BDIS-SLAM: a lightweight CPU-based dense stereo SLAM for surgery.

PURPOSE: Common dense stereo simultaneous localization and mapping (SLAM) approaches in minimally invasive surgery (MIS) require high-end parallel computational resources for real-time implementation. Yet, it is not always feasible since the computational resources should be allocated to other tasks like segmentation, detection, and tracking. To solve the problem of limited parallel computational power, this research aims at a lightweight dense stereo SLAM system that works on a single-core CPU and achieves real-time performance (more than 30 Hz in typical scenarios). METHODS: A new dense stereo mapping module is integrated with the ORB-SLAM2 system and named BDIS-SLAM. Our new dense stereo mapping module includes stereo matching and 3D dense depth mosaic methods. Stereo matching is achieved with the recently proposed CPU-level real-time matching algorithm Bayesian Dense Inverse Searching (BDIS). A BDIS-based shape recovery and a depth mosaic strategy are integrated as a new thread and coupled with the backbone ORB-SLAM2 system for real-time stereo shape recovery. RESULTS: Experiments on in vivo data sets show that BDIS-SLAM runs at over 30 Hz speed on modern single-core CPU in typical endoscopy/colonoscopy scenarios. BDIS-SLAM only consumes around an additional 12 % time compared with the backbone ORB-SLAM2. Although our lightweight BDIS-SLAM simplifies the process by ignoring deformation and fusion procedures, it can provide a usable dense mapping for modern MIS on computationally constrained devices. CONCLUSION: The proposed BDIS-SLAM is a lightweight stereo dense SLAM system for MIS. It achieves 30 Hz on a modern single-core CPU in typical endoscopy/colonoscopy scenarios (image size around 640 × 480 ). BDIS-SLAM provides a low-cost solution for dense mapping in MIS and has the potential to be applied in surgical robots and AR systems. Code is available at https://github.com/JingweiSong/BDIS-SLAM .

Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans.

Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understanding tumor growth dynamics and designing personalized radiotherapy treatment plans.Mathematical models of GBM growth can complement the data in the prediction of spatial distributions of tumor cells. However, this requires estimating patient-specific parameters of the model from clinical data, which is a challenging inverse problem due to limited temporal data and the limited time between imaging and diagnosis. This work proposes a method that uses Physics-Informed Neural Networks (PINNs) to estimate patient-specific parameters of a reaction-diffusion PDE model of GBM growth from a single 3D structural MRI snapshot. PINNs embed both the data and the PDE into a loss function, thus integrating theory and data. Key innovations include the identification and estimation of characteristic non-dimensional parameters, a pre-training step that utilizes the non-dimensional parameters and a fine-tuning step to determine the patient specific parameters. Additionally, the diffuse domain method is employed to handle the complex brain geometry within the PINN framework. Our method is validated both on synthetic and patient datasets, and shows promise for real-time parametric inference in the clinical setting for personalized GBM treatment.

Automating the Detection of IV Fluid Contamination Using Unsupervised Machine Learning.

BACKGROUND: Intravenous (IV) fluid contamination is a common cause of preanalytical error that can delay or misguide treatment decisions, leading to patient harm. Current approaches for detecting contamination rely on delta checks, which require a prior result, or manual technologist intervention, which is inefficient and vulnerable to human error. Supervised machine learning may provide a means to detect contamination, but its implementation is hindered by its reliance on expert-labeled training data. An automated approach that is accurate, reproducible, and practical is needed. METHODS: A total of 25 747 291 basic metabolic panel (BMP) results from 312 721 patients were obtained from the laboratory information system (LIS). A Uniform Manifold Approximation and Projection (UMAP) model was trained and tested using a combination of real patient data and simulated IV fluid contamination. To provide an objective metric for classification, an "enrichment score" was derived and its performance assessed. Our current workflow was compared to UMAP predictions using expert chart review. RESULTS: UMAP embeddings from real patient results demonstrated outliers suspicious for IV fluid contamination when compared with the simulated contamination's embeddings. At a flag rate of 3 per 1000 results, the positive predictive value (PPV) was adjudicated to be 0.78 from 100 consecutive positive predictions. Of these, 58 were previously undetected by our current clinical workflows, with 49 BMPs displaying a total of 56 critical results. CONCLUSIONS: Accurate and automatable detection of IV fluid contamination in BMP results is achievable without curating expertly labeled training data.

TRAF6 and TRAF2/3 Binding Motifs in CD40 Differentially Regulate B Cell Function in T-Dependent Antibody Responses and Dendritic Cell Function in Experimental Autoimmune Encephalomyelitis.

Expression of the costimulatory molecule CD40 on both B cells and dendritic cells (DCs) is required for induction of experimental autoimmune encephalomyelitis (EAE), and cell-autonomous CD40 expression on B cells is required for primary T-dependent (TD) Ab responses. We now ask whether the function of CD40 expressed by different cell types in these responses is mediated by the same or different cytoplasmic domains. CD40 has been reported to possess multiple cytoplasmic domains, including distinct TRAF6 and TRAF2/3 binding motifs. To elucidate the in vivo function of these motifs in B cells and DCs involved in EAE and TD germinal center responses, we have generated knock-in mice containing distinct CD40 cytoplasmic domain TRAF-binding site mutations and have used these animals, together with bone marrow chimeric mice, to assess the roles that these motifs play in CD40 function. We found that both TRAF2/3 and TRAF6 motifs of CD40 are critically involved in EAE induction and demonstrated that this is mediated by a role of both motifs for priming of pathogenic T cells by DCs. In contrast, the TRAF2/3 binding motif, but not the TRAF6 binding motif, is required for B cell CD40 function in TD high-affinity Ab responses. These data demonstrate that the requirements for expression of specific TRAF-binding CD40 motifs differ for B cells or DCs that function in specific immune responses and thus identify targets for intervention to modulate these responses.

The effects of preconception and early gestation SARS-CoV-2 infection on pregnancy outcomes and placental pathology.

OBJECTIVE: To evaluate if peri-pregnancy timing of a PCR+ test for SARS-CoV-2 RNA affects pregnancy outcomes and placental pathology. METHODS: This is a retrospective cohort study conducted in a tertiary center. Pregnancy outcomes and placental pathology were compiled for women who tested positive for SARS-CoV-2 RNA from a nasopharyngeal swab assessed by RT-PCR. The population comprised four groups that were PCR+ preconception (T0) or in the 1st (T1), 2nd (T2), or 3rd (T3) trimester of pregnancy. A fifth, control group (TC) tested PCR- for SARS-CoV-2 before delivery. RESULTS: Seventy-one pregnancies were studied. The T0 group exhibited lower gestational ages at delivery, had infants with the lowest birth weights, the highest rate of pregnancy loss before 20 weeks. Features of maternal vascular malperfusion and accelerated villous maturation were prominent findings in the histopathology of placentas from women PCR+ for SARS-CoV-2 RNA, especially in the T0 and the T1 groups. CONCLUSION: Women at highest risk for pregnancy complications are those who test PCR+ for viral RNA preconception or during first trimester of pregnancy.

CD40 Drives Central Nervous System Autoimmune Disease by Inducing Complementary Effector Programs via B Cells and Dendritic Cells.

Costimulatory CD40 plays an essential role in autoimmune diseases, including experimental autoimmune encephalomyelitis (EAE), a murine model of human multiple sclerosis (MS). However, how CD40 drives autoimmune disease pathogenesis is not well defined. Here, we used a conditional knockout approach to determine how CD40 orchestrates a CNS autoimmune disease induced by recombinant human myelin oligodendrocyte glycoprotein (rhMOG). We found that deletion of CD40 in either dendritic cells (DCs) or B cells profoundly reduced EAE disease pathogenesis. Mechanistically, CD40 expression on DCs was required for priming pathogenic Th cells in peripheral draining lymph nodes and promoting their appearance in the CNS. By contrast, B cell CD40 was essential for class-switched MOG-specific Ab production, which played a crucial role in disease pathogenesis. In fact, passive transfer of MOG-immune serum or IgG into mice lacking CD40 on B cells but not DCs reconstituted autoimmune disease, which was associated with inundation of the spinal cord parenchyma by Ig and complement. These data demonstrate that CD40 supports distinct effector programs in B cells and DCs that converge to drive a CNS autoimmune disease and identify targets for intervention.

Translation suppression underlies the restrained COVID-19 mRNA vaccine response in the high-risk immunocompromised group.

Background: Immunocompromised (IC) patients show diminished immune response to COVID-19 mRNA vaccines (Co-mV). To date, there is no 'empirical' evidence to link the perturbation of translation, a rate-limiting step for mRNA vaccine efficiency (VE), to the dampened response of Co-mV. Materials and methods: Impact of immunosuppressants (ISs), tacrolimus (T), mycophenolate (M), rapamycin/sirolimus (S), and their combinations on Pfizer Co-mV translation were determined by the Spike (Sp) protein expression following Co-mV transfection in HEK293 cells. In vivo impact of ISs on SARS-CoV-2 spike specific antigen (SpAg) and associated antibody levels (IgGSp) in serum were assessed in Balb/c mice after two doses (2D) of the Pfizer vaccine. Spike Ag and IgGSp levels were assessed in 259 IC patients and 50 healthy controls (HC) who received 2D of Pfizer or Moderna Co-mV as well as in 67 immunosuppressed solid organ transplant (SOT) patients and 843 non-transplanted (NT) subjects following three doses (3D) of Co-mV. Higher Co-mV concentrations and transient drug holidays were evaluated. Results: We observed significantly lower IgGSP response in IC patients (p<0.0001) compared to their matched controls in 2D and 3D Co-mV groups. IC patients on M or S showed a profound dampening of IgGSP response relative to those that were not on these drugs. M and S, when used individually or in combination, significantly attenuated the Co-mV-induced Sp expression, whereas T did not exert significant influence. Sirolimus combo pretreatment in vivo significantly attenuated the Co-mV induced IgMSp and IgGSp production, which correlated with a decreasing trend in the early levels (after day 1) of Co-mV induced Sp immunogen levels. Neither higher Co-mV concentrations (6µg) nor withholding S for 1-day could overcome the inhibition of Sp protein levels. Interestingly, 3-days S holiday or using T alone rescued Sp levels in vitro. Conclusions: This is the first study to demonstrate that ISs, sirolimus and mycophenolate inhibited Co-mV-induced Sp protein synthesis via translation repression. Selective use of tacrolimus or drug holiday of sirolimus can be a potential means to rescue translation-dependent Sp protein production. These findings lay a strong foundation for guiding future studies aimed at improving Co-mV responses in high-risk IC patients.

Progress in symmetry preserving robot perception and control through geometry and learning.

This article reports on recent progress in robot perception and control methods developed by taking the symmetry of the problem into account. Inspired by existing mathematical tools for studying the symmetry structures of geometric spaces, geometric sensor registration, state estimator, and control methods provide indispensable insights into the problem formulations and generalization of robotics algorithms to challenging unknown environments. When combined with computational methods for learning hard-to-measure quantities, symmetry-preserving methods unleash tremendous performance. The article supports this claim by showcasing experimental results of robot perception, state estimation, and control in real-world scenarios.

Next-Generation Cancer Magnetic Resonance Imaging With Tumor-Targeted Alkylphosphocholine Metal Analogs.

OBJECTIVES: In an effort to exploit the elevated need for phospholipids displayed by cancer cells relative to normal cells, we have developed tumor-targeted alkylphosphocholines (APCs) as broad-spectrum cancer imaging and therapy agents. Radioactive APC analogs have exhibited selective uptake and prolonged tumor retention in over 50 cancer types in preclinical models, as well as over 15 cancer types in over a dozen clinical trials. To push the structural limits of this platform, we recently added a chelating moiety capable of binding gadolinium and many other metals for cancer-targeted magnetic resonance imaging (MRI), positron emission tomography imaging, and targeted radionuclide therapy. The aim of this work was to synthesize, characterize, and validate the tumor selectivity of a new broad-spectrum, tumor-targeted, macrocyclic MRI chelate, Gd-NM600, in xenograft and orthotopic tumor models. A secondary aim was to identify and track the in vivo chemical speciation and spatial localization of this new chelate Gd-NM600 in order to assess its Gd deposition properties. MATERIALS AND METHODS: T1 relaxivities of Gd-NM600 were characterized in water and plasma at 1.5 T and 3.0 T. Tumor uptake and subcellular localization studies were performed using transmission electron microscopy. We imaged 8 different preclinical models of human cancer over time and compared the T1-weighted imaging results to that of a commercial macrocyclic Gd chelate, Gd-DOTA. Finally, matrix-assisted laser desorption and ionization-mass spectrometry imaging was used to characterize and map the tissue distribution of the chemical species of Gd-NM600. RESULTS: Gd-NM600 exhibits high T1 relaxivity (approximately 16.4 s-1/mM at 1.5 T), excellent tumor uptake (3.95 %ID/g at 48 hours), prolonged tumor retention (7 days), and MRI conspicuity. Moreover, minimal tumor uptake saturability of Gd-NM600 was observed. Broad-spectrum tumor-specific uptake was demonstrated in 8 different human cancer models. Cancer cell uptake of Gd-NM600 via endosomal internalization and processing was revealed with transmission electron microscopy. Importantly, tissue mass spectrometry imaging successfully interrogated the spatial localization and chemical speciation of Gd compounds and also identified breakdown products of Gd species. CONCLUSIONS: We have introduced a new macrocyclic cancer-targeted Gd chelate that achieves broad-spectrum tumor uptake and prolonged retention. Furthermore, we have demonstrated in vivo stability of Gd-NM600 by ultrahigh resolution MS tissue imaging. A tumor-targeted contrast agent coupled with the enhanced imaging resolution of MRI relative to positron emission tomography may transform oncologic imaging.

Stain-free detection of embryo polarization using deep learning.

Polarization of the mammalian embryo at the right developmental time is critical for its development to term and would be valuable in assessing the potential of human embryos. However, tracking polarization requires invasive fluorescence staining, impermissible in the in vitro fertilization clinic. Here, we report the use of artificial intelligence to detect polarization from unstained time-lapse movies of mouse embryos. We assembled a dataset of bright-field movie frames from 8-cell-stage embryos, side-by-side with corresponding images of fluorescent markers of cell polarization. We then used an ensemble learning model to detect whether any bright-field frame showed an embryo before or after onset of polarization. Our resulting model has an accuracy of 85% for detecting polarization, significantly outperforming human volunteers trained on the same data (61% accuracy). We discovered that our self-learning model focuses upon the angle between cells as one known cue for compaction, which precedes polarization, but it outperforms the use of this cue alone. By compressing three-dimensional time-lapsed image data into two-dimensions, we are able to reduce data to an easily manageable size for deep learning processing. In conclusion, we describe a method for detecting a key developmental feature of embryo development that avoids clinically impermissible fluorescence staining.

Comparison of 6 SARS-CoV-2 Molecular Methods and Correlation With the Cycle Threshold Distribution in Clinical Specimens.

BACKGROUND: The detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patient samples is of critical importance in the management of patients and monitoring transmission in the population. However, data on the analytical performance characteristics for detection of SARS-CoV-2 in clinical specimens between individual targets within the same platform, and among different analytical platforms, are limited. METHODS: Here we evaluated the performance of 6 different sample-to-answer SARS-CoV-2 detection methods-Roche cobas 6800, Cepheid GeneXpert, Diasorin Simplexa, Luminex Aries emergency use authorization (EUA), Luminex Aries research use only (RUO), and bioMérieux BioFire-in clinical specimens with a range of viral loads. RESULTS: The positive percentage agreement between the Roche cobas 6800 and GeneXpert was 100%, Diasorin 95%, Aries EUA 74%, Aries RUO 83%, and BioFire 97%. Notably, in samples with cycle threshold (Ct) values below 30 for the E gene on the Roche cobas 6800 platform, we found 100% positive agreement among all platforms. Given these results, we examined the distribution of over 10 000 Ct values of all positive specimens from individuals at our institution on the Roche cobas platform. Nearly 60% of specimens from asymptomatic individuals had a PCR Ct value >30 as measured using the cobas 6800 assay E gene. CONCLUSIONS: Our results demonstrate performance characteristics between different platforms by Ct value and provide data regarding the distribution of viral RNA present in positive specimens.

Comparison of serratus anterior plane block with epidural and paravertebral block in critically ill trauma patients with multiple rib fractures.

BACKGROUND: Pain from rib fractures is associated with significant pulmonary morbidity. Epidural and paravertebral blocks (EPVBs) have been recommended as part of a multimodal approach to rib fracture pain, but their utility is often challenging in the trauma intensive care unit (ICU). The serratus anterior plane block (SAPB) has potential as an alternative approach for chest wall analgesia. METHODS: This retrospective study compared critically injured adults sustaining multiple rib fractures who had SAPB (n=14) to EPVB (n=25). Patients were matched by age, body mass index, American Society of Anesthesiology Physical Status, whether the patient required intubation, number of rib fractures and injury severity score. Outcome measures included hospital length of stay, ICU length of stay, preblock and post block rapid shallow breathing index (RSBI) in intubated patients, pain scores and morphine equivalent doses administered 24-hour preblock and post-block in non-intubated patients, and mortality. RESULTS: There were no demographic differences between the two groups after matching. Nearly all of the patients who received either SAPB or EPVB demonstrated a reduction in RSBI or pain scores. The preblock RSBI was higher in the serratus anterior plane block group, but there was no difference between any of the other outcome measures. DISCUSSION: This retrospective study of our institutional data suggests no difference in efficacy between the serratus anterior plane block and neuraxial block for traumatic rib fracture pain in critically ill patients, but the sample size was too small to show statistical equivalence. Serratus anterior plane block is technically easier to perform with fewer theoretical contraindications compared with traditional neuraxial block. Further study with prospective comparative trials is warranted. LEVEL OF EVIDENCE: Retrospective matched cohort; Level IV.

A multi-modal diagnostic model improves detection of cardiac amyloidosis among patients with diagnostic confirmation by cardiac biopsy.

BACKGROUND: Timely recognition of cardiac amyloidosis is clinically important, but the diagnosis is frequently delayed. OBJECTIVES: We sought to identify a multi-modality approach with the highest diagnostic accuracy in patients evaluated by cardiac biopsy, the diagnostic gold standard. METHODS: Consecutive patients (N = 242) who underwent cardiac biopsy for suspected amyloidosis within an 18-year period were retrospectively identified. Cardiac biomarker, ECG, and echocardiography results were examined for correlation with biopsy-proven disease. A prediction model for cardiac amyloidosis was derived using multivariable logistic regression. RESULTS: The overall cohort was characterized by elevated BNP (median 727 ng/mL), increased left ventricular wall thickness (IWT; median 1.7 cm), and reduced voltage-to-mass ratio (median 0.06 mm/[g/m2]). One hundred and thirteen patients (46%) had either light chain (n = 53) or transthyretin (n = 60) amyloidosis by cardiac biopsy. A prediction model including age, relative wall thickness, left atrial pressure by E/e', and low limb lead voltage (<0.5 mV) showed good discrimination for cardiac amyloidosis with an optimism-corrected c-index of 0.87 (95% CI 0.83-0.92). The diagnostic accuracy of this model (79% sensitivity, 84% specificity) surpassed that of traditional screening parameters, such as IWT in the absence of left ventricular hypertrophy on ECG (98% sensitivity, 20% specificity) and IWT with low limb lead voltage (49% sensitivity, 91% specificity). CONCLUSION: Among patients with an advanced infiltrative cardiomyopathy phenotype, traditional biomarker, ECG, and echocardiography-based screening tests have limited individual diagnostic utility for cardiac amyloidosis. A prediction algorithm including age, relative wall thickness, E/e', and low limb lead voltage improves the detection of cardiac biopsy-proven disease.

Large-Scale Assessment of Scan-Time Variability and Multiple-Procedure Efficiency for Cross-Sectional Neuroradiological Exams in Clinical Practice.

Scheduling of CT and MR exams requires reasonable estimates for expected scan duration. However, scan-time variability and efficiency gains from combining multiple exams are not quantitatively well characterized. In this work, we developed an informatics approach to quantify typical duration, duration variability, and multiple-procedure efficiency on a large scale, and used the approach to analyze 48,766 CT- and MR-based neuroradiological exams performed over one year. We found MR exam durations demonstrated higher absolute variability, but lower relative variability and lower multiple-procedure efficiency, compared to CT exams (p < 0.001). Our approach enables quantification of real-world operational performance and variability to inform optimal patient scheduling, efficient resource utilization, and sustainable service planning.

177Lu-NM600 Targeted Radionuclide Therapy Extends Survival in Syngeneic Murine Models of Triple-Negative Breast Cancer.

There is a clinically unmet need for effective treatments for triple-negative breast cancer (TNBC), as it remains the most aggressive subtype of breast cancer. Herein, we demonstrate a promising strategy using a tumor-targeting alkylphosphocholine (NM600) for targeted radionuclide therapy of TNBC. Methods: NM600 was radiolabeled with 86Y for PET imaging and 177Lu for targeted radionuclide therapy. 86Y-NM600 PET imaging was performed on female BALB/C mice bearing syngeneic 4T07 (nonmetastatic) and 4T1 (metastatic) TNBC tumor grafts (n = 3-5). Quantitative data derived from a PET-image region-of-interest analysis, which was corroborated by ex vivo biodistribution, were used to estimate the dosimetry of 177Lu-NM600 treatments. Weight measurement, complete blood counts, and histopathology analysis were performed to determine 177Lu-NM600 toxicity in naïve BALB/C mice administered 9.25 or 18.5 MBq. Groups of mice bearing 4T07 or 4T1 grafts (n = 5-6) received excipient or 9.25 or 18.5 MBq of 177Lu-NM600 as a single or fractionated schedule, and tumor growth and overall survival were monitored. Results: Excellent tumor targeting and rapid normal-tissue clearance of 86Y-NM600 were noted in both 4T07 and 4T1 murine models. Ex vivo biodistribution corroborated the accuracy of the PET data and validated 86Y-NM600 as a surrogate for 177Lu-NM600. 177Lu-NM600 dosimetry showed absorbed doses of 2.04 ± 0.32 and 1.68 ± 0.06 Gy/MBq to 4T07 and 4T1 tumors, respectively, which were larger than those delivered to liver (1.28 ± 0.09 Gy/MBq) and to bone marrow (0.31 ± 0.05 Gy/MBq). The 177Lu-NM600 injected activities used for treatment were well tolerated and resulted in significant tumor growth inhibition and prolonged overall survival in both tested TNBC models. A complete response was attained in 60% of treated mice bearing 4T07 grafts. Conclusion: Overall, our results suggest that 177Lu-NM600 targeted radionuclide therapy has potential for TNBC and merits further exploration in a clinical setting.

Optimizing management of replacement fluids for therapeutic plasma exchange: Use of an automated mathematical model to predict post-procedure fibrinogen and antithrombin levels in high-risk patients.

BACKGROUND: Therapeutic plasma exchange (TPE) utilizes an extracorporeal circuit to remove pathologic proteins causing serious illness. When processing a patient's entire blood volume through an extracorporeal circuit, proteins responsible for maintaining hemostatic system homeostasis can reach critically low levels if replacement fluid types and volumes are not carefully titrated, which may increase complications. METHODS: The charts from 27 patients undergoing 46 TPE procedures were reviewed to evaluate the accuracy of our predictive mathematical model, utilizing the following patient information: weight, hematocrit, pre- and post-TPE factor levels (fibrinogen, n = 46, and antithrombin, n = 23), process volume and volumes of fluids (eg, plasma, albumin, and normal saline) administered during TPE and adverse events during and after TPE. RESULTS: Altogether, 25% of patients experienced minor adverse events that resolved spontaneously or with management. There were no bleeding or thrombotic complications. The mean difference between predicted and measured post-TPE fibrinogen concentrations was -0.29 mg/dL (SD ±23.0, range -59 to 37), while percent difference between measured and predicted fibrinogen concentration was 0.94% (SD ±10.8, range of -22 to 19). The mean difference between predicted and measured post-TPE antithrombin concentrations were 0.89% activity (SD ±10.0, range -23 to 14), while mean percent difference between predicted and measured antithrombin concentrations was 3.87% (SD ±14.5, range -25 to 38). CONCLUSIONS: Our model reliably predicts post-TPE fibrinogen and antithrombin concentrations, and may help optimize patient management and attenuate complications.

In Silico Docking of Alkylphosphocholine Analogs to Human Serum Albumin Predicts Partitioning and Pharmacokinetics.

Alkylphosphocholine (APC) analogs are a novel class of broad-spectrum tumor-targeting agents that can be used for both diagnosis and treatment of cancer. The potential for clinical translation for APC analogs will strongly depend on their pharmacokinetic (PK) profiles. The aim of this work was to understand how the chemical structures of various APC analogs impact binding and PK. To achieve this aim, we performed in silico docking analysis, in vitro and in vivo partitioning experiments, and in vivo PK studies. Our results have identified 7 potential high-affinity binding sites of these compounds on human serum albumin (HSA) and suggest that the size of the functional group directly influences the albumin binding, partitioning, and PK. Namely, the bulkier the functional groups, the weaker the agent binds to albumin, the more the agent partitions onto lipoproteins, and the less time the agent spends in circulation. The results of these experiments provide novel molecular insights into the binding, partitioning, and PK of this class of compounds and similar molecules as well as suggest pharmacological strategies to alter their PK profiles. Importantly, our methodology may provide a way to design better drugs by better characterizing the PK profile for lead compound optimization.