string period integrals. Amplitudes double copied with this map must obey either the string monodromy relations or the field theory Kleiss-Kuijf (KK) and Bern, Carrasco, and Johansson (BCJ) relations; there are no other options. Our construction elucidates the "single-valued projection" property of the Riemann zeta-function values for the four-point string theory double copy.

Aggregation in Aqueous Solutions of 2-(Tetrafluoro(trifluoromethyl)-λ6-sulfanyl-ethan-1-ol (CF3SF4-ethanol)): A Comparison with Aqueous Trifluoroethanol and Hexafluoroisopropanol Using Molecular Dynamics Simulations and Dynamic Light Scattering Experiments.

2-Tetrafluoro(trifluoromethyl)-λ6-sulfanylethan-1-ol (CF3SF4-ethanol) combines the polar hydrophobicity of tetrafluoro(trifluoromethyl)-λ6-sulfanyl (CF3SF4) group with the polarity of simple alcohols. The properties of aqueous solutions of the well-known fluorinated alcohols 2,2,2-trifluoroethanol (TFE) and 1,1,1,3,3,3-hexafluoroisopropanol (HFIP) were compared with those of aqueous solutions of the novel CF3SF4-ethanol. Those properties were computed using all atom molecular dynamics simulations with OPLS-compatible parameters. DFT ab initio calculations were used to accurately describe the nonsymmetrical, hypervalent sulfur in CF3SF4-ethanol. Although the molecular and conformational characteristics of CF3SF4-ethanol are like those of both TFE and HFIP, the greater hydrophobicity and lower polarity of CF3SF4-ethanol resulted in solution phase aggregation at a much lower concentration. The properties computed for TFE and HFIP in this work were consistent with published computational and experimental studies. CF3SF4-ethanol is predicted to be environmentally benign and hence an excellent green solvent candidate while possessing many of the same properties as TFE or HFIP.

Characterizing the Folding Transition-State Ensembles in the Energy Landscape of an RNA Tetraloop.

Molecular dynamics (MD) simulations have become increasingly powerful and can now describe the folding/unfolding of small biomolecules in atomic detail. However, a major challenge in MD simulations is to represent the complex energy landscape of biomolecules using a small number of reaction coordinates. In this study, we investigate the folding pathways of an RNA tetraloop, gcGCAAgc, using five classical MD simulations with a combined simulation time of approximately 120 µs. Our approach involves analyzing the tetraloop dynamics, including the folding transition state ensembles, using the energy landscape visualization method (ELViM). The ELViM is an approach that uses internal distances to compare any two conformations, allowing for a detailed description of the folding process without requiring root mean square alignment of structures. This method has previously been applied to describe the energy landscape of disordered ß-amyloid peptides and other proteins. The ELViM results in a non-linear projection of the multidimensional space, providing a comprehensive representation of the tetraloop's energy landscape. Our results reveal four distinct transition-state regions and establish the paths that lead to the folded tetraloop structure. This detailed analysis of the tetraloop's folding process has important implications for understanding RNA folding, and the ELViM approach can be used to study other biomolecules.

The impacts of the 340B Program on health care quality for low-income patients.

OBJECTIVE: To assess the effects of hospital 340B eligibility on quality of inpatient care provided to Medicaid and uninsured patients and for all patients. DATA: Agency for Health Care Research and Quality's Healthcare Cost and Utilization Project State Inpatient Data, Hospital Cost Reporting Information System Data, Office of Pharmacy Affairs Information System Data, and American Hospital Association Annual Survey. DESIGN: Regression discontinuity design comparing hospitals just above the DSH percentage program eligibility threshold to those just below. Quality measures include all-cause mortality and 30-day readmission rates as well as condition-specific measures. DATA EXTRACTION: Inpatient data from general acute care hospitals from 2008 to 2014 in 15 states. Data linked on hospital 340B eligibility and participation. PRINCIPAL FINDINGS: We did not find discontinuities in inpatient care quality across the Program eligibility threshold for Medicaid and uninsured patients; specifically, on all-cause mortality (beta = -0.04 percentage points, 95% CI: -0.16, 0.08), 30-day readmission rates (beta = -0.16 percentage points, 95% CI: -0.81, 0.5), or other measures. Among insured and non-Medicaid patients, we found discontinuities for acute myocardial infarction (beta = -0.87 percentage points, 95% CI: -1.55, -0.2) and postoperative sepsis (beta = -0.15 percentage points, 95% CI: -0.23, -0.07) mortality. CONCLUSIONS: 340B Program participation has not demonstrated improved quality of inpatient care among Medicaid or uninsured patients.

Measuring neutron capture cross sections of radioactive nuclei: From activations at the FZK Van de Graaff to direct neutron captures in inverse kinematics with a storage ring at TRIUMF.

Measuring neutron capture cross sections of radioactive nuclei is a crucial step towards a better understanding of the origin of the elements heavier than iron. For decades, the precise measurement of direct neutron capture cross sections in the "stellar" energy range (eV up to a few MeV) was limited to stable and longer-lived nuclei that could be provided as physical samples and then irradiated with neutrons. New experimental methods are now being developed to extend these direct measurements towards shorter-lived radioactive nuclei (t1/2< 1 y). One project in this direction is a low-energy heavy-ion storage ring coupled to the ISAC facility at TRIUMF, Canada's accelerator laboratory in Vancouver BC, which has a compact neutron source in the ring matrix. Such a pioneering facility could be built within the next 10 years and store a wide range of radioactive ions provided directly from the existing ISOL facility, allowing for the first time to carry out direct neutron capture measurements on short-lived isotopes in inverse kinematics.

Hospital concentration and low-income populations: Evidence from New York State Medicaid.

While a large body of evidence has examined hospital concentration, its effects on health care for low-income populations are less explored. We use comprehensive discharge data from New York State to measure the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. Holding fixed hospital factors constant, a one percent increase in HHI leads to a 0.6% (s.e. = 0.28%) decrease in the number of Medicaid admissions for the average hospital. The strongest effects are on admissions for birth (-1.3%, s.e. = 0.58%). These average hospital-level decreases largely reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. In particular, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. We find evidence that for births, physicians serving high shares of Medicaid beneficiaries in particular experience reduced admissions as concentration increased. These reductions may reflect preferences among these physicians or reduced admitting privileges by hospitals as a means to screen out Medicaid patients.

Applied machine learning to identify differential risk groups underlying externalizing and internalizing problem behaviors trajectories: A case study using a cohort of Asian American children.

BACKGROUND: Internalizing and externalizing problems account for over 75% of the mental health burden in children and adolescents in the US, with higher burden among minority children. While complex interactions of multilevel factors are associated with these outcomes and may enable early identification of children in higher risk, prior research has been limited by data and application of traditional analysis methods. In this case example focused on Asian American children, we address the gap by applying data-driven statistical and machine learning methods to study clusters of mental health trajectories among children, investigate optimal predictions of children at high-risk cluster, and identify key early predictors. METHODS: Data from the US Early Childhood Longitudinal Study 2010-2011 were used. Multilevel information provided by children, families, teachers, schools, and care-providers were considered as predictors. Unsupervised machine learning algorithm was applied to identify groups of internalizing and externalizing problems trajectories. For prediction of high-risk group, ensemble algorithm, Superlearner, was implemented by combining several supervised machine learning algorithms. Performance of Superlearner and candidate algorithms, including logistic regression, was assessed using discrimination and calibration metrics via crossvalidation. Variable importance measures along with partial dependence plots were utilized to rank and visualize key predictors. FINDINGS: We found two clusters suggesting high- and low-risk groups for both externalizing and internalizing problems trajectories. While Superlearner had overall best discrimination performance, logistic regression had comparable performance for externalizing problems but worse for internalizing problems. Predictions from logistic regression were not well calibrated compared to those from Superlearner, however they were still better than few candidate algorithms. Important predictors identified were combination of test scores, child factors, teacher rated scores, and contextual factors, which showed non-linear associations with predicted probabilities. CONCLUSIONS: We demonstrated the application of data-driven analytical approach to predict mental health outcomes among Asian American children. Findings from the cluster analysis can inform critical age for early intervention, while prediction analysis has potential to inform intervention programing prioritization decisions. However, to better understand external validity, replicability, and value of machine learning in broader mental health research, more studies applying similar analytical approach is needed.

High-throughput single-molecule quantification of individual base stacking energies in nucleic acids.

Base stacking interactions between adjacent bases in DNA and RNA are important for many biological processes and in biotechnology applications. Previous work has estimated stacking energies between pairs of bases, but contributions of individual bases has remained unknown. Here, we use a Centrifuge Force Microscope for high-throughput single molecule experiments to measure stacking energies between adjacent bases. We found stacking energies strongest between purines (G|A at -2.3 ± 0.2 kcal/mol) and weakest between pyrimidines (C|T at -0.5 ± 0.1 kcal/mol). Hybrid stacking with phosphorylated, methylated, and RNA nucleotides had no measurable effect, but a fluorophore modification reduced stacking energy. We experimentally show that base stacking can influence stability of a DNA nanostructure, modulate kinetics of enzymatic ligation, and assess accuracy of force fields in molecular dynamics simulations. Our results provide insights into fundamental DNA interactions that are critical in biology and can inform design in biotechnology applications.

Toehold clipping: A mechanism for remote control of DNA strand displacement.

The ability to create stimuli-responsive DNA nanostructures has played a prominent role in dynamic DNA nanotechnology. Primary among these is the process of toehold-based strand displacement, where a nucleic acid molecule can act as a trigger to cause conformational changes in custom-designed DNA nanostructures. Here, we add another layer of control to strand displacement reactions through a 'toehold clipping' process. By designing DNA complexes with a photocleavable linker-containing toehold or an RNA toehold, we show that we can use light (UV) or enzyme (ribonuclease) to eliminate the toehold, thus preventing strand displacement reactions. We use molecular dynamics simulations to analyze the structural effects of incorporating a photocleavable linker in DNA complexes. Beyond simple DNA duplexes, we also demonstrate the toehold clipping process in a model DNA nanostructure, by designing a toehold containing double-bundle DNA tetrahedron that disassembles when an invading strand is added, but stays intact after the toehold clipping process even in the presence of the invading strand. This work is an example of combining multiple physical or molecular stimuli to provide additional remote control over DNA nanostructure reconfiguration, advances that hold potential use in biosensing, drug delivery or molecular computation.

Design of a protein-targeted DNA aptamer using atomistic simulation.

The concentrations of specific macromolecular species can be quantified using diagnostic tools that rely on molecular recognition by nucleic acid aptamers. One such approach involves the formation of osmium tetroxide 2,2'-bipyridine protein adducts, followed by electrochemical detection of analytes that bind specifically to electrode-tethered aptamers. In conjunction with a 27-mer DNA aptamer that binds specifically to exosite II on human alpha thrombin, this technique permits, in theory, a highly sensitive diagnostic tool for the quantification of serum thrombin levels. However, thrombin's aptamer binding site is lined by two tryptophan residues and the conjugation of bulky osmium groups to these residues weakens aptamer binding by an estimated 4 to 12 kcal/mol, undermining detection sensitivity. Therefore, we have rationally modified this DNA aptamer to strengthen its thrombin binding in the presence of conjugated osmium. Specifically, aptamers carrying long hydrophobic thymine derivatives in place of guanine 21 have binding affinities for osmium-conjugated thrombin that are enhanced by 10 to 15 kcal/mol, suggesting that these modified aptamers may be effective in a highly sensitive electrochemical sensor for the quantification of low concentrations of thrombin. Our approach of using molecular simulation to subtly re-engineer a DNA aptamer may be generally applicable for the optimization of other macromolecular binding interfaces.Communicated by Ramaswamy H. Sarma.

Paradoxical Effects of Depression on Psoriatic Arthritis Outcomes in a Combined Psoriasis-Psoriatic Arthritis Center.

Backgroud: Psoriatic arthritis (PsA) is a chronic, inflammatory arthritis that, when left untreated, can lead to erosions, deformities and decrease in quality of life. PsA is known to be associated with multiple comorbidities, including cardiovascular, metabolic and mental health syndromes, all of which can increase its overall morbidity and mortality. Objective: To characterize a cohort of patients with PsA and understand the impact of depression on PsA outcome measures. Methods: 527 consecutive patients with PsA were enrolled in an observational, longitudinal registry that followed them prospectively at standard of care visits. Demographics, medical history, medication use, and clinical exam were all recorded. Results: Depression was reported in 22.8% of the population, anxiety in 18%, and attention deficit hyperactivity disorder in 4%. Depression was more common in female participants (P < .001). At baseline, individuals with PsA and concomitant depression had similar tender and swollen joint counts and RAPID3 compared to those without depression, and had lower body surface area affected by psoriasis (P = .04). At year one, all patients had improvement in clinical outcomes. However, patients with depression had a significantly higher tender joint count compared to those without depression (P = .001), despite similar swollen joint count and body surface area. Conclusion: In patients with depression, there is a discrepancy between improvement in physician assessed measures and patient reported outcomes. These observations underscore the importance of addressing depression and psychological distress as part of PsA treatment outcomes and points towards the need to address residual pain through co-adjuvant approaches.